From 116fbf57af24c70d24588f31c695b4d2a30c28a0 Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Sat, 7 Oct 2023 22:26:30 +0800 Subject: [PATCH 01/32] feat(udf): support `datediff` dates before 1900 (#3499) --- hybridse/src/codegen/udf_ir_builder_test.cc | 42 +++++++- hybridse/src/udf/default_udf_library.cc | 28 +++--- hybridse/src/udf/udf.cc | 106 +++++++++++++++----- hybridse/src/udf/udf.h | 10 +- 4 files changed, 134 insertions(+), 52 deletions(-) diff --git a/hybridse/src/codegen/udf_ir_builder_test.cc b/hybridse/src/codegen/udf_ir_builder_test.cc index 13a82a1a925..6cd82be7859 100644 --- a/hybridse/src/codegen/udf_ir_builder_test.cc +++ b/hybridse/src/codegen/udf_ir_builder_test.cc @@ -1078,14 +1078,21 @@ TEST_F(UdfIRBuilderTest, DateDiff) { CheckUdf, Nullable, Nullable>(func_name, 44924, "2022-12-31", "1900-01-01"); CheckUdf, Nullable, Nullable>(func_name, 50, "20220620", "2022-05-01 11:11:11"); - CheckUdf, Nullable, Nullable>(func_name, 0, "2022-05-01", "20220501"); + CheckUdf, Nullable, Nullable>(func_name, 0, + "2022-05-01", "20220501"); CheckUdf, Nullable, Nullable>(func_name, nullptr, "2022-02-29", "20220501"); - CheckUdf, Nullable, Nullable>(func_name, nullptr, "1899-05-20", - "2020-05-20"); + CheckUdf, Nullable, Nullable>(func_name, 9, "1899-05-20", "1899-05-11"); CheckUdf, Nullable, Nullable>(func_name, nullptr, "2022-05-40", "2020-05-20"); - CheckUdf, Nullable, Nullable>(func_name, nullptr, "2020-05-20", - "1899-05-20"); + CheckUdf, Nullable, Nullable>(func_name, -30, "1199-10-12", "1199-11-11"); + // rfc3399 full format + CheckUdf, Nullable, Nullable>( + func_name, 20, "2000-01-01t00:12:00.1+08:00", "1999-12-12T12:12:12+08:00"); + CheckUdf, Nullable, Nullable>( + func_name, 19, "2000-01-01t00:12:00.1+08:00", "1999-12-12T20:12:12Z"); + CheckUdf, Nullable, Nullable>( + func_name, 20, "2000-01-01t06:12:00.1+08:00", "1999-12-12T12:12:12Z"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, nullptr, "20220501"); CheckUdf, Nullable, Nullable>(func_name, nullptr, "2022-05-01", nullptr); CheckUdf, Nullable, Nullable>(func_name, nullptr, nullptr, nullptr); @@ -1093,6 +1100,8 @@ TEST_F(UdfIRBuilderTest, DateDiff) { // mix types CheckUdf, Nullable, Nullable>(func_name, -19, "2022-05-01", Date(2022, 5, 20)); CheckUdf, Nullable, Nullable>(func_name, 19, Date(2022, 5, 20), "2022-05-01"); + CheckUdf, Nullable, Nullable>(func_name, 3, Date(1900, 1, 1), "1899-12-29"); + CheckUdf, Nullable, Nullable>(func_name, -3, "1899-12-29", Date(1900, 1, 1)); CheckUdf, Nullable, Nullable>(func_name, nullptr, nullptr, "2022-05-01"); CheckUdf, Nullable, Nullable>(func_name, nullptr, Date(2022, 5, 20), nullptr); CheckUdf, Nullable, Nullable>(func_name, nullptr, nullptr, nullptr); @@ -1101,6 +1110,29 @@ TEST_F(UdfIRBuilderTest, DateDiff) { CheckUdf, Nullable, Nullable>(func_name, nullptr, nullptr, nullptr); } +TEST_F(UdfIRBuilderTest, DateDiffNull) { + auto func_name = "datediff"; + + // out-of-range format + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1900-01-00", + "1999-12-12T12:12:12Z"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1977-13-01", + "1999-12-12T12:12:12Z"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, "19771232", + "1999-12-12T12:12:12Z"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1999-12-12T25:12:12Z", + "1999-12-12T12:12:12Z"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1999-12-12T12:66:12Z", + "1999-12-12T12:12:12Z"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1999-12-12T12:00:61Z", + "1999-12-12T12:12:12Z"); + + // invalid format + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1999-12-12T12:12:12Z", + "202 2-12-2 9"); + CheckUdf, Nullable, Nullable>(func_name, nullptr, "1999-12-12T12:12:12Z", + "12:30:30"); +} class UdfIRCastTest : public ::testing::TestWithParam>> {}; diff --git a/hybridse/src/udf/default_udf_library.cc b/hybridse/src/udf/default_udf_library.cc index f2c9bc1afd8..8b98212fffb 100644 --- a/hybridse/src/udf/default_udf_library.cc +++ b/hybridse/src/udf/default_udf_library.cc @@ -2591,16 +2591,21 @@ void DefaultUdfLibrary::InitTimeAndDateUdf() { }); RegisterExternal("datediff") - .args(reinterpret_cast(static_cast(v1::date_diff))) - .return_by_arg(true) - .returns>() + .args(static_cast(v1::date_diff)) .doc(R"( @brief days difference from date1 to date2 Supported date string style: - yyyy-mm-dd - yyyymmdd - - yyyy-mm-dd hh:mm:ss + - yyyy-mm-dd HH:MM:SS + - yyyy-mm-ddTHH:MM:SS.fff+HH:MM (RFC3399 format) + + Dates from string are transformed into the same time zone (which is currently always UTC+8) before differentiation, + dates from date type by default is at UTC+8, you may see a +1/-1 difference if the two date string have different time zones. + + Hint: since openmldb date type limits range from year 1900, to datadiff from/to a date before + 1900, pass it as string. Example: @@ -2614,20 +2619,11 @@ void DefaultUdfLibrary::InitTimeAndDateUdf() { @endcode @since 0.7.0)"); RegisterExternal("datediff") - .args( - reinterpret_cast(static_cast(v1::date_diff))) - .return_by_arg(true) - .returns>(); + .args(static_cast(v1::date_diff)); RegisterExternal("datediff") - .args( - reinterpret_cast(static_cast(v1::date_diff))) - .return_by_arg(true) - .returns>(); + .args(static_cast(v1::date_diff)); RegisterExternal("datediff") - .args( - reinterpret_cast(static_cast(v1::date_diff))) - .return_by_arg(true) - .returns>(); + .args(static_cast(v1::date_diff)); RegisterExternal("unix_timestamp") .args(reinterpret_cast(static_cast(v1::date_to_unix_timestamp))) diff --git a/hybridse/src/udf/udf.cc b/hybridse/src/udf/udf.cc index c32a58b8adb..2ec7033472f 100644 --- a/hybridse/src/udf/udf.cc +++ b/hybridse/src/udf/udf.cc @@ -16,7 +16,6 @@ #include "udf/udf.h" -#include #include #include @@ -28,6 +27,7 @@ #include "absl/strings/ascii.h" #include "absl/strings/str_replace.h" #include "absl/time/civil_time.h" +#include "absl/time/time.h" #include "base/iterator.h" #include "boost/date_time.hpp" #include "boost/date_time/gregorian/parsers.hpp" @@ -37,7 +37,7 @@ #include "codec/row.h" #include "codec/type_codec.h" #include "codegen/fn_ir_builder.h" -#include "farmhash.h" // NOLINT +#include "farmhash.h" #include "node/node_manager.h" #include "node/sql_node.h" #include "re2/re2.h" @@ -57,6 +57,20 @@ using openmldb::base::StringRef; using openmldb::base::Timestamp; using openmldb::base::Date; +// strftime()-like formatting options with extensions +// ref absl::FormatTime +static constexpr char DATE_FMT_YMD_1[] = "%E4Y-%m-%d"; +static constexpr char DATE_FMT_YMD_2[] = "%E4Y%m%d"; +static constexpr char DATE_FMT_YMDHMS[] = "%E4Y-%m-%d %H:%M:%S"; +static constexpr char DATE_FMT_RF3399_FULL[] = "%Y-%m-%d%ET%H:%M:%E*S%Ez"; + +// TODO(chenjing): 时区统一配置 +static constexpr int32_t TZ = 8; +static const absl::TimeZone DEFAULT_TZ = absl::FixedTimeZone(TZ * 60 * 60); +static constexpr time_t TZ_OFFSET = TZ * 3600000; +static constexpr int MAX_ALLOC_SIZE = 2 * 1024 * 1024; // 2M +bthread_key_t B_THREAD_LOCAL_MEM_POOL_KEY; + void hex(StringRef *str, StringRef *output) { std::ostringstream ss; for (uint32_t i=0; i < str->size_; i++) { @@ -104,12 +118,6 @@ void unhex(StringRef *str, StringRef *output, bool* is_null) { } } -// TODO(chenjing): 时区统一配置 -constexpr int32_t TZ = 8; -constexpr time_t TZ_OFFSET = TZ * 3600000; -constexpr int MAX_ALLOC_SIZE = 2 * 1024 * 1024; // 2M -bthread_key_t B_THREAD_LOCAL_MEM_POOL_KEY; - void trivial_fun() {} void dayofyear(int64_t ts, int32_t* out, bool* is_null) { @@ -818,7 +826,26 @@ void string_to_date(StringRef *str, Date *output, return; } -void date_diff(Date *date1, Date *date2, int *diff, bool *is_null) { +absl::StatusOr string_to_time(absl::string_view ref) { + absl::string_view fmt = DATE_FMT_RF3399_FULL; + if (19 == ref.size()) { + fmt = DATE_FMT_YMDHMS; + } else if (10 == ref.size()) { + fmt = DATE_FMT_YMD_1; + } else if (8 == ref.size()) { + fmt = DATE_FMT_YMD_2; + } + absl::Time tm; + std::string err; + bool ret = absl::ParseTime(fmt, ref, &tm, &err); + + if (!ret) { + return absl::InvalidArgumentError(err); + } + return tm; +} + +void date_diff(Date *date1, Date *date2, int32_t *diff, bool *is_null) { if (date1 == nullptr || date2 == nullptr || date1->date_ <= 0 || date2->date_ <= 0) { *is_null = true; return; @@ -838,36 +865,61 @@ void date_diff(Date *date1, Date *date2, int *diff, bool *is_null) { *is_null = false; } -void date_diff(StringRef *date1, StringRef *date2, int *diff, bool *is_null) { - Date d1; - string_to_date(date1, &d1, is_null); - if (*is_null) { +void date_diff(StringRef *date1, StringRef *date2, int32_t *diff, bool *is_null) { + auto t1 = string_to_time(absl::string_view(date1->data_, date1->size_)); + if (!t1.ok()) { + *is_null = true; return; } - Date d2; - string_to_date(date2, &d2, is_null); - if (*is_null) { + auto t2 = string_to_time(absl::string_view(date2->data_, date2->size_)); + if (!t2.ok()) { + *is_null = true; return; } - date_diff(&d1, &d2, diff, is_null); + + auto d1 = absl::ToCivilDay(t1.value(), DEFAULT_TZ); + auto d2 = absl::ToCivilDay(t2.value(), DEFAULT_TZ); + + *diff = d1 - d2; + *is_null = false; } -void date_diff(StringRef *date1, Date *date2, int *diff, bool *is_null) { - Date d1; - string_to_date(date1, &d1, is_null); - if (*is_null) { +void date_diff(StringRef *date1, Date *date2, int32_t *diff, bool *is_null) { + auto t1 = string_to_time(absl::string_view(date1->data_, date1->size_)); + if (!t1.ok()) { + *is_null = true; return; } - date_diff(&d1, date2, diff, is_null); + auto d1 = absl::ToCivilDay(t1.value(), DEFAULT_TZ); + + int32_t year, month, day; + if (!Date::Decode(date2->date_, &year, &month, &day)) { + *is_null = true; + return; + } + auto d2 = absl::CivilDay(year, month, day); + + *diff = d1 - d2; + *is_null = false; } -void date_diff(Date *date1, StringRef *date2, int *diff, bool *is_null) { - Date d2; - string_to_date(date2, &d2, is_null); - if (*is_null) { +void date_diff(Date *date1, StringRef *date2, int32_t *diff, bool *is_null) { + auto t2 = string_to_time(absl::string_view(date2->data_, date2->size_)); + if (!t2.ok()) { + *is_null = true; return; } - date_diff(date1, &d2, diff, is_null); + auto d2 = absl::ToCivilDay(t2.value(), DEFAULT_TZ); + + int32_t year, month, day; + if (!Date::Decode(date1->date_, &year, &month, &day)) { + *is_null = true; + return; + } + auto d1 = absl::CivilDay(year, month, day); + + *diff = d1 - d2; + *is_null = false; } // cast string to timestamp with yyyy-mm-dd or YYYY-mm-dd HH:MM:SS diff --git a/hybridse/src/udf/udf.h b/hybridse/src/udf/udf.h index c2f2d2dc6f0..a761e99f88b 100644 --- a/hybridse/src/udf/udf.h +++ b/hybridse/src/udf/udf.h @@ -367,10 +367,10 @@ void timestamp_to_date(Timestamp *timestamp, Date *output, bool *is_null); void date_to_string(Date *date, StringRef *output); -void date_diff(Date *date1, Date *date2, int *diff, bool *is_null); -void date_diff(StringRef *date1, StringRef *date2, int *diff, bool *is_null); -void date_diff(StringRef *date1, Date *date2, int *diff, bool *is_null); -void date_diff(Date *date1, StringRef *date2, int *diff, bool *is_null); +void date_diff(Date *date1, Date *date2, int32_t *diff, bool *is_null); +void date_diff(StringRef *date1, StringRef *date2, int32_t *diff, bool *is_null); +void date_diff(StringRef *date1, Date *date2, int32_t *diff, bool *is_null); +void date_diff(Date *date1, StringRef *date2, int32_t *diff, bool *is_null); void like(StringRef *name, StringRef *pattern, StringRef *escape, bool *out, bool *is_null); @@ -384,6 +384,8 @@ void regexp_like(StringRef *name, StringRef *pattern, bool *out, bool *is_null); void date_to_timestamp(Date *date, Timestamp *output, bool *is_null); void string_to_date(StringRef *str, Date *output, bool *is_null); +absl::StatusOr string_to_time(absl::string_view str); + void string_to_timestamp(StringRef *str, Timestamp *output, bool *is_null); void date_to_unix_timestamp(Date *date, int64_t *output, bool *is_null); void string_to_unix_timestamp(StringRef *str, int64_t *output, bool *is_null); From bcc0b1f4d633ea6c0c4ab9da182048913c1672c5 Mon Sep 17 00:00:00 2001 From: dl239 Date: Sun, 8 Oct 2023 10:26:53 +0800 Subject: [PATCH 02/32] docs: update version (#3517) --- CMakeLists.txt | 2 +- demo/Dockerfile | 2 +- java/hybridse-native/pom.xml | 2 +- java/hybridse-proto/pom.xml | 2 +- java/hybridse-sdk/pom.xml | 2 +- java/openmldb-batch/pom.xml | 2 +- java/openmldb-batchjob/pom.xml | 2 +- java/openmldb-common/pom.xml | 2 +- java/openmldb-jdbc/pom.xml | 2 +- java/openmldb-native/pom.xml | 2 +- java/openmldb-spark-connector/pom.xml | 2 +- java/openmldb-synctool/pom.xml | 2 +- java/openmldb-taskmanager/pom.xml | 2 +- java/pom.xml | 4 ++-- python/openmldb_sdk/setup.py | 2 +- python/openmldb_tool/setup.py | 2 +- test/integration-test/openmldb-test-python/install.sh | 2 +- 17 files changed, 18 insertions(+), 18 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index a9f10095c38..21066a3c505 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -36,7 +36,7 @@ endif() message (STATUS "CMAKE_BUILD_TYPE: ${CMAKE_BUILD_TYPE}") set(OPENMLDB_VERSION_MAJOR 0) set(OPENMLDB_VERSION_MINOR 8) -set(OPENMLDB_VERSION_BUG 2) +set(OPENMLDB_VERSION_BUG 3) function(get_commitid CODE_DIR COMMIT_ID) find_package(Git REQUIRED) diff --git a/demo/Dockerfile b/demo/Dockerfile index e6495931d35..6dc38d46c2b 100644 --- a/demo/Dockerfile +++ b/demo/Dockerfile @@ -25,7 +25,7 @@ COPY *_dist.yml /work/ ENV LANG=en_US.UTF-8 ENV SPARK_HOME=/work/openmldb/spark-3.2.1-bin-openmldbspark -ARG OPENMLDB_VERSION=0.8.2 +ARG OPENMLDB_VERSION=0.8.3 ENV OPENMLDB_VERSION="${OPENMLDB_VERSION}" RUN if [ "${USE_ADD_WHL}" = "true" ] ; then \ diff --git a/java/hybridse-native/pom.xml b/java/hybridse-native/pom.xml index e347b945b6c..629da3b0282 100644 --- a/java/hybridse-native/pom.xml +++ b/java/hybridse-native/pom.xml @@ -5,7 +5,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT ../pom.xml 4.0.0 diff --git a/java/hybridse-proto/pom.xml b/java/hybridse-proto/pom.xml index 83b28bdd95f..a78a0da61cf 100644 --- a/java/hybridse-proto/pom.xml +++ b/java/hybridse-proto/pom.xml @@ -4,7 +4,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT ../pom.xml 4.0.0 diff --git a/java/hybridse-sdk/pom.xml b/java/hybridse-sdk/pom.xml index e103c064280..ee37ccdf60f 100644 --- a/java/hybridse-sdk/pom.xml +++ b/java/hybridse-sdk/pom.xml @@ -6,7 +6,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT ../pom.xml 4.0.0 diff --git a/java/openmldb-batch/pom.xml b/java/openmldb-batch/pom.xml index a2a93ad4d3a..f2da581860d 100644 --- a/java/openmldb-batch/pom.xml +++ b/java/openmldb-batch/pom.xml @@ -7,7 +7,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT openmldb-batch diff --git a/java/openmldb-batchjob/pom.xml b/java/openmldb-batchjob/pom.xml index fddac8ffb82..408cb79e16d 100644 --- a/java/openmldb-batchjob/pom.xml +++ b/java/openmldb-batchjob/pom.xml @@ -7,7 +7,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT openmldb-batchjob diff --git a/java/openmldb-common/pom.xml b/java/openmldb-common/pom.xml index 8bd3e054cce..d42db9b7d54 100644 --- a/java/openmldb-common/pom.xml +++ b/java/openmldb-common/pom.xml @@ -5,7 +5,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT 4.0.0 openmldb-common diff --git a/java/openmldb-jdbc/pom.xml b/java/openmldb-jdbc/pom.xml index 3978579b373..d98f248d811 100644 --- a/java/openmldb-jdbc/pom.xml +++ b/java/openmldb-jdbc/pom.xml @@ -5,7 +5,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT ../pom.xml 4.0.0 diff --git a/java/openmldb-native/pom.xml b/java/openmldb-native/pom.xml index 8bd8a8399f3..b9ad048d640 100644 --- a/java/openmldb-native/pom.xml +++ b/java/openmldb-native/pom.xml @@ -5,7 +5,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT ../pom.xml 4.0.0 diff --git a/java/openmldb-spark-connector/pom.xml b/java/openmldb-spark-connector/pom.xml index 3f79972c60a..7431aae760f 100644 --- a/java/openmldb-spark-connector/pom.xml +++ b/java/openmldb-spark-connector/pom.xml @@ -6,7 +6,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT openmldb-spark-connector diff --git a/java/openmldb-synctool/pom.xml b/java/openmldb-synctool/pom.xml index a877d921eac..360f26e26be 100644 --- a/java/openmldb-synctool/pom.xml +++ b/java/openmldb-synctool/pom.xml @@ -6,7 +6,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT openmldb-synctool openmldb-synctool diff --git a/java/openmldb-taskmanager/pom.xml b/java/openmldb-taskmanager/pom.xml index 56aeef8b7c3..e983c4027e2 100644 --- a/java/openmldb-taskmanager/pom.xml +++ b/java/openmldb-taskmanager/pom.xml @@ -6,7 +6,7 @@ openmldb-parent com.4paradigm.openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT openmldb-taskmanager openmldb-taskmanager diff --git a/java/pom.xml b/java/pom.xml index 3a46ab4d5c1..00c893a4201 100644 --- a/java/pom.xml +++ b/java/pom.xml @@ -7,7 +7,7 @@ openmldb-parent pom openmldb - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT hybridse-sdk hybridse-native @@ -65,7 +65,7 @@ - 0.8.2-SNAPSHOT + 0.8.3-SNAPSHOT error 2.9.0 diff --git a/python/openmldb_sdk/setup.py b/python/openmldb_sdk/setup.py index 528250e1822..c96e2ae899b 100644 --- a/python/openmldb_sdk/setup.py +++ b/python/openmldb_sdk/setup.py @@ -18,7 +18,7 @@ setup( name='openmldb', - version='0.8.2a0', + version='0.8.3a0', author='OpenMLDB Team', author_email=' ', url='https://github.com/4paradigm/OpenMLDB', diff --git a/python/openmldb_tool/setup.py b/python/openmldb_tool/setup.py index 097b3c229c8..7b9a8dcf27f 100644 --- a/python/openmldb_tool/setup.py +++ b/python/openmldb_tool/setup.py @@ -18,7 +18,7 @@ setup( name="openmldb-tool", - version="0.8.2a0", + version='0.8.3a0', author="OpenMLDB Team", author_email=" ", url="https://github.com/4paradigm/OpenMLDB", diff --git a/test/integration-test/openmldb-test-python/install.sh b/test/integration-test/openmldb-test-python/install.sh index 9b16e934807..1f2babc873c 100644 --- a/test/integration-test/openmldb-test-python/install.sh +++ b/test/integration-test/openmldb-test-python/install.sh @@ -17,7 +17,7 @@ set -eE -x CURRENT_DIR=$(dirname "$0") -SPARK_VERSION=0.8.2 +SPARK_VERSION=0.8.3 pushd "${CURRENT_DIR}" cp -r ../../../openmldb ./ sed -i"" -e "s/OPENMLDB_MODE:=standalone/OPENMLDB_MODE:=cluster/g" openmldb/conf/openmldb-env.sh From 2224a6cef3e43be632367a1ad4803e94792c6064 Mon Sep 17 00:00:00 2001 From: HuangWei Date: Wed, 11 Oct 2023 16:07:41 +0800 Subject: [PATCH 03/32] build: thirdparty parallel compile option & fix centos6 build (#3492) * build: fix centos6 build * fix * fix * fix --- .github/workflows/other-os-build.yml | 46 +++++++++++++++++++--------- Makefile | 4 +-- docs/zh/deploy/compile.md | 22 ++++++++++--- steps/centos6_build.sh | 17 +++++++--- 4 files changed, 64 insertions(+), 25 deletions(-) diff --git a/.github/workflows/other-os-build.yml b/.github/workflows/other-os-build.yml index fcc99fb674b..aa63c3cc19a 100644 --- a/.github/workflows/other-os-build.yml +++ b/.github/workflows/other-os-build.yml @@ -78,41 +78,60 @@ jobs: shell: bash run: | cd /root/OpenMLDB + # centos6_build.sh will try build zetasql even cache hit, just ignore the failure IN_WORKFLOW=true bash steps/centos6_build.sh # bazel bin export PATH=$PATH:`pwd` source /opt/rh/devtoolset-8/enable if [[ "${USE_DEPS_CACHE}" != "true" ]]; then - echo "build thirdparty" - make thirdparty CMAKE_INSTALL_PREFIX=${OPENMLDB_PREFIX} BUILD_BUNDLE=ON NPROC=8 + echo "build thirdparty, make opt is better than nproc?" + make thirdparty CMAKE_INSTALL_PREFIX=${OPENMLDB_PREFIX} BUILD_BUNDLE=ON THIRD_PARTY_CMAKE_FLAGS=-DMAKEOPTS=-j8 + # 5.8G ./.deps, avail 8G rm -rf .deps/build # GitHub runner disk space is limited fi echo "build" + # 1.4G ./.deps, avail 13G + + # will failed if openmldb_sdk is on cmake -S . -B `pwd`/build -DCMAKE_PREFIX_PATH=`pwd`/.deps/usr -DCMAKE_BUILD_TYPE=RelWithDebInfo \ -DSQL_PYSDK_ENABLE=${SQL_PYSDK_ENABLE} -DSQL_JAVASDK_ENABLE=OFF \ -DTESTING_ENABLE=OFF -DCMAKE_INSTALL_PREFIX=${OPENMLDB_PREFIX} \ -DHYBRIDSE_TESTING_ENABLE=OFF -DEXAMPLES_ENABLE=OFF -DEXAMPLES_TESTING_ENABLE=OFF - cmake --build build --target install -- -j2 - # clean up to save disk space(~11G), don't know which is relative, build again in next step - rm -rf build + # target openmldb 6.7G ./build(no py/java), avail 5.2G + # openmldb+cp_python_sdk_so 7.7G ./build(has py), python just ~180M + # target 'install' cost more, preinstall/fast won't build all, so use install/fast if needed + # or https://cmake.org/cmake/help/latest/variable/CMAKE_SKIP_INSTALL_ALL_DEPENDENCY.html + cmake --build build --target openmldb cp_python_sdk_so -- -j2 + du -h --max-depth=1 + df -h + # if target above cost too much disk, make java build failed, try to rm build cache + # don't rm cache now cuz build java from emtpy will cost 20min + # rm build/hybridse build/src -rf if [[ "${SQL_JAVASDK_ENABLE}" == "ON" ]]; then echo "build java sdk" cmake -S . -B `pwd`/build -DCMAKE_PREFIX_PATH=`pwd`/.deps/usr -DCMAKE_BUILD_TYPE=RelWithDebInfo \ -DSQL_PYSDK_ENABLE=OFF -DSQL_JAVASDK_ENABLE=ON \ -DTESTING_ENABLE=OFF -DCMAKE_INSTALL_PREFIX=${OPENMLDB_PREFIX} \ -DHYBRIDSE_TESTING_ENABLE=OFF -DEXAMPLES_ENABLE=OFF -DEXAMPLES_TESTING_ENABLE=OFF - cmake --build build --target sql_javasdk_package -- -j2 + # if build the whole java, 7.6G ./build, 5.7G ./java, avail 331M + # so split it and build native only + # 7.6G ./build, 1.8G ./java, avail 5.2G + cmake --build build --target cp_native_so -- -j2 + du -h --max-depth=1 + df -h + rm build/hybridse build/src -rf + cd java + ./mvnw -pl openmldb-native clean package -DskipTests=true -Dscalatest.skip=true -Dwagon.skip=true -Dmaven.test.skip=true --batch-mode fi - - - name: package - run: | - tar czf ${{ env.OPENMLDB_PREFIX }}.tar.gz ${{ env.OPENMLDB_PREFIX }}/ + rm build/hybridse build/src -rf + du -h --max-depth=1 + df -h - name: upload binary uses: actions/upload-artifact@v2 with: - path: openmldb-*.tar.gz - name: binary-package + path: build/bin/openmldb + name: binary - name: upload java native if: ${{ env.SQL_JAVASDK_ENABLE == 'ON' }} @@ -127,8 +146,7 @@ jobs: with: name: python-whl path: | - python/openmldb_sdk/dist/openmldb*.whl - + python/openmldb_sdk/dist/openmldb*.whl # TODO(hw): upload cxx sdk # macos no need to build thirdparty, but binary/os needs to be built on each os diff --git a/Makefile b/Makefile index 74274755b4b..697b12923af 100644 --- a/Makefile +++ b/Makefile @@ -154,7 +154,7 @@ thirdparty-fast: if [ "$$new_zetasql_version" != "$(ZETASQL_VERSION)" ] ; then \ echo "[deps]: thirdparty up-to-date. reinstall zetasql from $(ZETASQL_VERSION) to $$new_zetasql_version"; \ $(MAKE) thirdparty-configure; \ - $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) -j $(NPROC) --target zetasql; \ + $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target zetasql; \ else \ echo "[deps]: all up-to-date. zetasql already installed with version: $(ZETASQL_VERSION)"; \ fi; \ @@ -166,7 +166,7 @@ thirdparty-fast: # third party compiled code install to 'OpenMLDB/.deps/usr', source code install to 'OpenMLDB/thirdsrc' thirdparty: thirdparty-configure - $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) -j $(NPROC) + $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) thirdparty-configure: $(CMAKE_PRG) -S third-party -B $(THIRD_PARTY_BUILD_DIR) -DSRC_INSTALL_DIR=$(THIRD_PARTY_SRC_DIR) -DDEPS_INSTALL_DIR=$(THIRD_PARTY_DIR) $(THIRD_PARTY_CMAKE_FLAGS) diff --git a/docs/zh/deploy/compile.md b/docs/zh/deploy/compile.md index aec38f6a5a3..896009ca2ce 100644 --- a/docs/zh/deploy/compile.md +++ b/docs/zh/deploy/compile.md @@ -110,7 +110,7 @@ make CMAKE_BUILD_TYPE=Debug - CMAKE_EXTRA_FLAGS: 传递给 cmake 的额外参数 - 默认: ‘’ + 默认: '' - BUILD_BUNDLED: 从源码编译 thirdparty 依赖，而不是下载预编译包 @@ -124,6 +124,9 @@ make CMAKE_BUILD_TYPE=Debug 默认: all +- THIRD_PARTY_CMAKE_FLAGS: 编译thirdparty时可以配置额外参数。例如，配置每个thirdparty项目并发编译，`THIRD_PARTY_CMAKE_FLAGS=-DMAKEOPTS=-j8`。thirdparty不受NPROC影响，thirdparty的多项目将会串行执行。 + 默认：'' + ### 并发编译Java SDK ``` @@ -185,14 +188,25 @@ docker run -it -v`pwd`:/root/OpenMLDB ghcr.io/4paradigm/centos6_gcc7_hybridsql b ```bash cd OpenMLDB bash steps/centos6_build.sh +# THIRD_PARTY_CMAKE_FLAGS=-DMAKEOPTS=-j8 bash steps/centos6_build.sh # run fast when build single project # OPENMLDB_SOURCE=true bash steps/centos6_build.sh -# SQL_JAVASDK_ENABLE=ON SQL_PYSDK_ENABLE=ON NRPOC=8 bash steps/centos6_build.sh +# SQL_JAVASDK_ENABLE=ON SQL_PYSDK_ENABLE=ON NPROC=8 bash steps/centos6_build.sh # NPROC will build openmldb in parallel, thirdparty should use THIRD_PARTY_CMAKE_FLAGS ``` +本地2.20GHz CPU，SSD硬盘，32线程编译三方库与OpenMLDB主体，耗时参考： +`THIRD_PARTY_CMAKE_FLAGS=-DMAKEOPTS=-j32 SQL_JAVASDK_ENABLE=ON SQL_PYSDK_ENABLE=ON NPROC=32 bash steps/centos6_build.sh` +- thirdparty（不包括下载src时间）~40m：zetasql打patch 13m，所有thirdparty编译30m +- OpenMLDB 本体，包括python和java native，~12min + #### 云编译 -Fork OpenMLDB仓库后，可以使用在`Actions`中触发workflow `Other OS Build`，编译产出在`Actions`的`Artifacts`中。workflow 配置 `os name`为`centos6`， -如果不需要Java或Python SDK，可配置`java sdk enable`或`python sdk enable`为`OFF`，节约编译时间。 +Fork OpenMLDB仓库后，可以使用在`Actions`中触发workflow `Other OS Build`，编译产出在`Actions`的`Artifacts`中。workflow 配置方式： +- 不要更换`Use workflow from`为某个tag，可以是其他分支。 +- 选择`os name`为`centos6`。 +- 如果不是编译main分支，在`The branch, tag or SHA to checkout, otherwise use the branch`中填写想要的分支名、Tag(e.g. v0.8.2)或SHA。 +- 编译产出在触发后的runs界面中，参考[成功产出的runs链接](https://github.com/4paradigm/OpenMLDB/actions/runs/6044951902)。 + - 一定会产出openmldb binary文件。 + - 如果不需要Java或Python SDK，可配置`java sdk enable`或`python sdk enable`为`OFF`，节约编译时间。 此编译流程需要从源码编译thirdparty，且资源较少，无法开启较高的并发编译。因此编译时间较长，大约需要3h5m（2h thirdparty+1h OpenMLDB）。workflow会缓存thirdparty的编译产出，因此第二次编译会快很多（1h15m OpenMLDB）。 diff --git a/steps/centos6_build.sh b/steps/centos6_build.sh index a5614b10693..b5cee80838f 100644 --- a/steps/centos6_build.sh +++ b/steps/centos6_build.sh @@ -19,6 +19,7 @@ set +x # self build or workflow IN_WORKFLOW=${IN_WORKFLOW:-"false"} +USE_DEPS_CACHE=${USE_DEPS_CACHE:-"false"} # if download from openmldb.ai OPENMLDB_SOURCE=${OPENMLDB_SOURCE:-"false"} @@ -36,6 +37,13 @@ function tool_install() { chmod +x bazel } +if [ "$USE_DEPS_CACHE" == "true" ]; then + echo "use deps cache, exit" + exit 0 +else + echo "not use deps cache, install tools and build deps" +fi + if [ "$IN_WORKFLOW" == "true" ]; then echo "in workflow" else @@ -56,13 +64,12 @@ echo "add patch in fetch cmake" sed -i'' '34s/WITH_TOOLS=OFF$/WITH_TOOLS=OFF -DWITH_CORE_TOOLS=OFF/' third-party/cmake/FetchRocksDB.cmake # if BUILD_BUNDLED=OFF will download pre-built thirdparty, not good -# so we use cmake to build zetasql only -# it's hard to avoid add zetasql patch twice, so we check the dir to avoid -if [ -d ".deps/build/src/zetasql" ]; then - echo "zetasql already exists, skip add patch, if you want, rm .deps/build/src/zetasql* -rf" +# so we use cmake to build zetasql only and add patch to it +# it's hard to avoid add zetasql patch twice, so we check the stamp to avoid +if [ -e ".deps/build/src/zetasql-stamp/zetasql-build" ]; then + echo "zetasql already exists, skip add patch, if you want, rm .deps/build/src/zetasql-stamp/zetasql-build or whole .deps/build/src/zetasql*" else echo "modify in .deps needs a make first, download&build zetasql first(build will fail)" - # sed -i'' '31s/${BUILD_BUNDLED}/ON/' third-party/CMakeLists.txt cmake -S third-party -B "$(pwd)"/.deps -DSRC_INSTALL_DIR="$(pwd)"/thirdsrc -DDEPS_INSTALL_DIR="$(pwd)"/.deps/usr -DBUILD_BUNDLED=ON cmake --build "$(pwd)"/.deps --target zetasql echo "add patch in .deps zetasql" From 1386632befd9a49191965df9dbc2cc5d649ac852 Mon Sep 17 00:00:00 2001 From: HuangWei Date: Wed, 11 Oct 2023 16:12:50 +0800 Subject: [PATCH 04/32] feat: check table status when CLI login (#3506) * feat: check table status when CLI login * fix --- src/cmd/sql_cmd.h | 49 +++++++++++++++++++++++++++++++++-- src/sdk/sql_cluster_router.cc | 2 +- 2 files changed, 48 insertions(+), 3 deletions(-) diff --git a/src/cmd/sql_cmd.h b/src/cmd/sql_cmd.h index 5cf1b99cd0c..2d941c65a35 100644 --- a/src/cmd/sql_cmd.h +++ b/src/cmd/sql_cmd.h @@ -141,14 +141,59 @@ std::string ExecFetch(const std::string& sql) { return ss.str(); } -void HandleSQL(const std::string& sql) { - std::cout << ExecFetch(sql); +void HandleSQL(const std::string& sql) { std::cout << ExecFetch(sql); } + +std::string SafeGetString(std::shared_ptr rs, int idx) { + std::string tmp; + if (!rs->GetString(idx, &tmp)) { + LOG(WARNING) << "fail to get string in col " << idx; + return ""; + } + return tmp; +} + +bool CheckAllTableStatus() { + hybridse::sdk::Status status; + auto rs = sr->ExecuteSQL("show table status like '%'", &status); + bool is_ok = true; + if (status.IsOK()) { + // ref GetTableStatusSchema, just use idx to get column + while (rs->Next()) { + auto table = SafeGetString(rs, 1); + auto db = SafeGetString(rs, 2); + auto pu = SafeGetString(rs, 8); + auto warnings = SafeGetString(rs, 13); + std::string msg = absl::StrCat("table ", db, ".", table, " is broken, `show table status` to check detail"); + bool is_broken = false; + if (pu != "0") { + is_broken = true; + msg.append(", unalive partition: ").append(pu); + } + if (!warnings.empty()) { + is_broken = true; + msg.append(", warning preview: ").append(warnings.substr(0, 100)); + } + if (is_broken) { + is_ok = false; + std::cout << "ERROR: " << msg << std::endl; + } + } + } else { + std::cout << "ERROR: fail to get all table status, " << status.ToString() << std::endl; + is_ok = false; + } + return is_ok; } // cluster mode if zk_cluster is not empty, otherwise standalone mode void Shell() { DCHECK(cs); DCHECK(sr); + // before all, check all table status + if (!CheckAllTableStatus()) { + std::cout << "HINT: Use `openmldb_tool inspect` to get full report." << std::endl; + } + // If use FLAGS_cmd, non-interactive. No Logo and make sure router interactive is false if (!FLAGS_cmd.empty()) { std::string db = FLAGS_database; diff --git a/src/sdk/sql_cluster_router.cc b/src/sdk/sql_cluster_router.cc index 296cd3d5755..eea62b508ff 100644 --- a/src/sdk/sql_cluster_router.cc +++ b/src/sdk/sql_cluster_router.cc @@ -4279,7 +4279,7 @@ static const std::initializer_list GetTableStatusSchema() { // 1. memory: binlog + snapshot // 2. SSD/HDD: binlog + rocksdb data (sst files), wal files and checkpoints are not included // - Partition: partition number -// - partition_unalive: partition number that is unalive +// - Partition_unalive: partition number that is unalive // - Replica: replica number // - Offline_path: data path for offline data // - Offline_format: format for offline data From 34377414f89eb475eef6f2ea3b62c062300c7e0c Mon Sep 17 00:00:00 2001 From: HuangWei Date: Wed, 11 Oct 2023 17:21:59 +0800 Subject: [PATCH 05/32] fix: add deploy bias on demo and docs (#3520) --- demo/byzer-taxi/openmldb_byzer_taxi.bznb | 2 +- .../demo/src/main/java/com/openmldb/demo/App.java | 2 +- demo/jd-recommendation/sql_scripts/deploy.sql | 2 +- demo/predict-taxi-trip-duration/README.md | 4 ++-- demo/predict-taxi-trip-duration/script/taxi.sql | 2 +- .../train_and_serve.ipynb | 2 +- .../train_and_serve.py | 3 ++- docs/en/use_case/lightgbm_demo.md | 2 +- .../deploy_integration/OpenMLDB_Byzer_taxi.md | 2 +- .../openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md | 10 ++++++++-- docs/zh/quickstart/sdk/java_sdk.md | 2 +- docs/zh/use_case/JD_recommendation.md | 2 +- docs/zh/use_case/taxi_tour_duration_prediction.md | 6 +++++- 13 files changed, 26 insertions(+), 15 deletions(-) diff --git a/demo/byzer-taxi/openmldb_byzer_taxi.bznb b/demo/byzer-taxi/openmldb_byzer_taxi.bznb index dc1c925cb0f..b4835f7cc85 100644 --- a/demo/byzer-taxi/openmldb_byzer_taxi.bznb +++ b/demo/byzer-taxi/openmldb_byzer_taxi.bznb @@ -64,7 +64,7 @@ "job_id" : null }, { "id" : "240", - "content" : "run command as FeatureStoreExt.`` where\r\nzkAddress=\"127.0.0.1:2181\"\r\nand zkPath=\"/openmldb\"\r\nand `sql-0`='''\r\nSET @@execute_mode='online';\r\n'''\r\nand `sql-1`='''\r\nDEPLOY d1 SELECT trip_duration, passenger_count,\r\nsum(pickup_latitude) OVER w AS vendor_sum_pl,\r\nmax(pickup_latitude) OVER w AS vendor_max_pl,\r\nmin(pickup_latitude) OVER w AS vendor_min_pl,\r\navg(pickup_latitude) OVER w AS vendor_avg_pl,\r\nsum(pickup_latitude) OVER w2 AS pc_sum_pl,\r\nmax(pickup_latitude) OVER w2 AS pc_max_pl,\r\nmin(pickup_latitude) OVER w2 AS pc_min_pl,\r\navg(pickup_latitude) OVER w2 AS pc_avg_pl ,\r\ncount(vendor_id) OVER w2 AS pc_cnt,\r\ncount(vendor_id) OVER w AS vendor_cnt\r\nFROM t1 \r\nWINDOW w AS (PARTITION BY vendor_id ORDER BY pickup_datetime ROWS_RANGE BETWEEN 1d PRECEDING AND CURRENT ROW),\r\nw2 AS (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN 1d PRECEDING AND CURRENT ROW);\r\n'''\r\nand db=\"db1\"\r\nand action=\"ddl\";", + "content" : "run command as FeatureStoreExt.`` where\r\nzkAddress=\"127.0.0.1:2181\"\r\nand zkPath=\"/openmldb\"\r\nand `sql-0`='''\r\nSET @@execute_mode='online';\r\n'''\r\nand `sql-1`='''\r\nDEPLOY d1 OPTIONS(RANGE_BIAS="inf", ROWS_BIAS="inf") SELECT trip_duration, passenger_count,\r\nsum(pickup_latitude) OVER w AS vendor_sum_pl,\r\nmax(pickup_latitude) OVER w AS vendor_max_pl,\r\nmin(pickup_latitude) OVER w AS vendor_min_pl,\r\navg(pickup_latitude) OVER w AS vendor_avg_pl,\r\nsum(pickup_latitude) OVER w2 AS pc_sum_pl,\r\nmax(pickup_latitude) OVER w2 AS pc_max_pl,\r\nmin(pickup_latitude) OVER w2 AS pc_min_pl,\r\navg(pickup_latitude) OVER w2 AS pc_avg_pl ,\r\ncount(vendor_id) OVER w2 AS pc_cnt,\r\ncount(vendor_id) OVER w AS vendor_cnt\r\nFROM t1 \r\nWINDOW w AS (PARTITION BY vendor_id ORDER BY pickup_datetime ROWS_RANGE BETWEEN 1d PRECEDING AND CURRENT ROW),\r\nw2 AS (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN 1d PRECEDING AND CURRENT ROW);\r\n'''\r\nand db=\"db1\"\r\nand action=\"ddl\";", "job_id" : null }, { "id" : "241", diff --git a/demo/java_quickstart/demo/src/main/java/com/openmldb/demo/App.java b/demo/java_quickstart/demo/src/main/java/com/openmldb/demo/App.java index 2923832d3b8..cbe363f4359 100644 --- a/demo/java_quickstart/demo/src/main/java/com/openmldb/demo/App.java +++ b/demo/java_quickstart/demo/src/main/java/com/openmldb/demo/App.java @@ -146,7 +146,7 @@ private void createDeployment() { "(PARTITION BY %s.c1 ORDER BY %s.c7 ROWS_RANGE BETWEEN 2d PRECEDING AND CURRENT ROW);", table, table, table); // 上线一个Deployment - String deploySql = String.format("DEPLOY %s %s", deploymentName, selectSql); + String deploySql = String.format("DEPLOY %s OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') %s", deploymentName, selectSql); // set return null rs, don't check the returned value, it's false state.execute(deploySql); } catch (Exception e) { diff --git a/demo/jd-recommendation/sql_scripts/deploy.sql b/demo/jd-recommendation/sql_scripts/deploy.sql index 7cb2121e869..e37408b6396 100644 --- a/demo/jd-recommendation/sql_scripts/deploy.sql +++ b/demo/jd-recommendation/sql_scripts/deploy.sql @@ -1,6 +1,6 @@ USE JD_db; SET @@execute_mode='online'; -DEPLOY demo select * from +DEPLOY demo OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') select * from ( select `reqId` as reqId_1, diff --git a/demo/predict-taxi-trip-duration/README.md b/demo/predict-taxi-trip-duration/README.md index bd44778c2a3..a35f2eb9363 100644 --- a/demo/predict-taxi-trip-duration/README.md +++ b/demo/predict-taxi-trip-duration/README.md @@ -85,7 +85,7 @@ python3 train.py /tmp/feature_data /tmp/model.txt # The below commands are executed in the CLI > USE demo_db; > SET @@execute_mode='online'; -> DEPLOY demo SELECT trip_duration, passenger_count, +> DEPLOY demo OPTIONS(RANGE_BIAS="inf", ROWS_BIAS="inf") SELECT trip_duration, passenger_count, sum(pickup_latitude) OVER w AS vendor_sum_pl, max(pickup_latitude) OVER w AS vendor_max_pl, min(pickup_latitude) OVER w AS vendor_min_pl, @@ -193,7 +193,7 @@ python3 train.py /tmp/feature.csv /tmp/model.txt ```sql # The below commands are executed in the CLI > USE demo_db; -> DEPLOY demo SELECT trip_duration, passenger_count, +> DEPLOY demo OPTIONS(RANGE_BIAS="inf", ROWS_BIAS="inf") SELECT trip_duration, passenger_count, sum(pickup_latitude) OVER w AS vendor_sum_pl, max(pickup_latitude) OVER w AS vendor_max_pl, min(pickup_latitude) OVER w AS vendor_min_pl, diff --git a/demo/predict-taxi-trip-duration/script/taxi.sql b/demo/predict-taxi-trip-duration/script/taxi.sql index bbdd219b2e5..8ade33df870 100644 --- a/demo/predict-taxi-trip-duration/script/taxi.sql +++ b/demo/predict-taxi-trip-duration/script/taxi.sql @@ -22,7 +22,7 @@ w2 AS (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN OPTIONS(mode='overwrite'); SET @@execute_mode='online'; -DEPLOY demo SELECT trip_duration, passenger_count, +DEPLOY demo OPTIONS(RANGE_BIAS="inf", ROWS_BIAS="inf") SELECT trip_duration, passenger_count, sum(pickup_latitude) OVER w AS vendor_sum_pl, max(pickup_latitude) OVER w AS vendor_max_pl, min(pickup_latitude) OVER w AS vendor_min_pl, diff --git a/demo/talkingdata-adtracking-fraud-detection/train_and_serve.ipynb b/demo/talkingdata-adtracking-fraud-detection/train_and_serve.ipynb index 6a7c71ff412..b3b01306588 100644 --- a/demo/talkingdata-adtracking-fraud-detection/train_and_serve.ipynb +++ b/demo/talkingdata-adtracking-fraud-detection/train_and_serve.ipynb @@ -187,7 +187,7 @@ "outputs": [], "source": [ "deploy_name='d1'\n", - "%sql DEPLOY $deploy_name $sql_part;" + "%sql DEPLOY $deploy_name OPTIONS(RANGE_BIAS=\"inf\", ROWS_BIAS=\"inf\") $sql_part;" ] }, { diff --git a/demo/talkingdata-adtracking-fraud-detection/train_and_serve.py b/demo/talkingdata-adtracking-fraud-detection/train_and_serve.py index 9cdd93d2074..a592edfdb0e 100644 --- a/demo/talkingdata-adtracking-fraud-detection/train_and_serve.py +++ b/demo/talkingdata-adtracking-fraud-detection/train_and_serve.py @@ -166,7 +166,8 @@ def nothrow_execute(sql): connection.execute("SET @@execute_mode='online';") connection.execute(f'USE {DB_NAME}') nothrow_execute(f'DROP DEPLOYMENT {DEPLOY_NAME}') -deploy_sql = f"""DEPLOY {DEPLOY_NAME} {sql_part}""" +# to avoid data expired by abs ttl, set inf +deploy_sql = f"""DEPLOY {DEPLOY_NAME} OPTIONS(RANGE_BIAS="inf", ROWS_BIAS="inf") {sql_part}""" print(deploy_sql) connection.execute(deploy_sql) print('Import data to online') diff --git a/docs/en/use_case/lightgbm_demo.md b/docs/en/use_case/lightgbm_demo.md index f4e602373a6..80a3d98ba98 100644 --- a/docs/en/use_case/lightgbm_demo.md +++ b/docs/en/use_case/lightgbm_demo.md @@ -152,7 +152,7 @@ Assuming that the model produced by the features designed in Section 2.3 in the ```sql > USE demo_db; > SET @@execute_mode='online'; -> DEPLOY demo SELECT trip_duration, passenger_count, +> DEPLOY demo OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') SELECT trip_duration, passenger_count, sum(pickup_latitude) OVER w AS vendor_sum_pl, max(pickup_latitude) OVER w AS vendor_max_pl, min(pickup_latitude) OVER w AS vendor_min_pl, diff --git a/docs/zh/integration/deploy_integration/OpenMLDB_Byzer_taxi.md b/docs/zh/integration/deploy_integration/OpenMLDB_Byzer_taxi.md index 926c079469d..9250d593341 100644 --- a/docs/zh/integration/deploy_integration/OpenMLDB_Byzer_taxi.md +++ b/docs/zh/integration/deploy_integration/OpenMLDB_Byzer_taxi.md @@ -232,7 +232,7 @@ and `sql-0`=''' SET @@execute_mode='online'; ''' and `sql-1`=''' -DEPLOY d1 SELECT trip_duration, passenger_count, +DEPLOY d1 OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') SELECT trip_duration, passenger_count, sum(pickup_latitude) OVER w AS vendor_sum_pl, max(pickup_latitude) OVER w AS vendor_max_pl, min(pickup_latitude) OVER w AS vendor_min_pl, diff --git a/docs/zh/openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md b/docs/zh/openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md index 4f94e228357..41b3e1141e8 100644 --- a/docs/zh/openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md +++ b/docs/zh/openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md @@ -175,9 +175,9 @@ deploy demo options(SYNC="false") SELECT t1.col1, t2.col2, sum(col4) OVER w1 as WINDOW w1 AS (PARTITION BY t1.col2 ORDER BY t1.col3 ROWS BETWEEN 2 PRECEDING AND CURRENT ROW); ``` -#### 设置偏移 +#### 设置偏移BIAS -如果你并不希望数据根据deploy的索引淘汰，或者希望晚一点淘汰，可以在deploy时设置偏移，常用于数据时间戳并不实时的情况、测试等情况。如果deploy后的索引ttl为abs 3h，但是数据的时间戳是3h前的(以系统时间为基准)，那么这条数据就会被淘汰，无法参与计算。设置一定时间或永久的偏移，则可以让数据更久的停留在在线表中。 +如果你并不希望数据根据deploy的索引淘汰，或者希望晚一点淘汰，可以在deploy时设置偏移BIAS，常用于数据时间戳并不实时的情况、测试等情况。如果deploy后的索引ttl为abs 3h，但是数据的时间戳是3h前的(以系统时间为基准)，那么这条数据就会被淘汰，无法参与计算。设置一定时间或永久的偏移，则可以让数据更久的停留在在线表中。 时间偏移，单位可以是`s`、`m`、`h`、`d`，也可以是整数，单位为`ms`，也可以是`inf`，表示永不淘汰；如果是行数偏移，可以是整数，单位是`row`，也可以是`inf`，表示永不淘汰。两种偏移中，0均表示不偏移。 @@ -185,6 +185,12 @@ deploy demo options(SYNC="false") SELECT t1.col1, t2.col2, sum(col4) OVER w1 as 而时间偏移的单位是`min`，我们会在内部将其转换为`min`，并且取上界。比如，新索引ttl是abs 2min，加上偏移20s，结果是`2min + ub(20s) = 3min`，然后和旧索引1min取上界，最终索引ttl是`max(1min, 3min) = 3min`。 +**Example** +```sql +DEPLOY demo OPTIONS(RANGE_BIAS="inf", ROWS_BIAS="inf") SELECT t1.col1, t2.col2, sum(col4) OVER w1 as w1_col4_sum FROM t1 LAST JOIN t2 ORDER BY t2.col3 ON t1.col2 = t2.col2 + WINDOW w1 AS (PARTITION BY t1.col2 ORDER BY t1.col3 ROWS BETWEEN 2 PRECEDING AND CURRENT ROW); +``` + ## 相关SQL [USE DATABASE](../ddl/USE_DATABASE_STATEMENT.md) diff --git a/docs/zh/quickstart/sdk/java_sdk.md b/docs/zh/quickstart/sdk/java_sdk.md index 966d50db785..166b44adb8e 100644 --- a/docs/zh/quickstart/sdk/java_sdk.md +++ b/docs/zh/quickstart/sdk/java_sdk.md @@ -403,7 +403,7 @@ try { "(PARTITION BY %s.c1 ORDER BY %s.c7 ROWS_RANGE BETWEEN 2d PRECEDING AND CURRENT ROW);", table, table, table); // 上线一个Deployment - String deploySql = String.format("DEPLOY %s %s", deploymentName, selectSql); + String deploySql = String.format("DEPLOY %s OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') %s", deploymentName, selectSql); // set return null rs, don't check the returned value, it's false state.execute(deploySql); } catch (Exception e) { diff --git a/docs/zh/use_case/JD_recommendation.md b/docs/zh/use_case/JD_recommendation.md index d4035be912a..cb4ce603059 100644 --- a/docs/zh/use_case/JD_recommendation.md +++ b/docs/zh/use_case/JD_recommendation.md @@ -393,7 +393,7 @@ bash train_deepfm.sh $demodir/feature_preprocess/out ```sql -- OpenMLDB CLI USE JD_db; - DEPLOY demo ; + DEPLOY demo OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') ; ``` 也可以在 Docker 容器内直接运行部署脚本： diff --git a/docs/zh/use_case/taxi_tour_duration_prediction.md b/docs/zh/use_case/taxi_tour_duration_prediction.md index faaff3bf922..dfb84de28da 100644 --- a/docs/zh/use_case/taxi_tour_duration_prediction.md +++ b/docs/zh/use_case/taxi_tour_duration_prediction.md @@ -151,7 +151,7 @@ w2 AS (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN --OpenMLDB CLI USE demo_db; SET @@execute_mode='online'; - DEPLOY demo SELECT trip_duration, passenger_count, + DEPLOY demo OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') SELECT trip_duration, passenger_count, sum(pickup_latitude) OVER w AS vendor_sum_pl, max(pickup_latitude) OVER w AS vendor_max_pl, min(pickup_latitude) OVER w AS vendor_min_pl, @@ -167,6 +167,10 @@ w2 AS (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN w2 AS (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN 1d PRECEDING AND CURRENT ROW); ``` +```{note} +此处DEPLOY包含BIAS OPTIONS，是因为导入在线存储的数据文件不会更新，对于当前时间来讲，可能会超过DEPLOY后的表索引的时间TTL，导致表淘汰掉这些数据。时间淘汰，只看每个索引的ts列和ttl，只要数据中该列的值<(当前时间-abs_ttl)，在该索引上就会被淘汰，与其他因素无关，各个索引也互相不影响。如果你的数据不是实时产生的新timestamp，也需要考虑带上BIAS OPTIONS。 +``` + ### 步骤 7：导入在线数据 首先，请切换到**在线**执行模式。接着在在线模式下，导入样例数据 `/work/taxi-trip/data/taxi_tour_table_train_simple.csv` 作为在线数据，用于在线特征计算。 From 72a49d8b4d872016c54f5d837d3ad1a991aaee32 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Thu, 12 Oct 2023 10:04:24 +0800 Subject: [PATCH 06/32] docs(udf): upgrade udf list (#3541) Co-authored-by: aceforeverd --- .../reference/sql/functions_and_operators/Files/udfs_8h.md | 7 ++++++- .../openmldb_sql/functions_and_operators/Files/udfs_8h.md | 7 ++++++- 2 files changed, 12 insertions(+), 2 deletions(-) diff --git a/docs/en/reference/sql/functions_and_operators/Files/udfs_8h.md b/docs/en/reference/sql/functions_and_operators/Files/udfs_8h.md index ac96c6bfc3f..d1696b6c764 100644 --- a/docs/en/reference/sql/functions_and_operators/Files/udfs_8h.md +++ b/docs/en/reference/sql/functions_and_operators/Files/udfs_8h.md @@ -1178,7 +1178,12 @@ Supported date string style: * yyyy-mm-dd * yyyymmdd -* yyyy-mm-dd hh:mm:ss +* yyyy-mm-dd HH:MM:SS +* yyyy-mm-ddTHH:MM:SS.fff+HH:MM (RFC3399 format) + +Dates from string are transformed into the same time zone (which is currently always UTC+8) before differentiation, dates from date type by default is at UTC+8, you may see a +1/-1 difference if the two date string have different time zones. + +Hint: since openmldb date type limits range from year 1900, to datadiff from/to a date before 1900, pass it as string. Example: diff --git a/docs/zh/openmldb_sql/functions_and_operators/Files/udfs_8h.md b/docs/zh/openmldb_sql/functions_and_operators/Files/udfs_8h.md index ac96c6bfc3f..d1696b6c764 100644 --- a/docs/zh/openmldb_sql/functions_and_operators/Files/udfs_8h.md +++ b/docs/zh/openmldb_sql/functions_and_operators/Files/udfs_8h.md @@ -1178,7 +1178,12 @@ Supported date string style: * yyyy-mm-dd * yyyymmdd -* yyyy-mm-dd hh:mm:ss +* yyyy-mm-dd HH:MM:SS +* yyyy-mm-ddTHH:MM:SS.fff+HH:MM (RFC3399 format) + +Dates from string are transformed into the same time zone (which is currently always UTC+8) before differentiation, dates from date type by default is at UTC+8, you may see a +1/-1 difference if the two date string have different time zones. + +Hint: since openmldb date type limits range from year 1900, to datadiff from/to a date before 1900, pass it as string. Example: From 15a7d46dd5704421c037d5590d3bee96683df93f Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Thu, 12 Oct 2023 13:42:33 +0800 Subject: [PATCH 07/32] docs: change_for_airflow_provider_demo_of_integration_folder (#3467) --- .../airflow_provider_demo.md | 145 ++++++++++++++++++ .../images/add_connection.png | Bin 0 -> 32687 bytes .../deploy_integration/images/airflow_dag.png | Bin 0 -> 303427 bytes .../images/airflow_login.png | Bin 0 -> 42118 bytes .../images/airflow_test_result.png | Bin 0 -> 25328 bytes .../deploy_integration/images/connection.png | Bin 0 -> 157110 bytes .../images/connection_display.png | Bin 0 -> 21200 bytes .../images/connection_settings.png | Bin 0 -> 188000 bytes .../deploy_integration/images/dag_code.png | Bin 0 -> 51039 bytes .../deploy_integration/images/dag_home.png | Bin 0 -> 64185 bytes .../deploy_integration/images/dag_run.png | Bin 0 -> 789458 bytes .../airflow_provider_demo.md | 24 +-- 12 files changed, 157 insertions(+), 12 deletions(-) create mode 100644 docs/en/integration/deploy_integration/airflow_provider_demo.md create mode 100644 docs/en/integration/deploy_integration/images/add_connection.png create mode 100644 docs/en/integration/deploy_integration/images/airflow_dag.png create mode 100644 docs/en/integration/deploy_integration/images/airflow_login.png create mode 100644 docs/en/integration/deploy_integration/images/airflow_test_result.png create mode 100644 docs/en/integration/deploy_integration/images/connection.png create mode 100644 docs/en/integration/deploy_integration/images/connection_display.png create mode 100644 docs/en/integration/deploy_integration/images/connection_settings.png create mode 100644 docs/en/integration/deploy_integration/images/dag_code.png create mode 100644 docs/en/integration/deploy_integration/images/dag_home.png create mode 100644 docs/en/integration/deploy_integration/images/dag_run.png diff --git a/docs/en/integration/deploy_integration/airflow_provider_demo.md b/docs/en/integration/deploy_integration/airflow_provider_demo.md new file mode 100644 index 00000000000..3f741cf4c61 --- /dev/null +++ b/docs/en/integration/deploy_integration/airflow_provider_demo.md @@ -0,0 +1,145 @@ +# Airflow +We provide [Airflow OpenMLDB Provider](https://github.com/4paradigm/OpenMLDB/tree/main/extensions/airflow-provider-openmldb), which facilitates the integration of OpenMLDB with Airflow DAG. + +This specific case will undergo training and execution with Airflow's [TalkingData](https://chat.openai.com/talkingdata_demo). + +## TalkingData DAG + +To implement this workflow in Airflow, a DAG (Directed Acyclic Graph) file needs to be written. Here we use an example DAG file in [example_openmldb_complex.py](https://github.com/4paradigm/OpenMLDB/blob/main/extensions/airflow-provider-openmldb/openmldb_provider/example_dags/example_openmldb_complex.py). + +![airflow dag](images/airflow_dag.png) + +The diagram above illustrates the work process in DAG. It begins by creating a table, followed by offline data loading, feature extraction, and model training. If the model trained performs well (AUC >= 99.0), the workflow proceeds to execute deploy SQL and model serving online. Otherwise, a failure report is generated. + +In the following demonstration, you can directly import this DAG and run in Airflow. + + +## Demonstration + +We import the above DAG to perform feature computation and deployment for the TalkingData Demo, then perform real-time inference using the predict server of TalkingData Demo. + +### Preparation + +#### Download DAG + +Along with the DAG files, training scripts are also required. For convenience, we provide the [code package](https://openmldb.ai/download/airflow_demo/airflow_demo_files.tar.gz) for direct download. If you prefer to use the latest version, you can obtain it from [github example_dags](https://github.com/4paradigm/OpenMLDB/tree/main/extensions/airflow-provider-openmldb/openmldb_provider/example_dags). + +``` +wget https://openmldb.ai/download/airflow_demo/airflow_demo_files.tar.gz +tar zxf airflow_demo_files.tar.gz +ls airflow_demo_files +``` +#### Start Docker Image + +For smooth function, we recommend starting OpenMLDB using the docker image and installing Airflow within the docker container. + +Since Airflow Web requires an external port for login, the container's port must be exposed. Then map the downloaded file from the previous step to the `/work/airflow/dags` directory. This step is crucial for Airflow to load the DAGs from this folder correctly. + +``` +docker run -p 8080:8080 -v `pwd`/airflow_demo_files:/work/airflow_demo_files -it 4pdosc/openmldb:0.8.0 bash +``` + +#### Download and Install Airflow and Airflow OpenMLDB Provider +In the docker container, execute: +``` +pip3 install airflow-provider-openmldb +``` +Airflow will be downloaded as a dependency. + +#### Source Data and DAG Preparation +Copy the sample data file, named `/tmp/train_sample.csv`, to the tmp directory. Airflow DAG files and training scripts used in the DAG must also be copied to the Airflow directory. + +``` +cp /work/airflow_demo_files/train_sample.csv /tmp/ +mkdir -p /work/airflow/dags +cp /work/airflow_demo_files/example_openmldb_complex.py /work/airflow_demo_files/xgboost_train_sample.py /work/airflow/dags +``` + +### Step 1: Start OpenMLDB and Airflow +The command provided below will initiate the OpenMLDB cluster, enabling support for predict server and Airflow standalone. +``` +/work/init.sh +python3 /work/airflow_demo_files/predict_server.py --no-init > predict.log 2>&1 & +export AIRFLOW_HOME=/work/airflow +cd $AIRFLOW_HOME +airflow standalone +``` + +Airflow standalone will show username and password as shown below. + +![airflow login](images/airflow_login.png) + +In Airflow Web interface at `http://localhost:8080`, enter username and password. + +```{caution} +`airflow standalone` is a front-end program that exits with Airflow. You can exit Airflow after DAG completion to run [Step 3-Testing](#3-Testing), or place the Airflow process in the background. +``` + +### Step 2: Running DAG + +To check the status of the DAG "example_openmldb_complex" in Airflow Web, click on the DAG and select the `Code` tab, as shown below. + +![dag home](images/dag_home.png) + +In this code, you will notice the usage of `openmldb_conn_id`, as depicted in the following figure. The DAG doesn't directly employ the address of OpenMLDB; instead, it uses a connection, so you need to create a new connection with the same name. + +![dag code](images/dag_code.png) + +#### Create Connection +Click on connections in the Admin tab. +![connection](images/connection.png) + +Add the connection. +![add connection](images/add_connection.png) + +The Airflow OpenMLDB Provider is linked to the OpenMLDB API Server. Therefore, you should provide the address of the OpenMLDB API Server in this configuration, rather than the Zookeeper address. + +![connection settings](images/connection_settings.png) + +The completed connection is shown in the figure below. +![display](images/connection_display.png) + +#### Running DAG +Run the DAG to complete the training of the model, SQL deployment, and model deployment. A successful operation will yield results similar to the figure below. +![dag run](images/dag_run.png) + +### Step 3: Test + +If Airflow is currently running in the foreground within the container, you may exit the process now. The upcoming tests will not be dependent on Airflow. + +#### Online Data Import +The SQL and model deployment have been successfully executed in the Airflow DAG. However, there is currently no data in the online storage, necessitating an online data import. + +``` +curl -X POST http://127.0.0.1:9080/dbs/example_db -d'{"mode":"online", "sql":"load data infile \"file:///tmp/train_sample.csv\" into table example_table options(mode=\"append\");"}' +``` + +This import process is asynchronous, but since the data volume is small, it will be completed quickly. You can monitor the status of the import operations by using the `SHOW JOBS` command. +``` +curl -X POST http://127.0.0.1:9080/dbs/example_db -d'{"mode":"online", "sql":"show jobs"}' +``` + +#### Prediction +Execute the prediction script to make a prediction using the newly deployed SQL and model. +``` +python3 /work/airflow_demo_files/predict.py +``` +The result is as shown. +![result](images/airflow_test_result.png) + + +### Non-Interactive Testing + +Check if DAG has been successfully loaded: +``` +airflow dags list | grep openmldb +``` +Add required connection: +``` +airflow connections add openmldb_conn_id --conn-uri http://127.0.0.1:9080 +airflow connections list --conn-id openmldb_conn_id +``` +DAG test: +``` +airflow dags test example_openmldb_complex 2022-08-25 +``` diff --git a/docs/en/integration/deploy_integration/images/add_connection.png b/docs/en/integration/deploy_integration/images/add_connection.png new file mode 100644 index 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00000000000..143e8b82dbc --- /dev/null +++ b/docs/en/integration/deploy_integration/dolphinscheduler_task_demo.md @@ -0,0 +1,211 @@ +# DolphinScheduler + +## Introduction +In the whole process of machine learning from development to deployment, tasks including data processing, feature development, and model training demand significant time and effort. To streamline the development and deployment of AI models and simplify the overall machine-learning process, we introduce the DolphinScheduler OpenMLDB Task. It seamlessly integrates the capabilities of the feature platform into DolphinScheduler's workflow, effectively bridging feature engineering with scheduling, resulting in a comprehensive end-to-end MLOps workflow. In this article, we present a concise introduction and practical demonstration of the procedures for using the DolphinScheduler OpenMLDB Task. + +```{seealso} +For detailed information on the OpenMLDB Task, please refer to the [DolphinScheduler OpenMLDB Task Official Documentation](https://dolphinscheduler.apache.org/zh-cn/docs/3.1.5/guide/task/openmldb). +``` + +## Scenarios and Functions +### Why Develop DolphinScheduler OpenMLDB Task + +![eco](images/ecosystem.png) + +As an open-source machine learning database providing a comprehensive solution for production-level data and feature development, the key to enhancing OpenMLDB's usability and reducing usage barriers lies in upstream and downstream connectivity. As depicted in the diagram above, the ability to access the data source allows seamless data flow from DataOps into OpenMLDB. Then the generated features by OpenMLDB need to smoothly integrate with ModelOps for training. To alleviate the significant workload resulting from manual integration by developers using OpenMLDB, we have also developed the function for OpenMLDB integration into Deployment and Monitoring. In this article, we introduce the framework for integrating OpenMLDB into the DolphinScheduler workflow. The DolphinScheduler OpenMLDB Task simplifies the usage of OpenMLDB. In the meantime, OpenMLDB tasks are efficiently managed by Workflow, enabling greater automation. + +### What Can DolphinScheduler OpenMLDB Task Do + +OpenMLDB aims to expedite development launch, enabling developers to focus on the essence of their work rather than expending excessive effort on engineering implementation. By writing OpenMLDB Tasks, we can fulfill the offline import, feature extraction, SQL deployment, and online import requirements of OpenMLDB. Furthermore, we can also implement complete training and online processes using OpenMLDB in DolphinScheduler. + +![task func](images/task_func.png) + +For instance, the most straightforward user operation process we envision, as illustrated in the diagram above, involves steps 1-4: offline data import, offline feature extraction, SQL deployment, and online data import. All of these steps can be achieved by utilizing the DolphinScheduler OpenMLDB Task. + +In addition to SQL execution in OpenMLDB, real-time prediction also requires model deployment. Therefore in the following sections, we will demonstrate how to utilize the DolphinScheduler OpenMLDB Task to coordinate a comprehensive machine learning training and online deployment process, based on the TalkingData adtracking fraud detection challenge from Kaggle. Further information about the TalkingData competition can be found at [talkingdata-adtracking-fraud-detection](https://www.kaggle.com/competitions/talkingdata-adtracking-fraud-detection/discussion). + +## Demonstration +### Environment Configuration + +**Run OpenMLDB Docker Image** + +The test can be executed on macOS or Linux, and we recommend running this demo within the provided OpenMLDB docker image. In this setup, both OpenMLDB and DolphinScheduler will be launched inside the container, with the port of DolphinScheduler exposed. +``` +docker run -it -p 12345:12345 4pdosc/openmldb:0.8.0 bash +``` +```{attention} +For proper configuration of DolphinScheduler, the tenant should be set up as a user of the operating system, and this user must have sudo permissions. It is advised to download and initiate DolphinScheduler within the OpenMLDB container. Otherwise, please ensure that the user has sudo permissions. +``` + +As our current docker image does not have sudo installed, and DolphinScheduler requires sudo for running workflows, please install sudo in the container first: +``` +apt update && apt install sudo +``` + +The DolphinScheduler runs the task using sh, but in the docker, sh is `dash` as default. Thus modify it to `bash` with the following command: +``` +dpkg-reconfigure dash +``` +Enter `no`. + +**Data Preparation** + +The workflow loads data from `/tmp/train_Sample.csv ` to OpenMLDB. Thus, first download the source data to this address: +``` +curl -SLo /tmp/train_sample.csv https://openmldb.ai/download/dolphinschduler-task/train_sample.csv +``` + +**Run OpenMLDB Cluster and Predict Server** + +Run the following command in the container to start a OpenMLDB cluster： +``` +/work/init.sh +``` + +We will run a workflow that includes data import, offline training, and model deployment. The deployment of the model is done by sending the model address to the predict server. Let's begin by downloading and running the predict server in the background: +``` +cd /work +curl -SLo predict_server.py https://openmldb.ai/download/dolphinschduler-task/predict_server.py +python3 predict_server.py --no-init > predict.log 2>&1 & +``` +```{tip} +If an error occurred in the 'Online Prediction Test', please check `/work/predict.log`. +``` + +**Download and Run DolphinScheduler** + +Please note that DolphinScheduler supports OpenMLDB Task versions 3.1.3 and above. In this article, we will be using version 3.1.5, which can be downloaded from the [Official Website](https://dolphinscheduler.apache.org/zh-cn/download/3.1.5) or from a mirrored website. + +To start the DolphinScheduler standalone, follow the steps outlined in the [Official Documentation](https://dolphinscheduler.apache.org/zh-cn/docs/3.1.5/guide/installation/standalone) for more information. + +``` +# Official +curl -SLO https://dlcdn.apache.org/dolphinscheduler/3.1.5/apache-dolphinscheduler-3.1.5-bin.tar.gz +# Image curl -SLO http://openmldb.ai/download/dolphinschduler-task/apache-dolphinscheduler-dev-3.1.5-bin.tar.gz +tar -xvzf apache-dolphinscheduler-*-bin.tar.gz +cd apache-dolphinscheduler-*-bin +sed -i s#/opt/soft/python#/usr/bin/python3#g bin/env/dolphinscheduler_env.sh +./bin/dolphinscheduler-daemon.sh start standalone-server +``` + +```{hint} +In the official release version of DolphinScheduler, there is an issue with OpenMLDB Task in versions older than 3.1.3, which cannot be used directly. If you are using an older version, you can contact us to obtain a corresponding version. This problem has been resolved in versions 3.1.3 and later, making them suitable for use with the official release version. + +In other versions of DolphinScheduler, there may be a change in `bin/env/dolphinscheduler_env.sh`. If `PYTHON_HOME` does not exist in `bin/env/dolphinscheduler_env.sh`, additional configuration is required. You can modify it using the command `echo "export PYTHON_HOME=/usr/bin/python3" >>bin/env/dolphinscheduler_env.sh`. +``` + +To access the system UI, open your browser and go to the address http://localhost:12345/dolphinscheduler/ui (the default configuration allows cross-host access, but you need to ensure a smooth IP connection). The default username and password are admin/dolphinscheduler123. + +```{note} +The DolphinScheduler worker server requires the OpenMLDB Python SDK. For the DolphinScheduler standalone worker, you only need to install the OpenMLDB Python SDK locally. We have already installed it in our OpenMLDB docker image. If you are in a different environment, please install the openmldb SDK using the command `pip3 install openmldb`. +``` + +**Download Workflow Configuration** + +Workflow can be manually created, but for the purpose of simplifying the demonstration, we have provided a JSON workflow file directly, which you can download from the following link: [Click to Download](http://openmldb.ai/download/dolphinschduler-task/workflow_openmldb_demo.json). You can upload this file directly to the DolphinScheduler environment and make simple modifications (as shown in the demonstration below) to complete the entire workflow. + +Please note that the download will not be saved within the container but to the browser host you are using. The upload will be done on the web page later. + +### Run Demo + +#### Step 1: Initial Configuration + +To create a tenant in DolphinScheduler web, navigate to the tenant management interface, and fill in the required fields. Make sure to fill in **user with sudo permission**. You can use the default settings for the queue. You can use root in the docker container. + +![create tenant](images/ds_create_tenant.png) + +Bind the tenant to the user again. For simplicity, we directly bind to the admin user. Enter User Management page and click Edit Admin User. + +![bind tenant](images/ds_bind_tenant.png) + +After binding, the user status is similar as shown below. +![bind status](images/ds_bind_status.png) + +#### Step 2: Create Workflow +In DolphinScheduler, you need to create a project first, and then create a workflow within that project. + +To begin, create a test project. As shown in the following figure, click on "Create Project" and enter the project name. + +![create project](images/ds_create_project.png) + +![project](images/ds_project.png) + +Once inside the project page, you can import the downloaded workflow file. In the workflow definition tab, click on "Import Workflow". + +![import workflow](images/ds_import_workflow.png) + +After importing, the workflow table will show as follows. + +![workflow list](images/ds_workflow_list.png) + +Click on the workflow name to view the detailed content of the workflow, as shown in the following figure. + +![workflow detail](images/ds_workflow_detail.png) + +**Note**: A minor modification is required here since the task ID will change after importing the workflow. Specifically, the upstream and downstream IDs in the switch task will not exist and need to be manually modified. + +![switch](images/ds_switch.png) + +As depicted in the above figure, there are non-existent IDs in the settings of the switch task. Please modify the "branch flow" and "pre-check conditions" for successful and failed workflows to match the tasks of the current workflow. + +The correct results are shown in the following figure: + +![right](images/ds_switch_right.png) + +Once the modifications are completed, save the workflow directly. The default tenant in the imported workflow is "default," which is also **executable**. If you want to specify your own tenant, please select the tenant when saving the workflow, as shown in the following figure. + +![set tenant](images/ds_set_tenant.png) + +#### Step 3: Deploy Online Workflow + +After saving the workflow, it needs to be launched before running. Once it goes online, the run button will be activated. As illustrated in the following figure. + +![run](images/ds_run.png) + +After clicking "Run," wait for the workflow to complete. You can view the details of the workflow operation in the Workflow Instance page, as shown in the following figure. +![run status](images/ds_run_status.png) + +To demonstrate the process of a successful product launch, validation was not actually validated but returned a successful validation and flowed into the deploy branch. After running the deploy branch and successfully deploying SQL and subsequent tasks, the predict server receives the latest model. + +```{note} +If the `Failed` appears on the workflow instance, please click on the instance name and go to the detailed page to see which task execution error occurred. Double-click on the task and click on "View Log" in the upper right corner to view detailed error information. + +`load offline data`, `feature extraction`, and `load online` may display successful task execution in the DolphinScheduler, but actual task execution fails in OpenMLDB. This may lead to errors in the `train` task, where there is no source feature data to concatenate (Traceback `pd.concat`). + +When such problems occur, please query the true status of each task in OpenMLDB and run it directly using the command: `echo "show jobs;" | /work/openmldb/bin/openmldb --zk_cluster=127.0.1:2181 --zk_root_path=/openmldb --role=SQL_client`. If the status of a task is `FAILED`, please query the log of that task. The method can be found in [Task Log](../../quickstart/beginninger_mustread.md#offline). +``` + +#### Step 4: Test Online Prediction +The predict server also provides online prediction services, through `curl/predict`. You can construct a real-time request and send it to the predict server. +``` +curl -X POST 127.0.0.1:8881/predict -d '{"ip": 114904, + "app": 11, + "device": 1, + "os": 15, + "channel": 319, + "click_time": 1509960088000, + "is_attributed": 0}' +``` +The return result is as follows： + +![predict](images/ds_predict.png) + +#### Note + +If the workflow is run repeatedly, the `deploy SQL` task may fail because the deployment `demo` already exists. Please delete the deployment in the docker container before running the workflow again: +``` +/work/openmldb/bin/openmldb --zk_cluster=127.0.0.1:2181 --zk_root_path=/openmldb --role=sql_client --database=demo_db --interactive=false --cmd="drop deployment demo;" +``` + +You can confirm whether the deployment has been deleted by using the following command: +``` +/work/openmldb/bin/openmldb --zk_cluster=127.0.0.1:2181 --zk_root_path=/openmldb --role=sql_client --database=demo_db --interactive=false --cmd="show deployment demo;" +``` + +Restart the DolphinScheduler server (Note that restarting this will clear the metadata and require reconfiguring the environment and creating workflows): +``` +./bin/dolphinscheduler-daemon.sh stop standalone-server +./bin/dolphinscheduler-daemon.sh start standalone-server +``` + +If you want to preserve metadata, please refer to [Pseudo Cluster Deployment](https://dolphinscheduler.apache.org/zh-cn/docs/3.1.5/guide/installation/pseudo-cluster) to configure 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z!+Ak5Ii87+G=Yh_8A7kD=AYQ%5X+L>R5~IfpU6R3K)+DBQo<54$6k|fLHmB91Yf%il{ Date: Thu, 12 Oct 2023 13:53:19 +0800 Subject: [PATCH 09/32] docs: update-quickstart-folder (#3535) --- docs/en/quickstart/beginner_must_read.md | 144 +++++++++++++++ .../en/quickstart/{cli_tutorial.md => cli.md} | 0 docs/en/quickstart/function_boundary.md | 165 ++++++++++++++++++ docs/en/quickstart/index.rst | 5 +- docs/zh/quickstart/beginner_must_read.md | 2 +- docs/zh/quickstart/function_boundary.md | 4 +- 6 files changed, 316 insertions(+), 4 deletions(-) create mode 100644 docs/en/quickstart/beginner_must_read.md rename docs/en/quickstart/{cli_tutorial.md => cli.md} (100%) create mode 100644 docs/en/quickstart/function_boundary.md diff --git a/docs/en/quickstart/beginner_must_read.md b/docs/en/quickstart/beginner_must_read.md new file mode 100644 index 00000000000..759d423b32d --- /dev/null +++ b/docs/en/quickstart/beginner_must_read.md @@ -0,0 +1,144 @@ +# Essential Reading for Getting Started + +As OpenMLDB is a distributed system with various modes and extensive client functionality, users may encounter numerous questions and operational challenges, especially when using it for the first time. This article aims to guide beginners on diagnosing and debugging issues and providing effective information when seeking technical assistance. + +## Create OpenMLDB and Connection + +To begin, we recommend that users who are not well-versed in distributed multi-process management use Docker to set up OpenMLDB. This approach offers convenience and expedites the initial learning process. Once you have become acquainted with the various components of OpenMLDB, you can explore distributed deployment options. + +You can create an OpenMLDB instance using Docker by following the instructions in the [Quickstart guide](./openmldb_quickstart.md). Please note that the guide presents two versions: standalone and cluster. Ensure clarity regarding the version you intend to create and avoid mixed usage. + +A successful startup is indicated by your ability to connect to the OpenMLDB server using the CLI (Command Line Interface). In both standalone and cluster setups, you can use `/work/openmldb/bin/openmldb` to connect to OpenMLDB and execute `show components;` to check the running status of OpenMLDB server components. + +If you encounter difficulties connecting via the CLI, first verify whether the processes are running as expected. You can confirm the presence of nameserver and tablet server processes using `ps f | grep bin/openmldb`. In the case of the cluster setup, ensure that the ZooKeeper service is running by using `ps f | grep zoo.cfg`, and confirm the existence of the taskmanager process with `ps f | grep TaskManagerServer`. + +If all service processes are running correctly, but the CLI still cannot connect to the server, double-check the parameters for CLI operation. If issues persist, don't hesitate to contact us and provide the error information from the CLI. + +```{seealso} +If further configuration and server logs from OpenMLDB are required, you can use diagnostic tools to obtain them, as detailed in the [section below](#provide-configuration-and-logs-for-technical-support). +``` + +## Source Data + +### LOAD DATA + +When importing data from a file into OpenMLDB, the typical command used is `LOAD DATA`. For detailed information, please refer to [LOAD DATA INFILE](../openmldb_sql/dml/LOAD_DATA_STATEMENT.md). The data sources and formats that can be employed with `LOAD DATA` are contingent on several factors, including the OpenMLDB version (standalone or cluster), execution mode, and import mode (i.e., the `LOAD DATA` configuration item, `load_mode`). Specifically: + +In cluster version, the default `load_mode` is "cluster", and it can be set to "local". In standalone version, the default `load_mode` is "local," and **"cluster " is not supported**. Consequently, we discuss these scenarios in three distinct contexts: + +| LOAD DATA Type | Support execution mode (import to destination) | Support asynchronous/ synchronous | Support data sources | Support data formats | +| :-------------------------------- | :--------------------------------------------- | :--------------------------------- | :----------------------------------------------------------- | :--------------------------------------------- | +| Cluster version load_mode=cluster | Online, offline | Asynchronous, synchronous | File (with conditional restrictions, please refer to specific documentation) /hdfs/ hive | CSV/ parquet (HIVE source unrestricted format) | +| Cluster version load_mode=local | Online | Synchronous | Client local file | csv | +| Standalone version（only local) | Online | Synchronous | Client local file | csv | + +When the source data for `LOAD DATA` is in CSV format, it's essential to pay special attention to the timestamp column's format. Timestamps can be in "int64" format (referred to as int64 type) or "yyyy-MM-dd'T'HH:mm:ss[.SSS][XXX]" format (referred to as date type). + +| LOAD DATA Type | Support int64 type | Support date type | +| :-------------------------------- | :------------ | :----------- | +| Cluster version load_mode=cluster | **``✓``** | **``✓``** | +| Cluster version load_mode=local | **``✓``** | **``X``** | +| Standalone version（only local) | **``✓``** | **``X``** | + +```{hint} +The CSV file format can be inconvenient in certain situations, and we recommend considering the use of the Parquet format. This approach requires the OpenMLDB cluster version to be in use and necessitates the taskmanager component to be up and running. +``` + +## SQL Restriction + +OpenMLDB does not offer full compatibility with standard SQL, which means that certain SQL queries may not yield the expected results. If you encounter a situation where the SQL execution does not align with your expectations, it's advisable to initially verify whether the SQL adheres to the [Functional Boundary](./function_boundary.md) guidelines. + +## SQL Execution + +All commands within OpenMLDB are SQL-based. If you experience SQL execution failures or other issues (where it's unclear whether the command was executed successfully), consider the following checks: + +1. **SQL Accuracy**: Examine whether there are errors in the SQL syntax. Syntax errors can lead to unsuccessful SQL execution. You can refer to the [SQL Reference](../../openmldb_sql/) to correct any errors. +2. **Execution Status**: Determine if the command has progressed to the execution phase or if it failed to execute. This distinction is crucial for troubleshooting. + +For instance, if you encounter a syntax error prompt, it indicates a problem with the SQL writing, and you should consult the [SQL Reference](../../openmldb_sql/) for guidance on correcting it. + +``` +127.0.0.1:7527/db> create table t1(c1 int; +Error: Syntax error: Expected ")" or "," but got ";" [at 1:23] +create table t1(c1 int; + ^ +``` + +If the command has entered the execution phase but fails or experiences interaction issues, you should clarify the following details: + +- **OpenMLDB Version**: Is OpenMLDB being used in standalone mode or clustered mode? +- **Execution Mode**: What is the execution mode? You can use the `show variable` command in the CLI to retrieve this information. Note that the execution mode of the standalone version is not meaningful. + +Special attention to usage logic is required when working with the cluster version of OpenMLDB. + +### Cluster Version SQL Execution + +#### Offline + +For cluster offline commands, when operating in the default asynchronous mode, sending the command will yield a job ID as a return value. You can utilize `show job ` to inquire about the execution status of the job. + +If the offline job is an asynchronous SELECT query (without saving results), the results will not be displayed on the client (synchronous SELECT queries do display results). Instead, you can retrieve the results through `show joblog `, which comprises two sections: `stdout` and `stderr`. `stdout` contains the query results, while `stderr` contains the job's runtime log. If you discover that the job has failed or its status doesn't align with your expectations, it's essential to carefully review the job run log. + +```{note} +The location of these logs is determined by the `job.log.path` configuration in taskmanager.properties. If you have altered this configuration, you will need to search in the specified destination for the logs. By default, the stdout log can be found at `/work/openmldb/taskmanager/bin/logs/job_x.log`, while the job execution log is situated at `/work/openmldb/taskmanager/bin/logs/job_x_error.log` (note the "error" suffix). + +If the task manager operates in YARN mode rather than local mode, the information in job_x_error.log may be more limited, and detailed error information about the job might not be available. In such instances, you will need to employ the YARN app ID recorded in job_x_error.log to access the actual error details within the YARN system. +``` + +#### Online + +In the online mode of the cluster version, we typically recommend using the `DEPLOY` command to create a deployment, and access to APIServer through HTTP for real-time feature computations. Performing a SELECT query directly online, with CLI or other clients is referred to as "online preview." It's essential to be aware that online preview comes with several limitations, which are outlined in detail in the [Functional Boundary - Cluster Version Online Preview Mode](../function_boundary.md#cluster-version-online-preview-mode) document. Please avoid executing unsupported SQL queries in this context. + +### Provide Replication Scripts + +If you find yourself unable to resolve an issue through self-diagnosis, please provide us with a replication script. A comprehensive replication script should include the following components: + +``` +create database db; +use db; +-- create your table +create table xx (); + +-- offline or online +set @@execute_mode=''; + +-- load data or online insert +-- load data infile '' into table xx; +-- insert into xx values (),(); + +-- query / deploy ... + +``` + +If your question necessitates data for replication, please include the data. For offline data that doesn't support inserting offline, kindly provide a CSV or Parquet data file. If it pertains to online data, you can either provide a data file or directly insert it within the script. + +These data scripts should be capable of executing SQL commands in bulk by using redirection symbols. + +``` +/work/openmldb/bin/openmldb --host 127.0.0.1 --port 6527 < reproduce.sql +/work/openmldb/bin/openmldb --zk_cluster=127.0.0.1:2181 --zk_root_path=/openmldb --role=sql_client < reproduce.sql +``` + +Ensure that the replication script is functional locally to reproduce the issue, and then document the issue or forward it to us for further assistance. + +```{caution} +Please be aware that offline jobs default to asynchronous mode. If you intend to import and query offline, remember to set it to synchronous mode. For additional information, consult [Offline Command Configuration Details](../openmldb_sql/ddl/SET_STATEMENT.md#offline-command-configuration-details). Without this adjustment, querying before the import is completed will not yield meaningful results. +``` + +## Provide Configuration and Logs for Technical Support + +If your SQL execution issue cannot be replicated through replication scripts or if it's not related to SQL execution but rather a cluster management problem, we kindly request that you provide us with configuration details and logs from both the client and server for further investigation. + +Whether you are using Docker or a local cluster setup (where all processes are on the same server), you can swiftly gather configuration, log files, and other information using diagnostic tools. + +You can initiate the OpenMLDB server using either the `init.sh`/`start-all.sh` command for clustered versions or the `init.sh standalone`/`start-standalone.sh` command for standalone versions. After starting the server, you can employ the following commands, which correspond to clustered and standalone versions, respectively. + +``` +openmldb_tool --env=onebox --dist_conf=cluster_dist.yml +openmldb_tool --env=onebox --dist_conf=standalone_dist.yml +``` +`cluster_dist.yml` and `stadnalone_dist.yml` can be found in the `/work/` directory within the Docker container. Alternatively, you can copy the yml file from the [GitHub directory](https://github.com/4paradigm/OpenMLDB/tree/main/demo) for your use. + +If you are working with a distributed cluster, it's essential to have SSH password-free configuration in place for smooth usage of the diagnostic tools. Please refer to the [Diagnostic Tool documentation](../maintain/diagnose.md) for guidance on setting this up. + +If your environment doesn't allow for SSH password-free configuration, please manually collect the configuration details and logs as needed. diff --git a/docs/en/quickstart/cli_tutorial.md b/docs/en/quickstart/cli.md similarity index 100% rename from docs/en/quickstart/cli_tutorial.md rename to docs/en/quickstart/cli.md diff --git a/docs/en/quickstart/function_boundary.md b/docs/en/quickstart/function_boundary.md new file mode 100644 index 00000000000..9c2c0b7ae14 --- /dev/null +++ b/docs/en/quickstart/function_boundary.md @@ -0,0 +1,165 @@ +# Functional Boundary + +This article will introduce the functional boundary of OpenMLDB SQL. + +```{note} +If you have any questions about SQL statements, please refer to OpenMLDB SQL or directly use the search function to search. +``` + +## System Configuration - TaskManager + +You can configure the TaskManager to define various settings, including the offline storage address (`offline.data.prefix`) and the Spark mode required for offline job computation (`spark.master`), among others. + +- `offline.data.prefix`: This can be configured as either a file path or an HDFS path. It is recommended to use an HDFS path for production environments, while a local file path can be configured for testing environments (specifically for onebox, such as running within a Docker container). Note that using a file path as offline storage will not support distributed deployment with multiple Task Managers (data won't be transferred between Task Managers). If you plan to deploy Task Managers on multiple hosts, please use storage media like HDFS that can be accessed simultaneously by multiple hosts. If you intend to test the collaboration of multiple Task Managers, you can deploy multiple Task Managers on a single host and use a file path as offline storage. +- `spark.master=local[*]`: The default Spark configuration is in `local[*]` mode, which automatically binds CPU cores. If offline tasks are found to be slow, it is recommended to use the Yarn mode. After changing the configuration, you need to restart the Task Manager for the changes to take effect. For more configurations, please refer to [master-urls](https://spark.apache.org/docs/3.1.2/submitting-applications.html#master-urls). + +### spark.default.conf + +More optional configurations can be written in the `spark.default.conf` parameter in the format of `k1=v1;k2=v2`. For example: + +```Plain +spark.default.conf=spark.port.maxRetries=32;foo=bar +``` + +`spark.port.maxRetries`: The default is set to 16, and you can refer to [Spark Configuration](https://spark.apache.org/docs/3.1.2/configuration.html). Each offline job is associated with a Spark UI, corresponding to a port. Each port starts from the default initial port and increments by one for retry attempts. If the number of concurrently running jobs exceeds `spark.port.maxRetries`, the number of retries will also exceed `spark.port.maxRetries`, causing job startup failures. If you need to support a larger job concurrency, configure a higher value for `spark.port.maxRetries` and restart the Task Manager to apply the changes. + +## DDL Boundary - DEPLOY Statement + +You can deploy an online SQL solution using the `DEPLOY ` command. This operation automatically parses the SQL statement and helps create indexes (you can view index details using `DESC `). For more information, please refer to the [DEPLOY STATEMENT](../openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md) documentation. + +The success of the deployment operation is dependent on the presence of online data in the table. + +### Long Window SQL + +Long Window SQL: This refers to the `DEPLOY` statement with the `OPTIONS(long_windows=...)` configuration item. For syntax details, please refer to [Long Window](../openmldb_sql/deployment_manage/DEPLOY_STATEMENT.md#long-window-optimazation). Deployment conditions for long-window SQL are relatively strict, and it's essential to ensure that the tables used in the SQL statements do not contain online data. Otherwise, even if deploying SQL that matches the previous one, the operation will still fail. + +### Normal SQL + +- If the relevant index already exists before deployment, the `DEPLOY` operation will not create the index. The `DEPLOY` operation will succeed regardless of whether there is online data in the table. +- If a new index needs to be created during deployment, and there is already online data in the table, the `DEPLOY` operation will fail. + +There are two solutions: + +1. Strictly perform `DEPLOY` before importing online data, and avoid executing `DEPLOY` after online data is present in the table. +2. The `CREATE INDEX` statement can automatically import existing online data (data from existing indexes) when creating a new index. If it is necessary to execute `DEPLOY` when the table already has online data, you can manually execute a `CREATE INDEX` to create the required index (the new index will already have data), and then execute `DEPLOY` (in this case, `DEPLOY` will not create a new index, and the manually created indexes will be used directly for computation). + +```{note} +How can you determine which indexes to create? + +Currently, only the Java SDK supports this feature, and all the required indexes can be obtained through `SqlClusterExecutor.genDDL`. However, you will need to manually convert them into `CREATE INDE`X statements as `genDD`L provides table creation statements. In the future, it will support ** directly obtaining index creation statements** or **automatically importing data into a new index** with `DEPLOY`. +``` + +## DML Boundary + +### Offline Information + +There are two types of paths in the offline information of a table: `offline_path` and `symbolic_paths`. `offline_path` is the actual storage path for offline data, while `symbolic_paths` are soft link paths for offline data. Both paths can be modified using the `LOAD DATA` command, and `symbolic_paths` can also be modified using the `ALTER` statement. + +The key difference between `offline_path` and `symbolic_paths` is that `offline_path` is the path owned by the OpenMLDB cluster. If a hard copy is implemented, data will be written to this path. On the other hand, `symbolic_paths` are paths outside the OpenMLDB cluster, and soft copies will add a path to this information. When querying offline, data from both paths will be loaded. Both paths use the same format and read options and do not support paths with different configurations. + +Therefore, if `offline_path` already exists offline, the `LOAD DATA` command can only modify `symbolic_paths`. If `symbolic_paths` already exist offline, the `LOAD DATA` command can be used to modify both `offline_path` and `symbolic_paths`. + +The `errorifexists` option will raise an error if there is offline information in the table. It will raise errors if performing hard copy when there's soft links, or performing soft copy when a hard copy exisits. + +### LOAD DATA + +Regardless of whether data is imported online or offline using the `LOAD DATA` command, it is considered an offline job. The format rules for source data are the same for both offline and online scenarios. + +It is recommended to use HDFS files as source data. This approach allows for successful import whether TaskManager is in local mode, Yarn mode, or running on another host. However, if the source data is a local file, the ability to import it smoothly depends on the mode of TaskManager and the host where it is running: + +- In local mode, TaskManager can successfully import source data only if the source data is placed on the same host as the TaskManager process. +- When TaskManager is in Yarn mode (both client and cluster), a file path cannot be used as the source data address because it is not known on which host the container is running. + +### DELETE + +In tables with multiple indexes in the online storage, a `DELETE` operation may not delete corresponding data in all indexes. Consequently, there may be situations where data has been deleted, but the deleted data can still be found. + +For example: + +```SQL +create database db; +use db; +create table t1(c1 int, c2 int,index(key=c1),index(key=c2)); +desc t1; +set @@execute_mode='online'; +insert into t1 values (1,1),(2,2); +delete from t1 where c2=2; +select * from t1; +select * from t1 where c2=2; +``` + +The results are as follows: + +```Plain + --- ------- ------ ------ --------- + Field Type Null Default + --- ------- ------ ------ --------- + 1 c1 Int YES + 2 c2 Int YES + --- ------- ------ ------ --------- + --- -------------------- ------ ---- ------ --------------- + name keys ts ttl ttl_type + --- -------------------- ------ ---- ------ --------------- + 1 INDEX_0_1668504212 c1 - 0min kAbsoluteTime + 2 INDEX_1_1668504212 c2 - 0min kAbsoluteTime + --- -------------------- ------ ---- ------ --------------- + -------------- + storage_mode + -------------- + Memory + -------------- + ---- ---- + c1 c2 + ---- ---- + 1 1 + 2 2 + ---- ---- + +2 rows in set + ---- ---- + c1 c2 + ---- ---- + +0 rows in set +``` + +Explanation: + +Table `t1` has multiple indexes (which may be automatically created during `DEPLOY`). If you run `delete from t1 where c2=2`, it only deletes data in the second index, while the data in the first index remains unaffected. Therefore, if you subsequently run `select * from t1` and it uses the first index, there are two pieces of data that haven't been deleted. `select * from t1 where c2=2` uses the second index, and the result is empty, with data being successfully deleted. + +## DQL Boundary + +The supported query modes (i.e. `SELECT` statements) vary depending on the execution mode: + +| Execution Mode | Query Statement | +| -------------- | ------------------------------------------------------------ | +| Offline Mode | Batch query | +| Online Mode | Batch query (also known as online preview mode, only supports partial SQL) and request query (also known as online request mode) | + +### Online Preview Mode + +In OpenMLDB CLI, executing SQL in online mode puts it in online preview mode. Please note that online preview mode has limited support; you can refer to the [SELECT STATEMENT](../openmldb_sql/dql/SELECT_STATEMENT) documentation for more details. + +Online preview mode is primarily for previewing query results. If you need to run complex SQL queries, it's recommended to use offline mode. To query complete online data, consider using a data export tool such as the `SELECT INTO` command. Keep in mind that if the online table contains a large volume of data, it might trigger data truncation, and executing `SELECT * FROM table` could result in some data not being returned. + +Online data is usually distributed across multiple locations, and when you run `SELECT * FROM table`, it retrieves results from various Tablet Servers without performing global sorting. As a result, the order of data will be different with each execution of `SELECT * FROM table`. + +### Offline Mode and Online Request Mode + +In the [full process](./concepts/modes.md) of feature engineering development and deployment, offline mode and online request mode play prominent roles: + +- Offline Mode Batch Query: Used for offline feature generation. +- Query in Online Request Mode: Employed for real-time feature computation. + +While these two modes share the same SQL statements and produce consistent computation results, due to the use of two different execution engines (offline and online), not all SQL statements that work offline can be deployed online. SQL that can be executed in online request mode is a subset of offline executable SQL. Therefore, it's essential to test whether SQL can be deployed using `DEPLOY` after completing offline SQL development. + +## Offline Command Synchronization Mode + +All offline commands can be executed in synchronous mode using `set @@sync_job=true;`. In this mode, the command will only return after completion, whereas in asynchronous mode, job info is immediately returned, requires usage of `SHOW JOB ` to check the execution status of the job. In synchronous mode, the return values differ depending on the command. + +- DML commands like `LOAD DATA` and DQL commands like `SELECT INTO` return the ResultSet of Job Info. These results are identical to those in asynchronous mode, with the only difference being the return time. +- Normal `SELECT` queries in DQL return Job Info in asynchronous mode and query results in synchronous mode. However, support for this feature is currently incomplete, as explained in [Offline Sync Mode-select](../openmldb_sql/dql/SELECT_STATEMENT.md#offline-sync-mode-select). The results are in CSV format, but data integrity is not guaranteed, so it's not recommended to use as accurate query results. + - In the CLI interactive mode, the results are printed directly. + - In the SDK, ResultSet is returned, the query result as a string. Consequently, it's not recommended to use synchronous mode queries in the SDK and process their results. + +Synchronous mode comes with timeout considerations, which are detailed in [Configuration](../openmldb_sql/ddl/SET_STATEMENT.md#offline-command-configuaration-details). diff --git a/docs/en/quickstart/index.rst b/docs/en/quickstart/index.rst index aefceb8f206..aac5878eede 100644 --- a/docs/en/quickstart/index.rst +++ b/docs/en/quickstart/index.rst @@ -7,5 +7,8 @@ Quickstart openmldb_quickstart concepts/index - cli_tutorial + cli sdk/index + beginner_must_read + function_boundary + diff --git a/docs/zh/quickstart/beginner_must_read.md b/docs/zh/quickstart/beginner_must_read.md index 37f1b57ae8e..f5ba729613f 100644 --- a/docs/zh/quickstart/beginner_must_read.md +++ b/docs/zh/quickstart/beginner_must_read.md @@ -90,7 +90,7 @@ create table t1(c1 int; ``` create database db; use db; --- create youer table +-- create your table create table xx (); -- offline or online diff --git a/docs/zh/quickstart/function_boundary.md b/docs/zh/quickstart/function_boundary.md index 801d5d1b111..5d656f8eb75 100644 --- a/docs/zh/quickstart/function_boundary.md +++ b/docs/zh/quickstart/function_boundary.md @@ -147,7 +147,7 @@ OpenMLDB CLI 中在线模式下执行 SQL，均为在线预览模式。在线预 ### 离线模式与在线请求模式 -在[特征工程开发上线全流程](../tutorial/concepts/modes.md#11-特征工程开发上线全流程)中，主要使用离线模式和在线请求模式。 +在[特征工程开发上线全流程](./concepts/modes.md)中，主要使用离线模式和在线请求模式。 - 离线模式的批查询：离线特征生成 - 在线请求模式的请求查询：实时特征计算 @@ -164,4 +164,4 @@ OpenMLDB CLI 中在线模式下执行 SQL，均为在线预览模式。在线预 - CLI是交互模式，所以将结果直接打印。 - SDK中，返回的是一行一列的ResultSet，将整个查询结果作为一个字符串返回。所以，不建议SDK使用同步模式查询，并处理其结果。 -同步模式涉及超时问题，详情见[调整配置](../../openmldb_sql/ddl/SET_STATEMENT.md#离线命令配置详情)。 +同步模式涉及超时问题，详情见[调整配置](../openmldb_sql/ddl/SET_STATEMENT.md#离线命令配置详情)。 From 7aed9c724b2e41f186f5fc7811b11f2950e35b3e Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Thu, 12 Oct 2023 14:18:19 +0800 Subject: [PATCH 10/32] docs: change for index file of integration folder (#3485) --- docs/en/integration/deploy_integration/index.rst | 14 ++++++++++++++ docs/en/integration/develop/index.rst | 8 ++++++++ docs/en/integration/index.rst | 13 +++++++++++++ docs/en/integration/online_datasources/index.rst | 13 +++++++++++++ 4 files changed, 48 insertions(+) create mode 100644 docs/en/integration/deploy_integration/index.rst create mode 100644 docs/en/integration/develop/index.rst create mode 100644 docs/en/integration/index.rst create mode 100644 docs/en/integration/online_datasources/index.rst diff --git a/docs/en/integration/deploy_integration/index.rst b/docs/en/integration/deploy_integration/index.rst new file mode 100644 index 00000000000..15bff333619 --- /dev/null +++ b/docs/en/integration/deploy_integration/index.rst @@ -0,0 +1,14 @@ +============================= +dispatch +============================= + +.. toctree:: + :maxdepth: 1 + + airflow_provider_demo + dolphinscheduler_task_demo + OpenMLDB_Byzer_taxi + + + + diff --git a/docs/en/integration/develop/index.rst b/docs/en/integration/develop/index.rst new file mode 100644 index 00000000000..13e8fad3619 --- /dev/null +++ b/docs/en/integration/develop/index.rst @@ -0,0 +1,8 @@ +============================= +Develop +============================= + +.. toctree:: + :maxdepth: 1 + + jupyter_notebook \ No newline at end of file diff --git a/docs/en/integration/index.rst b/docs/en/integration/index.rst new file mode 100644 index 00000000000..023bd3c9ab9 --- /dev/null +++ b/docs/en/integration/index.rst @@ -0,0 +1,13 @@ +============================= +Upstream and downstream ecology +============================= + +.. toctree:: + :maxdepth: 1 + + online_datasources/index + offline_data_sources/index + deploy_integration/index + develop/index + + diff --git a/docs/en/integration/online_datasources/index.rst b/docs/en/integration/online_datasources/index.rst new file mode 100644 index 00000000000..7b2232ef05b --- /dev/null +++ b/docs/en/integration/online_datasources/index.rst @@ -0,0 +1,13 @@ +============================= +online data source +============================= + +.. toctree:: + :maxdepth: 1 + + kafka_connector_demo + pulsar_connector_demo + rocketmq_connector + + + From 50a11edcce81cd92fd3b34af84e7bb3a13179e3f Mon Sep 17 00:00:00 2001 From: HuangWei Date: Thu, 12 Oct 2023 16:42:31 +0800 Subject: [PATCH 11/32] docs: add case when desc (#3523) --- .../functions_and_operators/operators.md | 27 ++++++++++++------- 1 file changed, 18 insertions(+), 9 deletions(-) diff --git a/docs/zh/openmldb_sql/functions_and_operators/operators.md b/docs/zh/openmldb_sql/functions_and_operators/operators.md index e5a7ca86afe..31d79184bd8 100644 --- a/docs/zh/openmldb_sql/functions_and_operators/operators.md +++ b/docs/zh/openmldb_sql/functions_and_operators/operators.md @@ -1,4 +1,4 @@ -# 运算符 +# 表达式和运算符 ## 运算符优先级 @@ -19,9 +19,7 @@ %left UNARY_PRECEDENCE // For all unary operators, +, -, ~ ``` -## 各类运算 - -### 1. 比较运算 +## 比较运算 | 操作符名 | 功能描述 | | :-------------- | :--------------------- | @@ -37,7 +35,7 @@ | `ILIKE` | 模糊匹配, 大小写不敏感 | | `RLIKE` | 正则表达式匹配 | -### 2. 逻辑运算 +## 逻辑运算 | 操作符名 | 功能描述 | | :---------- | :------- | @@ -46,7 +44,7 @@ | `XOR` | 逻辑与或 | | `NOT`, `!` | 逻辑非, unary operator | -### 3. 算术运算 +## 算术运算 | 操作符名 | 功能描述 | | :--------- | :------------------------------------------------------- | @@ -59,7 +57,7 @@ | `+` | Unary plus | | `-` | Unary minus, 只支持数值型操作数-number | -### 4. 位运算 +## 位运算 | 操作符名 | Description | | :------- | :---------- | @@ -68,7 +66,7 @@ | `^` | Bitwise XOR | | `~` | Bitwise NOT, unary operator | -### 5. 类型运算和函数 +## 类型运算和函数 | 操作符名 | Description | | :------------- | :--------------------------------------------------------- | @@ -97,7 +95,7 @@ SELECT INT(1.2); X：表示从原类型转换为目标类型的转换是不支持的 -| src\|dist | bool | smallint | int | float | int64 | double | timestamp | date | string | +| src\|dst | bool | smallint | int | float | int64 | double | timestamp | date | string | | :------------ | :----- | :------- | :----- | :----- | :----- | :----- | :-------- | :----- | :----- | | **bool** | Safe | Safe | Safe | Safe | Safe | Safe | UnSafe | X | Safe | | **smallint** | UnSafe | Safe | Safe | Safe | Safe | Safe | UnSafe | X | Safe | @@ -114,3 +112,14 @@ X：表示从原类型转换为目标类型的转换是不支持的 | 操作符名 | 功能描述 | | :------- | :------------------------ | | `=` | 赋值 (可用于 SET 语句中 ) | + +## 条件表达式 + +### CASE 表达式 + ```sql + SELECT case 'bb' when 'aa' then 'apple' else 'nothing' end; -- SIMPLE CASE WHEN + SELECT case + when 'bb'='aa' then 'apple' + when 'bb'='bb' then 'banana' + else 'nothing' end; -- SEARCHED CASE WHEN + ``` From db52ce909d07ffa0a07bbee97cd07fffe7e1c009 Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Fri, 13 Oct 2023 17:46:23 +0800 Subject: [PATCH 12/32] docs: change_for_status_and_index_of_maintain_folder (#3478) * Change for status and index of maintain folder * Update status.md * Update status.md --------- Co-authored-by: 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you can monitor the outcomes of these operations, along with the current health status of the database, through a series of commonly used command combinations. By sequentially running the `showopstatus` and `showtablestatus` commands, you can ultimately verify the successful completion of the relevant maintenance tasks. + +## Step 1: View Command Status with `showopstatus` + +The `showopstatus` command serves the purpose of observing the execution status of specific maintenance commands. The current NS client supports this command to track the status of maintenance commands like `addreplica`, `delreplica`, `migrate`, `offlineendpoint`, `recoverendpoint`, `changeleader`, and `recovertable`. For a comprehensive understanding of these supported maintenance commands, refer to the [Operations CLI](./cli.md) document. + +You can monitor the status of relevant commands by utilizing the `showopstatus` command of the [OpenMLDB Operations Tool](./openmldb_ops.md) `openmldb_ops.py`, as shown in the example below: + +```bash +python tools/openmldb_ops.py --openmldb_bin_path=./bin/openmldb --zk_cluster=127.0.0.1:2181 --zk_root_path=/openmldb --cmd=showopstatus +``` + +Due to the asynchronous nature of maintenance command execution, you might need to run the `showopstatus` command multiple times to confirm the final state. The state transitions for related commands can occur in three stages: + +1. kInited => kDoing => kDone: Indicates successful command execution. +2. kInited => kDoing => kFailed: Denotes a failed command execution. +3. kInited => kCancelled: This state may arise after manually executing the `cancelop` command. + +Once the command running status changes to `kDone`, it signifies the successful execution of relevant commands. You can then proceed to the subsequent steps and use the `showtablestatus` command to inspect the status of tables. + +## Step 2: View Table Status with `showtablestatus` + +After successfully executing the relevant maintenance commands, it's crucial to perform an additional verification to identify any anomalies in the table status. This verification can be conducted using the `showtablestatus` command within the [OpenMLDB Operations and Maintenance Tool](./openmldb_ops.md). For instance: + +```bash +python tools/openmldb_ops.py --openmldb_bin_path=./bin/openmldb --zk_cluster=127.0.0.1:2181 --zk_root_path=/openmldb --cmd=showtablestatus +``` + +Upon execution, this command will generate a series of table-related information. Of particular importance is the column labeled `Partition_unalive`. If this column's value is 0, it signifies that the table is in a normal state. Conversely, any non-zero value indicates the presence of an anomaly, as illustrated in the following example: + +![image-20230113144942187](images/showtablestatus.png) From e9f01ddce7e3f88a8c8c712cc8edc299f7ad6b8a Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Mon, 16 Oct 2023 16:39:07 +0800 Subject: [PATCH 13/32] docs: change_for_jupyter_notebook_of_integration_develop_folder (#3472) * Change for jupyter_notebook of integration develop folder * Update jupyter_notebook.md * Update jupyter_notebook.md --------- Co-authored-by: Siqi Wang --- docs/en/integration/develop/images/muti.png | Bin 0 -> 174040 bytes docs/en/integration/develop/images/single.png | Bin 0 -> 67164 bytes .../develop/images/support_function.png | Bin 0 -> 113659 bytes .../integration/develop/jupyter_notebook.md | 64 ++++++++++++++++++ 4 files changed, 64 insertions(+) create mode 100644 docs/en/integration/develop/images/muti.png create mode 100644 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m_El3w$X|a~}{3uP+L;nZn{oir` literal 0 HcmV?d00001 diff --git a/docs/en/integration/develop/jupyter_notebook.md b/docs/en/integration/develop/jupyter_notebook.md new file mode 100644 index 00000000000..b15488958a8 --- /dev/null +++ b/docs/en/integration/develop/jupyter_notebook.md @@ -0,0 +1,64 @@ +# Jupyter Notebook + +Jupyter Notebook offers various functionalities, such as data computation, code development, document editing, code execution, and result display, through a browser-based web page. It is currently one of the most popular and user-friendly development environments. This article introduces the seamless integration of OpenMLDB and Notebook, harnessing the functional features of OpenMLDB and the convenience of Notebook to create a fast and user-friendly machine-learning development environment. + +## Integration of the Magic Function + +The SQL magic function is an extension of Notebook that allows users to execute SQL statements directly in a Notebook cell without writing complex Python code. It also supports customized output. OpenMLDB provides a standard SQL magic function that allows users to write and run OpenMLDB-supported SQL statements directly in the Notebook. These statements are submitted to OpenMLDB for execution, and the results are previewed and displayed in the Notebook. + +### Register OpenMLDB SQL Magic Function + +To support OpenMLDB magic function in Notebook, register as follows: + + ```Python + import openmldb + db = openmldb.dbapi.connect(database='demo_db',zk='0.0.0.0:2181',zkPath='/openmldb') + openmldb.sql_magic.register(db) + ``` + +### Execute a Single SQL Statement + +Developers can use the prompt `%` to execute a single-line SQL statement, as shown in the following figure. + +![img](images/single.png) + +### Execute multiple SQL statement + +Developers can also use the prompt `%%` to write multi-line SQL statements, as shown in the following figure. + +![img](images/muti.png) + +Please note that currently, executing multiple SQL statements simultaneously within a Notebook cell is not supported. Each SQL statement needs to be executed separately in different cells. + +### Magic Function + +The SQL magic function provided by OpenMLDB can execute all supported SQL syntax, including the unique offline mode of OpenMLDB, which allows for asynchronously submitting complex big data SQL statements to the offline execution engine, as shown in the following figure. + +![img](images/support_function.png) + +For more detailed instructions on using the OpenMLDB magic function, please refer to [The Use of Notebook Magic Function](https://openmldb.ai/docs/en/main/quickstart/sdk/python_sdk.html#notebook-magic-function). + +## Integration of OpenMLDB Python SDK with Notebook + +Notebook supports the Python runtime kernel, enabling the import and usage of various Python libraries through import statements. OpenMLDB provides a fully functional Python SDK that can be called within Notebook. OpenMLDB Python SDK not only offers a DBAPI based on the Python PEP249 standard but also supports the mainstream SQLAlchemy interface, which enables connecting to existing OpenMLDB clusters with just one line of code. + +### The Use of OpenMLDB DBAPI + +Using the DBAPI interface is straightforward. You only need to specify the ZooKeeper address and node path for connection. Upon successful connection, corresponding log information will be displayed. You can call the DBAPI interface of the OpenMLDB Python SDK within Notebook for development, as detailed in [The Use of OpenMLDB DBAPI](https://openmldb.ai/docs/en/main/quickstart/sdk/python_sdk.html#openmldb-dbapi). + +```Python +import openmldb.dbapi +db = openmldb.dbapi.connect('demo_db','0.0.0.0:2181','/openmldb') +``` + +### Using OpenMLDB SQLAlchemy + +Using SQLAlchemy is also simple. You can establish the connection by specifying the URI of OpenMLDB through the SQLAlchemy library. Alternatively, you can connect to a standalone OpenMLDB database using IP and port as parameters, as shown below. + +```Python +import sqlalchemy as db +engine = db.create_engine('openmldb://demo_db?zk=127.0.0.1:2181&zkPath=/openmldb') +connection = engine.connect() +``` + +After a successful connection, development can be carried out through the SQLAlchemy interface of the OpenMLDB Python SDK, as detailed in [Using OpenMLDB SQLAlchemy](https://openmldb.ai/docs/en/main/quickstart/sdk/python_sdk.html#openmldb-sqlalchemy). From 8c8d07049cc96c8c658cf391254b91cca8cd9fdf Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Mon, 16 Oct 2023 16:41:22 +0800 Subject: [PATCH 14/32] docs: update_openmldb_quickstart_of_quickstart_folder (#3486) * docs-update-openmldb_quickstart-of-quickstart-folder * Update openmldb_quickstart.md * Docs: Update-modes_flow-image * Update openmldb_quickstart.md * Update openmldb_quickstart.md * Delete unused file --------- Co-authored-by: Siqi Wang --- .../quickstart/concepts/images/modes-flow.png | Bin 0 -> 333650 bytes docs/en/quickstart/images/cli_cluster.png | Bin 0 -> 358166 bytes docs/en/quickstart/images/state_finished.png | Bin 0 -> 170727 bytes docs/en/quickstart/openmldb_quickstart.md | 79 ++++++++---------- 4 files changed, 37 insertions(+), 42 deletions(-) create mode 100644 docs/en/quickstart/concepts/images/modes-flow.png create mode 100644 docs/en/quickstart/images/cli_cluster.png create mode 100644 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z0Gx2gw7ZdFS=uoPZi2%$(y>AC90QVZU9{iEvz0*jUTQsvH^r8q9li9sMEkdW(P>nB2e~pP|)mAK%DqOCdzL8`h%2s+#;;LqGrK3R%hwW z{?Urb#z~|oK3s)V|2xcAmnpmbcrWhev>%w49@CfjBesb6QRrR*G(=9|$O)dP-=l_K zKEo)&?QEXbvCAhO>yMX<^ktVeqeMnF9}b_XR_$AsU6|G`7bX!08s&ce=;%1ITsPLu z|9}3R|L-l#1D$0ld+$^%pM9~sb|ZEd4ZXbcV|gbn|4K~l{r5#V;#k+Bbxm@k@OPG{ LZB7x*U8DXNM%Fm7 literal 0 HcmV?d00001 From bba4e51422b7412d4b691f2fc2e89048d6479216 Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Thu, 26 Oct 2023 14:50:09 +0800 Subject: [PATCH 24/32] docs: update the quickstart and sdk folder (#3537) * Docs: Update-quickstart-sdk-folder * Docs: update-quickstart-sdk-index-file * Update compile.md Update referred document to the latest * Update cxx_sdk.md with recent updates * Update go_sdk.md * Update rest_api.md * Update java_sdk.md to most recent upate * Update python_sdk.md to most recent updates * Update python_sdk.md image reference link --------- Co-authored-by: Siqi Wang --- docs/en/deploy/compile.md | 105 ++++++++---- docs/en/quickstart/sdk/cpp_sdk.md | 117 -------------- docs/en/quickstart/sdk/cxx_sdk.md | 138 ++++++++++++++++ docs/en/quickstart/sdk/go_sdk.md | 12 +- docs/en/quickstart/sdk/index.rst | 4 +- docs/en/quickstart/sdk/java_sdk.md | 234 +++++++++++++++++++++------ docs/en/quickstart/sdk/python_sdk.md | 91 ++++++----- docs/en/quickstart/sdk/rest_api.md | 31 ++-- 8 files changed, 476 insertions(+), 256 deletions(-) delete mode 100644 docs/en/quickstart/sdk/cpp_sdk.md create mode 100644 docs/en/quickstart/sdk/cxx_sdk.md diff --git a/docs/en/deploy/compile.md b/docs/en/deploy/compile.md index a20c921b4ac..3fdd9826726 100644 --- a/docs/en/deploy/compile.md +++ b/docs/en/deploy/compile.md @@ -1,11 +1,9 @@ -# Build +# Compilation from Source Code -## 1. Quick Start +## Compile and Use in Docker Container -[quick-start]: quick-start - -This section describes the steps to compile and use OpenMLDB inside its official docker image [hybridsql](https://hub.docker.com/r/4pdosc/hybridsql). -The docker image has packed required tools and dependencies, so there is no need to set them up separately. To compile without the official docker image, refer to the section [Detailed Instructions for Build](#detailed-instructions-for-build) below. +This section describes the steps to compile and use OpenMLDB inside its official docker image [hybridsql](https://hub.docker.com/r/4pdosc/hybridsql), mainly for quick start and development purposes in the docker container. +The docker image has packed the required tools and dependencies, so there is no need to set them up separately. To compile without the official docker image, refer to the section [Detailed Instructions for Build](#detailed-instructions-for-build) below. Keep in mind that you should always use the same version of both compile image and [OpenMLDB version](https://github.com/4paradigm/OpenMLDB/releases). This section demonstrates compiling for [OpenMLDB v0.8.3](https://github.com/4paradigm/OpenMLDB/releases/tag/v0.8.3) under `hybridsql:0.8.3` ，If you prefer to compile on the latest code in `main` branch, pull `hybridsql:latest` image instead. @@ -15,13 +13,13 @@ Keep in mind that you should always use the same version of both compile image a docker pull 4pdosc/hybridsql:0.8 ``` -2. Create a docker container with the hybridsql docker image +2. Create a docker container ```bash docker run -it 4pdosc/hybridsql:0.8 bash ``` -3. Download the OpenMLDB source code inside the docker container, and setting the branch into v0.8.3 +3. Download the OpenMLDB source code inside the docker container, and set the branch into v0.8.3 ```bash cd ~ @@ -41,52 +39,49 @@ Keep in mind that you should always use the same version of both compile image a make install ``` -Now you've finished the compilation job, and you may try run OpenMLDB inside the docker container. +Now you've finished the compilation job, you may try running OpenMLDB inside the docker container. -## 2. Detailed Instructions for Build +## Detailed Instructions for Build -[build]: build +This chapter discusses compiling source code without relying on pre-built container environments. -### 2.1. Hardware Requirements +### Hardware Requirements - **Memory**: 8GB+ recommended. - **Disk Space**: >=25GB of free disk space for full compilation. - **Operating System**: CentOS 7, Ubuntu 20.04 or macOS >= 10.15, other systems are not carefully tested but issue/PR welcome +- **CPU Architecture**: Currently, only x86 architecture is supported, and other architectures like ARM are not supported at the moment (please note that running x86 images on heterogeneous systems like M1 Mac is also not supported at this time). -Note: By default, the parallel build is disabled, and it usually takes an hour to finish all the compile jobs. You can enable the parallel build by tweaking the `NPROC` option if your machine's resource is enough. This will reduce the compile time but also consume more memory. For example, the following command set the number of concurrent build jobs to 4: +💡 Note: By default, the parallel build is disabled, and it usually takes an hour to finish all the compile jobs. You can enable the parallel build by tweaking the `NPROC` option if your machine's resource is enough. This will reduce the compile time but also consume more memory. For example, the following command sets the number of concurrent build jobs to 4: ```bash make NPROC=4 ``` -### 2.2. Prerequisites - -Make sure those tools are installed - +### Dependencies - gcc >= 8 or AppleClang >= 12.0.0 -- cmake 3.20 or later ( < cmake 3.24 is better) +- cmake 3.20 or later ( recommended < cmake 3.24) - jdk 8 - python3, python setuptools, python wheel - If you'd like to compile thirdparty from source, checkout the [third-party's requirement](../../third-party/README.md) for extra dependencies -### 2.3. Build and Install OpenMLDB +### Build and Install OpenMLDB Building OpenMLDB requires certain thirdparty dependencies. Hence a Makefile is provided as a convenience to setup thirdparty dependencies automatically and run CMake project in a single command `make`. The `make` command offers three methods to compile, each manages thirdparty differently: -- **Method One: Build and Run Inside Docker:** Using [hybridsql](https://hub.docker.com/r/4pdosc/hybridsql) docker image, the thirdparty is already bundled inside the image and no extra steps are required, refer to above section [Quick Start](#quick-start) -- **Method Two: Download Pre-Compiled Thirdparty:** Command is `make && make install`. It downloads necessary prebuild libraries from [hybridsql-assert](https://github.com/4paradigm/hybridsql-asserts/releases) and [zetasql](https://github.com/4paradigm/zetasql/releases). Currently it supports CentOS 7, Ubuntu 20.04 and macOS. -- **Method Three: Compile Thirdparty from Source:** This is the suggested way if the host system is not in the supported list for pre-compiled thirdparty (CentOS 7, Ubuntu 20.04 and macOS). Note that when compiling thirdparty for the first time requires extra time to finish, approximately 1 hour on a 2 core & 7 GB machine. To compile thirdparty from source, please pass `BUILD_BUNDLED=ON` to `make`: +- **Method One: Download Pre-Compiled Thirdparty:** Command is `make && make install`. It downloads necessary prebuild libraries from [hybridsql-assert](https://github.com/4paradigm/hybridsql-asserts/releases) and [zetasql](https://github.com/4paradigm/zetasql/releases). Currently it supports CentOS 7, Ubuntu 20.04 and macOS. +- **Method Two: Compile Thirdparty from Source:** This is the suggested way if the host system is not in the supported list for pre-compiled thirdparty (CentOS 7, Ubuntu 20.04 and macOS). Note that when compiling thirdparty for the first time requires extra time to finish, approximately 1 hour on a 2 core & 8 GB machine. To compile thirdparty from source, please pass `BUILD_BUNDLED=ON` to `make`: ```bash make BUILD_BUNDLED=ON make install ``` -All of the three methods above will install OpenMLDB binaries into `${PROJECT_ROOT}/openmldb` by default, you may tweak the installation directory with the option `CMAKE_INSTALL_PREFIX` (refer the following section [Extra options for `make`](#24-extra-options-for-make)). +All of the three methods above will install OpenMLDB binaries into `${PROJECT_ROOT}/openmldb` by default, you may tweak the installation directory with the option `CMAKE_INSTALL_PREFIX` (refer to the following section [Extra Parameters for `make`](#extra-parameters-for-make) ). -### 2.4. Extra Options for `make` +### Extra Parameters for `make` -You can customize the `make` behavior by passing following arguments, e.g., changing the build mode to `Debug` instead of `Release`: +You can customize the `make` behavior by passing the following arguments, e.g., changing the build mode to `Debug` instead of `Release`: ```bash make CMAKE_BUILD_TYPE=Debug @@ -132,10 +127,14 @@ make CMAKE_BUILD_TYPE=Debug Default: ON -- OPENMLDB_BUILD_TARGET: If you only want to build some targets, not all, e.g. only build a test `ddl_parser_test`, you can set it to `ddl_parser_test`. Multiple targets may be given, separated by spaces. It can reduce the build time, reduce the build output, save the storage space. +- OPENMLDB_BUILD_TARGET: If you only want to build some targets, not all, e.g. only build a test `ddl_parser_test`, you can set it to `ddl_parser_test`. Multiple targets may be given, separated by spaces. It can reduce build time, reduce build output, and save storage space. Default: all +- THIRD_PARTY_CMAKE_FLAGS: You can use this to configure additional parameters when compiling third-party dependencies. For instance, to specify concurrent compilation for each third-party project, you can set` THIRD_PARTY_CMAKE_FLAGS` to `-DMAKEOPTS=-j8`. Please note that NPROC does not affect third-party compilation; multiple third-party projects will be executed sequentially. + + Default: '' + ### Build Java SDK with Multi Processes ``` @@ -144,7 +143,7 @@ make SQL_JAVASDK_ENABLE=ON NPROC=4 The built jar packages are in the `target` path of each submodule. If you want to use the jar packages built by yourself, please DO NOT add them by systemPath(may get `ClassNotFoundException` about Protobuf and so on, requires a little work in compile and runtime phase). The better way is, use `mvn install -DskipTests=true -Dscalatest.skip=true -Dwagon.skip=true -Dmaven.test.skip=true -Dgpg.skip` to install them in local m2 repository, your project will use them. -## 3. Optimized Spark Distribution for OpenMLDB +## Optimized Spark Distribution for OpenMLDB [OpenMLDB Spark Distribution](https://github.com/4paradigm/spark) is the fork of [Apache Spark](https://github.com/apache/spark). It adopts specific optimization techniques for OpenMLDB. It provides native `LastJoin` implementation and achieves 10x~100x performance improvement compared with the original Spark distribution. The Java/Scala/Python/SQL APIs of the OpenMLDB Spark distribution are fully compatible with the standard Spark distribution. @@ -171,3 +170,55 @@ export SPARK_HOME=`pwd` ``` 3. Now you are all set to run OpenMLDB by enjoying the performance speedup from this optimized Spark distribution. + + +## Build for Other OS +As previously mentioned, if you want to run OpenMLDB or the SDK on a different OS, you will need to compile from the source code. We provide quick compilation solutions for several operating systems. For other OS, you'll need to perform source code compilation on your own. + +### Centos 6 or other glibc Linux OS +#### Local Compilation +To compile a version compatible with CentOS 6, you can use Docker and the `steps/centos6_build.sh` script. As shown below, we use the current directory as the mount directory and place the compilation output locally. + +```bash +git clone https://github.com/4paradigm/OpenMLDB.git +cd OpenMLDB +docker run -it -v`pwd`:/root/OpenMLDB ghcr.io/4paradigm/centos6_gcc7_hybridsql bash +``` +Execute the compilation script within the container, and the output will be in the "build" directory. If there are failures while downloading `bazel` or `icu4c` during compilation, you can use the image sources provided by OpenMLDB by configuring the environment variable `OPENMLDB_SOURCE=true`. Various environment variables that can be used with "make" will also work, as shown below. + +```bash +cd OpenMLDB +bash steps/centos6_build.sh +# THIRD_PARTY_CMAKE_FLAGS=-DMAKEOPTS=-j8 bash steps/centos6_build.sh # run fast when build single project +# OPENMLDB_SOURCE=true bash steps/centos6_build.sh +# SQL_JAVASDK_ENABLE=ON SQL_PYSDK_ENABLE=ON NPROC=8 bash steps/centos6_build.sh # NPROC will build openmldb in parallel, thirdparty should use THIRD_PARTY_CMAKE_FLAGS +``` + +For a local compilation with a 2.20GHz CPU, SSD hard drive, and 32 threads to build both third-party libraries and the OpenMLDB core, the approximate timeframes are as follows: +`THIRD_PARTY_CMAKE_FLAGS=-DMAKEOPTS=-j32 SQL_JAVASDK_ENABLE=ON SQL_PYSDK_ENABLE=ON NPROC=32 bash steps/centos6_build.sh` +- third-party (excluding source code download time): Approximately 40 minutes: + - Zetasql patch: 13 minutes + - Compilation of all third-party dependencies: 30 minutes +- OpenMLDB core, including Python and Java native components: Approximately 12 minutes + +Please note that these times can vary depending on your specific hardware and system performance. The provided compilation commands and environment variables are optimized for multi-threaded compilation, which can significantly reduce build times. + +#### Cloud Compilation + +After forking the OpenMLDB repository, you can trigger the `Other OS Build` workflow in `Actions`, and the output will be available in the `Actions` `Artifacts`. Here's how to configure the workflow: + +- Do not change the `Use workflow from` setting to a specific tag; it can be another branch. +- Choose the desired `OS name`, which in this case is `centos6`. +- If you are not compiling the main branch, provide the name of the branch, tag (e.g., v0.8.2), or SHA you want to compile in the `The branch, tag, or SHA to checkout, otherwise use the branch` field. +- The compilation output will be accessible in "runs", as shown in an example [here](https://github.com/4paradigm/OpenMLDB/actions/runs/6044951902). + - The workflow will definitely produce the OpenMLDB binary file. + - If you don't need the Java or Python SDK, you can configure `java sdk enable` or `python sdk enable` to be "OFF" to save compilation time. + +Please note that this compilation process involves building third-party dependencies from source code, and it may take a while to complete due to limited resources. The approximate time for this process is around 3 hours and 5 minutes (2 hours for third-party dependencies and 1 hour for OpenMLDB). However, the workflow caches the compilation output for third-party dependencies, so the second compilation will be much faster, taking approximately 1 hour and 15 minutes for OpenMLDB. + +### Macos 10.15, 11 + +MacOS doesn't require compiling third-party dependencies from source code, so compilation is relatively faster, taking about 1 hour and 15 minutes. Local compilation is similar to the steps outlined in the [Detailed Instructions for Build](#detailed-instructions-for-build) and does not require compiling third-party dependencies (`BUILD_BUNDLED=OFF`). For cloud compilation on macOS, trigger the `Other OS Build` workflow in `Actions` with the specified macOS version (`os name` as `macos10` or `macos11`). You can also disable Java or Python SDK compilation if they are not needed, by setting `java sdk enable` or `python sdk enable` to `OFF`. + + + diff --git a/docs/en/quickstart/sdk/cpp_sdk.md b/docs/en/quickstart/sdk/cpp_sdk.md deleted file mode 100644 index 59f4a284a63..00000000000 --- a/docs/en/quickstart/sdk/cpp_sdk.md +++ /dev/null @@ -1,117 +0,0 @@ -# C++ SDK - -## C++SDK package compilation and installation - -```plain -git clone git@github.com:4paradigm/OpenMLDB.git -cd OpenMLDB -make && make install -``` - -## Write user code - -The following code demonstrates the basic use of C++ SDK. openmldb_api.h and sdk/result_set.h is the header file that must be included. - -```c++ -#include -#include -#include - -#include "openmldb_api.h" -#include "sdk/result_set.h" - -int main() -{ - //Create and initialize the OpenmldbHandler object - //Stand-alone version: parameter (ip, port), such as: OpenmldbHandler handler ("127.0.0.1", 6527); - //Cluster version: parameters (ip: port, path), such as: OpenmldbHandler handler ("127.0.0.1:6527", "/openmldb"); - //Take the stand-alone version as an example. - OpenmldbHandler handler("127.0.0.1", 6527); - - // Define database name - std::time_t t = std::time(0); - std::string db = "test_db" + std::to_string(t); - - // Create SQL statement and database - std::string sql = "create database " + db + ";"; - // Execute the SQL statement. The execute() function returns the bool value. A value of true indicates correct execution - std::cout << execute(handler, sql); - - // Create SQL statement and use database - sql = "use " + db + ";"; - std::cout << execute(handler, sql); - - // Create SQL statement and create table - sql = "create table test_table (" - "col1 string, col2 bigint," - "index(key=col1, ts=col2));"; - std::cout << execute(handler, sql); - - // Create SQL statements and insert rows into the table - sql = "insert test_table values(\"hello\", 1)"; - std::cout << execute(handler, sql); - sql = "insert test_table values(\"Hi~\", 2)"; - std::cout << execute(handler, sql); - - // Basic mode - sql = "select * from test_table;"; - std::cout << execute(handler, sql); - - // Get the latest SQL execution result - auto res = get_resultset(); - // Output SQL execution results - print_resultset(res); - // The output in this example should be： - // +-------+--------+ - // | col1 | col2 | - // +-------+--------+ - // | hello | 1 | - // | Hi~ | 2 | - // +-------+---------+ - - - - // Band-parameter mode - //The position of the parameters to be filled in the SQL statement is set to "?" to express - sql = "select * from test_table where col1 = ? ;"; - // Create a ParameterRow object for filling parameters - ParameterRow para(&handler); - // Fill in parameters - para << "Hi~"; - // Execute SQL statement execute_parameterized() function returns the bool value. A value of true indicates correct execution - execute_parameterized(handler, db, sql, para); - res = get_resultset(); - print_resultset(res); - // The output in this example should be： - // +------+--------+ - // | col1 | col2 | - // +------+-------+ - // | Hi~ | 2 | - // +------+--------+ - - - // Request mode - sql = "select col1, sum(col2) over w as w_col2_sum from test_table " - "window w as (partition by test_table.col1 order by test_table.col2 " - "rows between 2 preceding and current row);"; - RequestRow req(&handler, db, sql); - req << "Hi~" << 3l; - execute_request(req); - res = get_resultset(); - print_resultset(res); - // The output in this example should be： - // +------+--------------------+ - // | col1 | w_col2_sum | - // +------+--------------------+ - // | Hi~ | 5 | - // +------+--------------------+ -} -``` - -## Compile and run - -```plain -gcc .cxx -o -lstdc++ -std=c++17 -I/include -L/lib -lopenmldbsdk -lpthread -./ -``` - diff --git a/docs/en/quickstart/sdk/cxx_sdk.md b/docs/en/quickstart/sdk/cxx_sdk.md new file mode 100644 index 00000000000..77041df9b52 --- /dev/null +++ b/docs/en/quickstart/sdk/cxx_sdk.md @@ -0,0 +1,138 @@ +# [Alpha] C++ SDK +```plain +The current functionality support of the C++ SDK is not yet complete. It is currently only recommended for development, testing, or specific use cases. It is not recommended for use in a production environment. For production use, we recommend using the Java SDK, which has the most comprehensive feature coverage and has undergone extensive testing for both functionality and performance. +``` +## C++ SDK Compilation and Installation +```plain +The C++ SDK static library is only supported on Linux systems and is not included in the standard release. If you need to use the C++ SDK library, you should compile the source code and enable the compilation option `INSTALL_CXXSDK=ON`. +``` +To compile, you need to meet the [hardware requirements](../../deploy/compile.md#hardware-requirements) and install the necessary [dependencies](../../deploy/compile.md#dependencies). +```plain +git clone git@github.com:4paradigm/OpenMLDB.git +cd OpenMLDB +make INSTALL_CXXSDK=ON && make install +``` + +## User Code + +The following code demonstrates the basic use of C++ SDK. `openmldb_api.h` and `sdk/result_set.h` is the header file that must be included. + +```c++ +#include +#include +#include + +#include "openmldb_api.h" +#include "sdk/result_set.h" + +int main() +{ + //Create and initialize the OpenmldbHandler object + //Stand-alone version: parameter (ip, port), such as: OpenmldbHandler handler ("127.0.0.1", 6527); + //Cluster version: parameters (ip: port, path), such as: OpenmldbHandler handler ("127.0.0.1:6527", "/openmldb"); + //Take the stand-alone version as an example. + OpenmldbHandler handler("127.0.0.1", 6527); + + // Define database name + std::time_t t = std::time(0); + std::string db = "test_db" + std::to_string(t); + + // Create SQL statement and database + std::string sql = "create database " + db + ";"; + // Execute the SQL statement. The execute() function returns bool. true indicates correct execution + std::cout << execute(handler, sql); + + // Create SQL statement to use database + sql = "use " + db + ";"; + std::cout << execute(handler, sql); + + // Create SQL statement to create table + sql = "create table test_table (" + "col1 string, col2 bigint," + "index(key=col1, ts=col2));"; + std::cout << execute(handler, sql); + + // Create SQL statements to insert rows into the table + sql = "insert test_table values(\"hello\", 1)"; + std::cout << execute(handler, sql); + sql = "insert test_table values(\"Hi~\", 2)"; + std::cout << execute(handler, sql); + + // Basic mode + sql = "select * from test_table;"; + std::cout << execute(handler, sql); + + // Get the latest SQL execution result + auto res = get_resultset(); + // Output SQL execution results + print_resultset(res); + // The output in this example should be： + // +-------+--------+ + // | col1 | col2 | + // +-------+--------+ + // | hello | 1 | + // | Hi~ | 2 | + // +-------+---------+ + + + + // Parameter mode + //The parameters to be filled in the SQL statement is marked as "?" + sql = "select * from test_table where col1 = ? ;"; + // Create a ParameterRow object for filling parameters + ParameterRow para(&handler); + // Fill in parameters + para << "Hi~"; + // Execute SQL statement, execute_parameterized() function returns bool. true indicates correct execution + execute_parameterized(handler, db, sql, para); + res = get_resultset(); + print_resultset(res); + // The output in this example should be： + // +------+--------+ + // | col1 | col2 | + // +------+-------+ + // | Hi~ | 2 | + // +------+--------+ + + + // Request mode + sql = "select col1, sum(col2) over w as w_col2_sum from test_table " + "window w as (partition by test_table.col1 order by test_table.col2 " + "rows between 2 preceding and current row);"; + RequestRow req(&handler, db, sql); + req << "Hi~" << 3l; + execute_request(req); + res = get_resultset(); + print_resultset(res); + // The output in this example should be： + // +------+--------------------+ + // | col1 | w_col2_sum | + // +------+--------------------+ + // | Hi~ | 5 | + // +------+--------------------+ +} +``` +## Multi-Thread +The `OpenMLDBHandler` object is not thread-safe, but the internal connection to the `SQLClusterRouter` can be used multi-threaded. You can achieve multi-threading by sharing the Router within the Handler object, which is more efficient than creating multiple independent Handler instances (each with its independent Router). However, in a multi-threaded mode, you should be cautious because interfaces without db depend on the Router's internal cache of used db, which might be modified by other threads. It's advisable to use the db interface in such cases. The following code demonstrates a method for multi-threaded usage: + +```c++ +OpenmldbHandler h1("127.0.0.1:2181", "/openmldb"); +OpenmldbHandler h2(h1.get_router()); + +std::thread t1([&](){ h1.execute("show components;"); print_resultset(h1.get_resultset());}); + +std::thread t2([&](){ h2.execute("show table status;"); print_resultset(h2.get_resultset());}); + +t1.join(); +t2.join(); +``` + +## Compile and run +You can refer to [Makefile](https://github.com/4paradigm/OpenMLDB/blob/main/demo/cxx_quickstart/Makefile) or use the command below to compile and run the sample code. + +```bash +gcc .cxx -o -lstdc++ -std=c++17 -I/include -L/lib -lopenmldbsdk -lpthread -lm -ldl -lstdc++fs + +./ +``` + diff --git a/docs/en/quickstart/sdk/go_sdk.md b/docs/en/quickstart/sdk/go_sdk.md index c30cbb2e502..4c07120a932 100644 --- a/docs/en/quickstart/sdk/go_sdk.md +++ b/docs/en/quickstart/sdk/go_sdk.md @@ -1,12 +1,14 @@ -# Go SDK - +# [Alpha] Go SDK +```plain +The current functionality support of the Go SDK is not yet complete. It is currently only recommended for development, testing, or specific use cases. It is not recommended for use in a production environment. For production use, we recommend using the Java SDK, which has the most comprehensive feature coverage and has undergone extensive testing for both functionality and performance. +``` ## Requirement - OpenMLDB version: >= v0.6.2 -- Deploy and run APIServer (refer to [APIServer deployment](https://openmldb.ai/docs/zh/main/deploy/install_deploy.html#apiserver) document) +- Deploy and run APIServer (refer to [APIServer deployment](../../main/deploy/install_deploy.html#apiserver) document) -## Go SDK package installment +## Go SDK installation ```bash go get github.com/4paradigm/OpenMLDB/go @@ -76,7 +78,7 @@ import ( "context" "database/sql" - // 加载 OpenMLDB SDK + // Load OpenMLDB SDK _ "github.com/4paradigm/OpenMLDB/go" ) diff --git a/docs/en/quickstart/sdk/index.rst b/docs/en/quickstart/sdk/index.rst index 2eec974bee0..d932b7f5442 100644 --- a/docs/en/quickstart/sdk/index.rst +++ b/docs/en/quickstart/sdk/index.rst @@ -7,6 +7,6 @@ SDK java_sdk python_sdk - rest_api go_sdk - cpp_sdk + cxx_sdk + rest_api \ No newline at end of file diff --git a/docs/en/quickstart/sdk/java_sdk.md b/docs/en/quickstart/sdk/java_sdk.md index a74f4c98f3c..489dea47282 100644 --- a/docs/en/quickstart/sdk/java_sdk.md +++ b/docs/en/quickstart/sdk/java_sdk.md @@ -1,8 +1,10 @@ # Java SDK -## Java SDK package installation +In Java SDK, the default execution mode for JDBC Statements is online, while the default execution mode for SqlClusterExecutor is offline. Please keep this in mind. -- Installing Java SDK package on Linux +## Java SDK Installation + +- Install Java SDK on Linux Configure the maven pom: @@ -19,7 +21,7 @@ ``` -- Installing Java SDK package on Mac +- Install Java SDK on Mac Configure the maven pom @@ -36,16 +38,14 @@ ``` -Note: Since the openmldb-native package contains the C++ static library compiled for OpenMLDB, it is defaults to the Linux static library. For macOS, the version of openmldb-native should be changed to `0.8.3-macos`, while the version of openmldb-jdbc should remain unchanged. - -The macOS version of openmldb-native only supports macOS 12. To run it on macOS 11 or macOS 10.15, the openmldb-native package needs to be compiled from source code on the corresponding OS. For detailed compilation methods, please refer to [Concurrent Compilation of Java SDK](https://openmldb.ai/docs/zh/main/deploy/compile.html#java-sdk). - -To connect to the OpenMLDB service using the Java SDK, you can use JDBC (recommended) or connect directly through SqlClusterExecutor. The following will demonstrate both connection methods in order. +Note: Since the openmldb-native package contains the C++ static library compiled for OpenMLDB, it defaults to the Linux static library. For macOS, the version of openmldb-native should be changed to `0.8.3-macos`, while the version of openmldb-jdbc remains unchanged. -## JDBC method +The macOS version of openmldb-native only supports macOS 12. To run it on macOS 11 or macOS 10.15, the openmldb-native package needs to be compiled from the source code on the corresponding OS. For detailed compilation methods, please refer to [Java SDK](../../deploy/compile.md#Build-java-sdk-with-multi-processes). +When using a self-compiled openmldb-native package, it is recommended to install it into your local Maven repository using `mvn install`. After that, you can reference it in your project's pom.xml file. It's not advisable to reference it using `scope=system`. -The connection method using JDBC is as follows: +To connect to the OpenMLDB service using the Java SDK, you can use JDBC (recommended) or connect directly through SqlClusterExecutor. The following will demonstrate both connection methods. +## Connection with JDBC ```java Class.forName("com._4paradigm.openmldb.jdbc.SQLDriver"); // No database in jdbcUrl @@ -58,10 +58,10 @@ Connection connection1 = DriverManager.getConnection("jdbc:openmldb:///test_db?z The database specified in the Connection address must exist when creating the connection. ```{caution} -he default execution mode for JDBC Connection is `online`. +The default execution mode for JDBC Connection is `online`. ``` -### Usage overview +### Statement All SQL commands can be executed using `Statement`, both in online and offline modes. To switch between offline and online modes, use command `SET @@execute_mode='...';``. For example: @@ -77,17 +77,22 @@ res = stmt.executeQuery("SELECT * from t1"); // For online mode, select or execu The `LOAD DATA` command is an asynchronous command, and the returned ResultSet contains information such as the job ID and state. You can execute `show job ` to check if the job has been completed. Note that the ResultSet needs to execute `next()` method to move the cursor to the first row of data. -It is also possible to change it to a synchronous command: +In offline mode, the default behavior is asynchronous execution, and the ResultSet returned is a Job Info. You can change this behavior to synchronous execution using `SET @@sync_job=true;`. However, please note that the ResultSet returned can vary depending on the specific SQL command. For more details, please refer to the [Function Boundary](../function_boundary.md). Synchronous execution is recommended when using `LOAD DATA` or `SELECT INTO` commands. -```SQL -SET @@sync_job=true; -``` +If synchronous commands are timing out, you can adjust the configuration as described in the [Offline Command Configuration](../../openmldb_sql/ddl/SET_STATEMENT.md). -If the actual execution time of the synchronous command exceeds the default maximum idle wait time of 0.5 hours, please [adjust the configuration](https://openmldb.ai/docs/zh/main/openmldb_sql/ddl/SET_STATEMENT.html#id4). +```{caution} +When you execute `SET @@execute_mode='offline'` on a `Statement`, it not only affects the current `Statement` but also impacts all `Statement` objects created, both existing and yet to be created, within the same `Connection`. Therefore, it is not advisable to create multiple `Statement` objects and expect them to execute in different modes. If you need to execute SQL in different modes, it's recommended to create multiple `Connection`. +``` ### PreparedStatement -`PreparedStatement` supports `SELECT`, `INSERT`, and `DELETE` operations. Note that `INSERT` only supports online insertion. +`PreparedStatement` supports `SELECT`, `INSERT`, and `DELETE`. +```{warning} +Any `PreparedStatement` executes only in the **online mode** and is not affected by the state before the `PreparedStatement` is created. `PreparedStatement` does not support switching to the offline mode. If you need to execute SQL in the offline mode, you can use a `Statement`. + +There are three types of `PreparedStatement` created by a `Connection`, which correspond to `getPreparedStatement`, `getInsertPreparedStmt`, and `getDeletePreparedStm`t in SqlClusterExecutor. +``` ```java PreparedStatement selectStatement = connection.prepareStatement("SELECT * FROM t1 WHERE id=?"); @@ -95,9 +100,10 @@ PreparedStatement insertStatement = connection.prepareStatement("INSERT INTO t1 PreparedStatement insertStatement = connection.prepareStatement("DELETE FROM t1 WHERE id=?"); ``` -## SqlClusterExecutor method +## SqlClusterExecutor +`SqlClusterExecutor` is the most comprehensive Java SDK connection method. It not only provides the basic CRUD operations that you can use with JDBC but also offers additional features like request modes and more. -### Creating a SqlClusterExecutor +### Create a SqlClusterExecutor First, configure the OpenMLDB connection parameters. @@ -108,14 +114,13 @@ option.setZkPath("/openmldb"); option.setSessionTimeout(10000); option.setRequestTimeout(60000); ``` - Then, use SdkOption to create the Executor. ```java sqlExecutor = new SqlClusterExecutor(option); ``` -`SqlClusterExecutor` execution of SQL operations is thread-safe, and in actual environments, a single `SqlClusterExecutor` can be created. However, since the execution mode (execute_mode) is an internal variable of `SqlClusterExecutor`, if you want to execute an offline command and an online command at the same time, unexpected results may occur. In this case, please use multiple `SqlClusterExecutors`. +`SqlClusterExecutor` execution of SQL operations is thread-safe, and in actual environments, a single `SqlClusterExecutor` can be created. However, since the execution mode (`execute_mode`) is an internal variable of `SqlClusterExecutor`, if you want to execute an offline command and an online command at the same time, unexpected results may occur. In this case, please use multiple `SqlClusterExecutors`. ```{caution} The default execution mode for SqlClusterExecutor is offline, which is different from the default mode for JDBC. @@ -158,7 +163,7 @@ try { } ``` -#### Executing batch SQL queries with Statement +#### Execute Batch SQL Queries with Statement Use the `Statement::execute` interface to execute batch SQL queries: @@ -200,15 +205,15 @@ try { ### PreparedStatement -`SqlClusterExecutor` can also obtain `PreparedStatement`, but you need to specify which type of `PreparedStatement` to obtain. For example, when using InsertPreparedStmt for insertion operations, there are three ways to do it. +`SqlClusterExecutor` can also obtain `PreparedStatement`, but you need to specify which type of `PreparedStatement` to obtain. For example, when using `InsertPreparedStmt` for insertion operations, there are three ways to do it. ```{note} -Insert operation only supports online mode and is not affected by execution mode. The data will always be inserted into the online database. +Any `PreparedStatement` executes exclusively in the **online mode** and is not influenced by the state of the `SqlClusterExecutor` at the time of its creation. `PreparedStatement` does not support switching to the offline mode. If you need to execute SQL in the offline mode, you can use a `Statement`. ``` #### Common Insert -1. Use the `SqlClusterExecutor::getInsertPreparedStmt(db, insertSql)` method to get the InsertPrepareStatement. +1. Use the `SqlClusterExecutor::getInsertPreparedStmt(db, insertSql)` method to get the `InsertPrepareStatement`. 2. Use the `PreparedStatement::execute()` method to execute the insert statement. ```java @@ -232,14 +237,14 @@ try { } ``` -#### Insert With Placeholder +#### Insert with Placeholder -1. Get InsertPrepareStatement by calling `SqlClusterExecutor::getInsertPreparedStmt(db, insertSqlWithPlaceHolder)` interface. -2. Use `PreparedStatement::setType(index, value)` interface to fill in data to the InsertPrepareStatement. Note that the index starts from 1. +1. Get `InsertPrepareStatement` by calling `SqlClusterExecutor::getInsertPreparedStmt(db, insertSqlWithPlaceHolder)` interface. +2. Use `PreparedStatement::setType(index, value)` interface to fill in data to the `InsertPrepareStatement`. Note that the index starts from 1. 3. Use `PreparedStatement::execute()` interface to execute the insert statement. ```{note} -When the conditions of the PreparedStatement are the same, you can repeatedly call the set method of the same object to fill in data before executing execute(). There is no need to create a new PreparedStatement object. +When the conditions of the `PreparedStatement` are the same, you can repeatedly call the set method of the same object to fill in data before executing `execute`. There is no need to create a new `PreparedStatement` object. ``` ```java @@ -266,13 +271,13 @@ try { ``` ```{note} -After execute, the cached data will be cleared and it is not possible to retry execute. +After `execute`, the cached data will be cleared and it is not possible to rerun `execute`. ``` -#### Batch Insert With Placeholder +#### Batch Insert with Placeholder -1. To use batch insert, first obtain the InsertPrepareStatement using the `SqlClusterExecutor::getInsertPreparedStmt(db, insertSqlWithPlaceHolder)` interface. -2. Then use the `PreparedStatement::setType(index, value)` interface to fill data into the InsertPrepareStatement. +1. To use batch insert, first obtain the `InsertPrepareStatement` using the `SqlClusterExecutor::getInsertPreparedStmt(db, insertSqlWithPlaceHolder)` interface. +2. Then use the `PreparedStatement::setType(index, value)` interface to fill data into the `InsertPrepareStatement`. 3. Use the `PreparedStatement::addBatch()` interface to complete filling for one row. 4. Continue to use `setType(index, value)` and `addBatch()` to fill multiple rows. 5. Use the `PreparedStatement::executeBatch()` interface to complete the batch insertion. @@ -305,12 +310,12 @@ try { ``` ```{note} -After executeBatch(), all cached data will be cleared and it's not possible to retry executeBatch(). +After `executeBatch`, all cached data will be cleared and it's not possible to rerun `executeBatch`. ``` -### Execute SQL request query +### Execute SQL Query -`RequestPreparedStmt` is a unique query mode (not supported by JDBC). This mode requires both the selectSql and a request data, so you need to provide the SQL and set the request data using setType when calling `getRequestPreparedStmt`. +`RequestPreparedStmt` is a unique query mode (not supported by JDBC). This mode requires both the selectSql and a request data, so you need to provide the SQL and set the request data using `setType` when calling `getRequestPreparedStmt`. There are three steps to execute a SQL request query: @@ -359,7 +364,7 @@ try { Assert.assertEquals(resultSet.getInt(2), 24); Assert.assertEquals(resultSet.getLong(3), 34); - // The return result set of the ordinary request query contains only one row of results. Therefore, the result of the second call to resultSet. next() is false + // The return result set of the ordinary request query contains only one row of results. Therefore, the result of the second call to resultSet.next() is false Assert.assertFalse(resultSet.next()); } catch (SQLException e) { @@ -368,7 +373,7 @@ try { } finally { try { if (resultSet != null) { - // result用完之后需要close + // close result resultSet.close(); } if (pstmt != null) { @@ -379,16 +384,82 @@ try { } } ``` +### Execute Deployment +To execute a deployment, you can use the `SqlClusterExecutor::getCallablePreparedStmt(db, deploymentName)` interface to obtain a `CallablePreparedStatement`. In contrast to the SQL request-based queries mentioned earlier, deployments are already online on the server, which makes them faster compared to SQL request-based queries. + +The process of using a deployment consists of two steps: +- Online Deployment +```java +// Deploy online (use selectSql). In a real production environment, deployments are typically already online and operational. +java.sql.Statement state = sqlExecutor.getStatement(); +try { + String selectSql = String.format("SELECT c1, c3, sum(c4) OVER w1 as w1_c4_sum FROM %s WINDOW w1 AS " + + "(PARTITION BY %s.c1 ORDER BY %s.c7 ROWS_RANGE BETWEEN 2d PRECEDING AND CURRENT ROW);", table, + table, table); + // Deploy + String deploySql = String.format("DEPLOY %s OPTIONS(RANGE_BIAS='inf', ROWS_BIAS='inf') %s", deploymentName, selectSql); + // set return null rs, don't check the returned value, it's false + state.execute(deploySql); +} catch (Exception e) { + e.printStackTrace(); +} +``` +- Execute Deployment +When executing a deployment, recreating a `CallablePreparedStmt` can be time-consuming. It is recommended to reuse the `CallablePreparedStmt` whenever possible. The `executeQuery()` method will automatically clear the request row cache for `setXX` requests. + +```java +// Execute Deployment +PreparedStatement pstmt = null; +ResultSet resultSet = null; +try { + pstmt = sqlExecutor.getCallablePreparedStmt(db, deploymentName); + // Obtain preparedstatement with name + // pstmt = sqlExecutor.getCallablePreparedStmt(db, deploymentName); + ResultSetMetaData metaData = pstmt.getMetaData(); + // Execute request mode requires setting query data in RequestPreparedStatement + setData(pstmt, metaData); + // executeQuery will execute select sql, and put result in resultSet + resultSet = pstmt.executeQuery(); -### Delete all data of a key under the specified index + Assert.assertTrue(resultSet.next()); + Assert.assertEquals(resultSet.getMetaData().getColumnCount(), 3); + Assert.assertEquals(resultSet.getString(1), "bb"); + Assert.assertEquals(resultSet.getInt(2), 24); + Assert.assertEquals(resultSet.getLong(3), 34); + Assert.assertFalse(resultSet.next()); + + // reuse way + for (int i = 0; i < 5; i++) { + setData(pstmt, metaData); + pstmt.executeQuery(); + // skip result check + } +} catch (SQLException e) { + e.printStackTrace(); + Assert.fail(); +} finally { + try { + if (resultSet != null) { + // close result + resultSet.close(); + } + if (pstmt != null) { + pstmt.close(); + } + } catch (SQLException throwables) { + throwables.printStackTrace(); + } +} +``` + +### Delete All Data of a Key under the Specified Index There are two ways to delete data through the Java SDK: - Execute delete SQL directly - - Use delete PreparedStatement -Note that this can only delete data under one index, not all indexes. Refer to [DELETE function boundary](https://openmldb.ai/docs/zh/main/quickstart/function_boundary.html#delete) for details. +Note that this can only delete data under one index, not all indexes. Refer to [DELETE function boundary](../function_boundary.md#delete) for details. ```java java.sql.Statement state = router.getStatement(); @@ -412,7 +483,7 @@ try { } ``` -### A complete example of using SqlClusterExecutor +### A Complete Example of SqlClusterExecutor Refer to the [Java quickstart demo](https://github.com/4paradigm/OpenMLDB/tree/main/demo/java_quickstart/demo). If it is used on macOS, please use openmldb-native of macOS version and increase the dependency of openmldb-native. @@ -427,9 +498,9 @@ java -cp target/demo-1.0-SNAPSHOT.jar com.openmldb.demo.App You must fill in `zkCluster` and `zkPath` (set method or the configuration `foo=bar` after `?` in JDBC). -### Optional configuration +### Optional Configuration -| Optional configuration | Description | +| Optional Configuration | Description | | ---------------------- | ------------------------------------------------------------ | | enableDebug | The default is false. Enable the debug log of hybridse (note that it is not the global debug log). You can view more logs of sql compilation and operation. However, not all of these logs are collected by the client. You need to view the tablet server logs. | | requestTimeout | The default is 60000 ms. This timeout is the rpc timeout sent by the client, except for those sent to the taskmanager (the rpc timeout of the job is controlled by the variable `job_timeout`). | @@ -441,16 +512,18 @@ You must fill in `zkCluster` and `zkPath` (set method or the configuration `foo= | zkLogFile | The default is empty, which is printed to stdout. | | sparkConfPath | The default is empty. You can change the spark conf used by the job through this configuration without configuring the taskmanager to restart. | -## SQL verification +## SQL Validation -The Java client supports the correct verification of SQL to verify whether it is executable. It is divided into batch and request modes. +The Java client supports the verification of SQL to verify whether it is executable. It is divided into batch and request modes. -- `ValidateSQLInBatch` can verify whether SQL can be executed at the offline end. +- `ValidateSQLInBatch` can verify whether SQL can be executed offline. - `ValidateSQLInRequest` can verify whether SQL can be deployed online. -Both interfaces need to go through all table schemas required by SQL. Currently, only single db is supported. Please do not use `db.table` format in SQL statements. +Both interfaces require providing all the table schemas required by the SQL and support multiple databases. For backward compatibility, it's allowed not to specify the db (current database in use) in the parameters. In such cases, it's equivalent to using the first db listed in use schema. It's important to ensure that the `` format tables are from the first db, which doesn't affect SQL statements in the `.
    ` format. + +For example, verify SQL `select count (c1) over w1 from t3 window w1 as (partition by c1 order by c2 rows between unbounded preceding and current row);`, In addition to this statement, you need to go through in the schema of table `t3` as the second parameter schemaMaps. The format is Map, key is the name of the db, and value is all the table schemas (maps) of each db. In fact, only a single db is supported, so there is usually only one db here, as shown in db3 below. The table schema map key under db is table name, and the value is `com._ 4paradigm.openmldb.sdk.Schema`, consisting of the name and type of each column. -For example, verify SQL `select count (c1) over w1 from t3 window w1 as (partition by c1 order by c2 rows between unbounded preceding and current row);`, In addition to this statement, you need to go through in the schema of table `t3` as the second parameter schemaMaps. The format is Map, key is the name of the db, and value is all the table schemas (maps) of each db. In fact, only a single db is supported, so there is usually only one db here, as shown in db3 below. The table schema map key under db is table name, and the value is com._ 4paradigm.openmldb.sdk.Schema, consisting of the name and type of each column. +The return result is a `List`. If the validation is successful, it returns an empty list. If the validation fails, it returns a list of error messages, such as `[error_msg, error_trace]`. ```java Map> schemaMaps = new HashMap<>(); @@ -461,5 +534,66 @@ schemaMaps.put("db3", dbSchema); List ret = SqlClusterExecutor.validateSQLInRequest("select count(c1) over w1 from t3 window "+ "w1 as(partition by c1 order by c2 rows between unbounded preceding and current row);", schemaMaps); Assert.assertEquals(ret.size(), 0); + +Map> schemaMaps = new HashMap<>(); +Map dbSchema = new HashMap<>(); +dbSchema = new HashMap<>(); +dbSchema.put("t3", new Schema(Arrays.asList(new Column("c1", Types.VARCHAR), new Column("c2", Types.BIGINT)))); +schemaMaps.put("db3", dbSchema); +// Can use parameter format of no db. Make sure that there's only one db in schemaMaps，and only
    format is used in sql. +// List ret = SqlClusterExecutor.validateSQLInRequest("select count(c1) over w1 from t3 window "+ +// "w1 as(partition by c1 order by c2 rows between unbounded preceding and current row);", schemaMaps); +List ret = SqlClusterExecutor.validateSQLInRequest("select count(c1) over w1 from t3 window "+ + "w1 as(partition by c1 order by c2 rows between unbounded preceding and current row);", "db3", schemaMaps); +Assert.assertEquals(ret.size(), 0); ``` +## DDL Generation + +The `public static List genDDL(String sql, Map> tableSchema)` method can help users generate table creation statements based on the SQL they want to deploy. It currently supports only a **single** database. The `sql` parameter should not be in the `.
    ` format. The `tableSchema` parameter should include the schemas of all tables that the SQL depends on. The format of `tableSchema` should be consistent with what was discussed earlier. Even if `tableSchema` contains multiple databases, the database information will be discarded, and all tables will be treated as if they belong to an unknown database. + +## SQL Output Schema + +The `public static Schema genOutputSchema(String sql, String usedDB, Map> tableSchema)` method allows you to obtain the Output Schema for SQL queries and supports multiple databases. If you specify the `usedDB`, you can use tables from that database within the SQL using the `
    ` format. For backward compatibility, there is also support for the` public static Schema genOutputSchema(String sql, Map> tableSchema)` method without specifying a database (usedDB). In this case, it is equivalent to using the first database listed as the used db. Therefore, you should ensure that tables in `
    ` format within the `SQ`L query are associated with this first database. + + +## SQL Table Lineage +The `public static List> getDependentTables(String sql, String usedDB, Map> tableSchema)` method allows you to retrieve all tables that the sql query depends on. Each `Pair` in the list corresponds to the database name and table name, with the first element being the primary table, and the rest `[1, end)` representing other dependent tables (excluding the primary table). If the input parameter `usedDB` is an empty string, it means the query is performed without specifying a database (use db) context, which is different from the compatibility rules mentioned earlier for methods like `genDDL`. + +## SQL Merge +The Java client supports merging multiple SQL statements and performs correctness validation in request mode using the `mergeSQL` interface. However, it's important to note that merging is only possible when all the input SQL statements have the same primary table. + +Input parameters: SQL group to be merged; the name of the current database being used; the join key(s) for the primary table (which can be multiple); the schema for all tables involved. + +For example, let's consider four SQL feature views: +``` +// Single-table direct feature +select c1 from main; +// Single-table aggregation feature +select sum(c1) over w1 of2 from main window w1 as (partition by c1 order by c2 rows between unbounded preceding and current row); +// Multi-table feature +select t1.c2 of4 from main last join t1 order by t1.c2 on main.c1==t1.c1; +// Multi-table aggregation feature +select sum(c2) over w1 from main window w1 as (union (select \"\" as id, * from t1) partition by c1 order by c2 rows between unbounded preceding and current row); +``` + +Since all of them have the same primary table, "main," they can be merged. The merging process is essentially a join operation. To perform this operation, you also need to specify a unique column in the "main" table that can be used to identify a unique row of data. For example, if the "id" column in the "main" table is not unique and there may be multiple rows with the same "id" values, you can use a combination of "id" and "c1" columns for the join. Similar to SQL validation, you would also provide a schema map for the tables involved in the merge. + + +```java +//To simplify the demonstration, we are using tables from a single database, so you only need to specify used db and table names if your SQL statements all use the
    format. you can leave the used database parameter as an empty string. If your SQL statements use the .
    format, you can leave the used db parameter as an empty string +String merged = SqlClusterExecutor.mergeSQL(sqls, "db", Arrays.asList("id", "c1"), schemaMaps); +``` + +The output is a single merged SQL statement, as shown below. The input SQL includes a total of four features, so the merged SQL will only output these four feature columns. (The join keys are automatically filtered.) + +``` +select `c1`, `of2`, `of4`, `sum(c2)over w1` from (select main.id as merge_id_0, c1 from main) as out0 last join (select main.id as merge_id_1, sum(c1) over w1 of2 from main window w1 as (partition by c1 order by c2 rows between unbounded preceding and current row)) as out1 on out0.merge_id_0 = out1.merge_id_1 last join (select main.id as merge_id_2, t1.c2 of4 from main last join t1 order by t1.c2 on main.c1==t1.c1) as out2 on out0.merge_id_0 = out2.merge_id_2 last join (select main.id as merge_id_3, sum(c2) over w1 from main window w1 as (union (select "" as id, * from t1) partition by c1 order by c2 rows between unbounded preceding and current row)) as out3 on out0.merge_id_0 = out3.merge_id_3; +``` + +```{note} +If you encounter an "Ambiguous column name" error during the merging process, it may be due to having the same column names in different feature groups. To resolve this, you should use aliases in your input SQL to distinguish between them. +``` + + + diff --git a/docs/en/quickstart/sdk/python_sdk.md b/docs/en/quickstart/sdk/python_sdk.md index 421f6b8ff93..6ae0e4705af 100644 --- a/docs/en/quickstart/sdk/python_sdk.md +++ b/docs/en/quickstart/sdk/python_sdk.md @@ -1,18 +1,20 @@ # Python SDK -## Python SDK package installation +The default execution mode is Online. -Execute the following command to install the Python SDK package: +## Python SDK Installation + +Execute the following command to install Python SDK: ```bash pip install openmldb ``` -## OpenMLDB DBAPI usage +## OpenMLDB DBAPI -This section demonstrates the basic use of the OpenMLDB DB API. +This section demonstrates the basic use of the OpenMLDB DB API. For all DBAPI interfaces, if an execution fails, it will raise a `DatabaseError` exception. Users can catch this exception and handle it as needed. The return value is a `Cursor`. For DDL SQL, you do not need to handle the return value. For other SQL statements, you can refer to the specific examples below for how to handle the return value. -### Create connection +### Create Connection Parameter `db_name` name must exist, and the database must be created before the connection is created. To continue, create a connection without a database and then use the database db through the `execute ("USE")` command. @@ -24,11 +26,11 @@ cursor = db.cursor() #### Configuration Details -Zk and zkPath configuration are required. +Zk and zkPath configurations are required. -The Python SDK can be used through OpenMLDB DBAPI/SQLAlchemy. The optional configurations are basically the same as those of the Java client. Please refer to the [Java SDK configuration](https://openmldb.ai/docs/zh/main/quickstart/sdk/java_sdk.html#sdk) for details. +The Python SDK can be used through OpenMLDB DBAPI/SQLAlchemy. The optional configurations are basically the same as those of the Java client. Please refer to the [Java SDK configuration](./java_sdk.md#sdk-configuration-details) for details. -### Create database +### Create Database Create database `db1`: @@ -37,7 +39,7 @@ cursor.execute("CREATE DATABASE db1") cursor.execute("USE db1") ``` -### Create table +### Create Table Create table `t1`: @@ -45,7 +47,7 @@ Create table `t1`: cursor.execute("CREATE TABLE t1 (col1 bigint, col2 date, col3 string, col4 string, col5 int, index(key=col3, ts=col1))") ``` -### Insert data into the table +### Insert Data into Table Insert one sentence of data into the table: @@ -53,7 +55,7 @@ Insert one sentence of data into the table: cursor.execute("INSERT INTO t1 VALUES(1000, '2020-12-25', 'guangdon', 'shenzhen', 1)") ``` -### Execute SQL query +### Execute SQL Query ```python result = cursor.execute("SELECT * FROM t1") @@ -62,15 +64,30 @@ print(result.fetchmany(10)) print(result.fetchall()) ``` -### SQL batch request query +### SQL Batch Query ```python -#In the Batch Request mode, the input parameters of the interface are“SQL”, “Common_Columns”, “Request_Columns” +#In the Batch Request mode, the input parameters of the interface are "SQL", "Common_Columns", "Request_Columns" result = cursor.batch_row_request("SELECT * FROM t1", ["col1","col2"], ({"col1": 2000, "col2": '2020-12-22', "col3": 'fujian', "col4":'xiamen', "col5": 2})) print(result.fetchone()) ``` +### Execute Deployment + +Please note that the execution of deployments is only supported by DBAPI, and there is no equivalent interface in OpenMLDB SQLAlchemy. Additionally, deployment execution supports single requests only and does not support batch requests. + +```python +cursor.execute("DEPLOY d1 SELECT col1 FROM t1") +# dict style +result = cursor.callproc("d1", {"col1": 1000, "col2": None, "col3": None, "col4": None, "col5": None}) +print(result.fetchall()) +# tuple style +result = cursor.callproc("d1", (1001, "2023-07-20", "abc", "def", 1)) +print(result.fetchall()) +# drop deployment before drop table +cursor.execute("DROP DEPLOYMENT d1") +``` -### Delete table +### Delete Table Delete table `t1`: @@ -78,7 +95,7 @@ Delete table `t1`: cursor.execute("DROP TABLE t1") ``` -### Delete database +### Delete Database Delete database `db1`: @@ -86,17 +103,17 @@ Delete database `db1`: cursor.execute("DROP DATABASE db1") ``` -### Close connection +### Close Connection ```python cursor.close() ``` -## OpenMLDB SQLAlchemy usage +## OpenMLDB SQLAlchemy -This section demonstrates using the Python SDK through OpenMLDB SQLAlchemy. +This section demonstrates the use of the Python SDK through OpenMLDB SQLAlchemy. Similarly, if any of the DBAPI interfaces fail, they will raise a `DatabaseError` exception. Users can catch and handle this exception as needed. The handling of return values should follow the SQLAlchemy standard. -### Create connection +### Create Connection ```python create_engine('openmldb:///db_name?zk=zkcluster&zkPath=zkpath') @@ -110,7 +127,7 @@ engine = db.create_engine('openmldb:///?zk=127.0.0.1:2181&zkPath=/openmldb') connection = engine.connect() ``` -### Create database +### Create Database Use the `connection.execute()` interface to create database `db1`: @@ -123,7 +140,7 @@ except Exception as e: connection.execute("USE db1") ``` -### Create table +### Create Table Use the `connection.execute()` interface to create table `t1`: @@ -134,7 +151,7 @@ except Exception as e: print(e) ``` -### Insert data into the table +### Insert Data into Table Use the `connection.execute (ddl)` interface to execute the SQL insert statement, and you can insert data into the table: @@ -156,7 +173,7 @@ except Exception as e: print(e) ``` -### Execute SQL batch query +### Execute SQL Batch Query Use the `connection.execute (sql)` interface to execute SQL batch query statements: @@ -171,7 +188,7 @@ except Exception as e: print(e) ``` -### Execute SQL request query +### Execute SQL Query Use the `connection.execute (sql, request)` interface to execute the SQL request query. You can put the input data into the second parameter of the execute function: @@ -182,7 +199,7 @@ except Exception as e: print(e) ``` -### Delete table +### Delete Table Use the `connection.execute (ddl)` interface to delete table `t1`: @@ -193,7 +210,7 @@ except Exception as e: print(e) ``` -### Delete database +### Delete Database Use the connection.execute（ddl）interface to delete database `db1`: @@ -204,7 +221,7 @@ except Exception as e: print(e) ``` -## Notebook Magic Function usage +## Notebook Magic Function The OpenMLDB Python SDK supports the expansion of Notebook magic function. Use the following statement to register the function. @@ -216,26 +233,24 @@ openmldb.sql_magic.register(db) Then you can use line magic function `%sql` and block magic function `%%sql` in Notebook. -![img](https://openmldb.ai/docs/zh/main/_images/openmldb_magic_function.png) - -## The complete usage example +![img](../images/openmldb_magic_function.png) -Refer to the [Python quickstart demo](https://github.com/4paradigm/OpenMLDB/tree/main/demo/python_quickstart/demo.py), including the above DBAPI and SQLAlchemy usage. +## A Complete Example -## common problem +Refer to the [Python quickstart demo](https://github.com/4paradigm/OpenMLDB/tree/main/demo/python_quickstart/demo.py), which includes the above DBAPI and SQLAlchemy usage. -- **What do I do when error** `ImportError：dlopen (.. _sql_router_sdk. so, 2): initializer function 0xnnnn not in mapped image for` **appears when using SQLAlchemy?** +## Q&A -In addition to import openmldb, you may also import other third-party libraries, which may cause confusion in the loading order. Due to the complexity of the system, you can try to use the virtual env environment (such as conda) to avoid interference. In addition, import openmldb before importing sqlalchemy, and ensure that the two imports are in the first place. +- **What do I do when error `ImportError：dlopen (.. _sql_router_sdk. so, 2): initializer function 0xnnnn not in mapped image for` appears when using SQLAlchemy?** -If the error still occur, it is recommended to connect to OpenMLDB by using request http to connect to apiserver. +In addition to importing OpenMLDB, you may also have imported other third-party libraries, which may cause confusion in the loading order. Due to the complexity of the system, you can try to use the virtual env environment (such as conda) to avoid interference. In addition, import OpenMLDB before importing SQLAlchemy, and ensure that the two imports are in the first place. -occur +If the error still occurs, it is recommended to connect to OpenMLDB by request http to connect to apiserver. -- **What do I do if Python SDK encountered the following problems?** +- **What do I do if Python SDK encounters the following problems?** ```plain [libprotobuf FATAL /Users/runner/work/crossbow/crossbow/vcpkg/buildtrees/protobuf/src/23fa7edd52-3ba2225d30.clean/src/google/protobuf/stubs/common.cc:87] This program was compiled against version 3.6.1 of the Protocol Buffer runtime library, which is not compatible with the installed version (3.15.8). Contact the program author for an update. ... ``` -This problem may be due to the introduction of other versions of protobuf in other libraries. You can try to use the virtual env environment (such as conda). +This problem may be due to the import of other versions of protobuf from other libraries. You can try to use the virtual env environment (such as conda). diff --git a/docs/en/quickstart/sdk/rest_api.md b/docs/en/quickstart/sdk/rest_api.md index 7d8f3c4a881..c2a6cc972ea 100644 --- a/docs/en/quickstart/sdk/rest_api.md +++ b/docs/en/quickstart/sdk/rest_api.md @@ -1,12 +1,12 @@ # REST API -## Important information +## Important -REST APIs interact with the services of APIServer and OpenMLDB, so the APIServer module must be properly deployed to be used effectively. APIServer is an optional module during installation and deployment. Refer to the APIServer deployment document. +REST APIs interact with the services of APIServer and OpenMLDB, so the APIServer module must be properly deployed to be used effectively. APIServer is an optional module during installation and deployment. Refer to [APIServer Deployment](../../deploy/install_deploy.md). At this stage, APIServer is mainly used for functional testing, not recommended for performance testing, nor recommended for the production environment. The default deployment of APIServer does not have a high availability mechanism at present and introduces additional network and codec overhead. -## Data insertion +## Data Insertion Request address: http://ip:port/dbs/{db_name}/tables/{table_name} @@ -23,7 +23,6 @@ The requestor: ``` - Currently, it only supports inserting one piece of data. - - The data should be arranged in strict accordance with the schema. Sample request data: @@ -44,7 +43,7 @@ Response: } ``` -## Real-time feature computing +## Real-Time Feature Computing Request address: http://ip:port/dbs/{db_name}/deployments/{deployment_name} @@ -81,11 +80,11 @@ Requestor - Input data in JSON format can have redundant columns. -**Sample request data** +**Sample Request Data** Example 1: Array format -```plain +```Plain curl http://127.0.0.1:8080/dbs/demo_db/deployments/demo_data_service -X POST -d'{ "input": [["aaa", 11, 22, 1.2, 1.3, 1635247427000, "2021-05-20"]] }' @@ -106,9 +105,7 @@ Response: Example 2: JSON format ```JSON -curl http://127.0.0.1:8080/dbs/demo_db/deployments/demo_data_service -X POST -d'{ - "input": [{"c1":"aaa", "c2":11, "c3":22, "c4":1.2, "c5":1.3, "c6":1635247427000, "c7":"2021-05-20", "foo":"bar"}] - }' +curl http://127.0.0.1:8080/dbs/demo_db/deployments/demo_data_service -X POST -d'{"input": [{"c1":"aaa", "c2":11, "c3":22, "c4":1.2, "c5":1.3, "c6":1635247427000, "c7":"2021-05-20", "foo":"bar"}]}' ``` Response: @@ -125,7 +122,7 @@ Response: ## Query -Request address: http://ip:port/dbs/ {db_name} +Request address: http://ip:port/dbs/{db_name} Request method: POST @@ -146,13 +143,13 @@ Request parameters: | Parameters | Type | Requirement | Description | | ---------- | ------ | ----------- | ------------------------------------------------------------ | -| mode | String | Yes | Available for `offsync` , `offasync`, `online` | +| mode | String | Yes | Set to `offsync` , `offasync`, `online` | | sql | String | Yes | | | input | Object | No | | | schema | Array | No | Support data types (case insensitive): `Bool`, `Int16`, `Int32`, `Int64`, `Float`, `Double`, `String`, `Date and Timestamp` | | data | Array | No | | -**Sample request data** +**Sample Request Data** Example 1: General query @@ -202,7 +199,7 @@ Response: } ``` -## Query deployment information +## Query Deployment Information Request address: http://ip:port/dbs/{db_name}/deployments/{deployment_name} @@ -239,7 +236,7 @@ Response: } ``` -## Acquire all library names +## Acquire All Library Names Request address: http://ip:port/dbs @@ -257,7 +254,7 @@ Response: } ``` -## Acquire all table names +## Acquire All Table Names Request address: http://ip:port/dbs/{db}/tables @@ -310,7 +307,7 @@ Response: } ``` -## Refresh APIServer metadata cache +## Refresh APIServer Metadata Cache Request address: http://ip:port/refresh From 671897e2112b23adc29c668e3d36fc7a84e43fdc Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Thu, 26 Oct 2023 16:36:27 +0800 Subject: [PATCH 25/32] refactor(codegen): null safe for struct ir builder (#3547) fixes #926 --- cases/query/const_query.yaml | 48 ++++++++++- hybridse/src/codegen/array_ir_builder.cc | 16 ++++ hybridse/src/codegen/array_ir_builder.h | 4 +- hybridse/src/codegen/cast_expr_ir_builder.cc | 86 ++++++++------------ hybridse/src/codegen/cast_expr_ir_builder.h | 24 ++---- hybridse/src/codegen/date_ir_builder.cc | 8 -- hybridse/src/codegen/date_ir_builder.h | 10 +-- hybridse/src/codegen/expr_ir_builder.cc | 5 +- hybridse/src/codegen/ir_base_builder.cc | 15 ++-- hybridse/src/codegen/native_value.h | 4 +- hybridse/src/codegen/string_ir_builder.cc | 12 +-- hybridse/src/codegen/string_ir_builder.h | 20 ++--- hybridse/src/codegen/struct_ir_builder.cc | 25 ++++-- hybridse/src/codegen/struct_ir_builder.h | 22 +++-- hybridse/src/codegen/timestamp_ir_builder.cc | 8 +- hybridse/src/codegen/type_ir_builder.cc | 45 ++++++++-- hybridse/src/codegen/type_ir_builder.h | 6 ++ hybridse/src/udf/default_udf_library.cc | 12 +-- 18 files changed, 197 insertions(+), 173 deletions(-) diff --git a/cases/query/const_query.yaml b/cases/query/const_query.yaml index 5efe6fa3c29..a3ea130d885 100644 --- a/cases/query/const_query.yaml +++ b/cases/query/const_query.yaml @@ -126,15 +126,55 @@ cases: columns: ['c1 bool', 'c2 int16', 'c3 int', 'c4 double', 'c5 string', 'c6 date', 'c7 timestamp' ] rows: - [ true, 3, 13, 10.0, 'a string', '2020-05-22', 1590115420000 ] + + # ================================================================================= + # Null safe for structure types: String, Date, Timestamp and Array + # creating struct from: + # 1. NULL liternal (const null) + # 2. another supported date type but fails to cast, e.g. timestamp(-1) returns NULL of timestamp + # + # casting to array type un-implemented + # ================================================================================= - id: 10 + desc: null safe for date mode: procedure-unsupport sql: | select datediff(Date(timestamp(-1)), Date("2021-05-01")) as out1, datediff(Date(timestamp(-2177481600)), Date("2021-05-01")) as out2, - datediff(cast(NULL as date), Date("2021-05-01")) as out3 - ; + datediff(cast(NULL as date), Date("2021-05-01")) as out3, + date(NULL) as out4, + date("abc") as out5, + date(timestamp("abc")) as out6 + expect: + columns: ["out1 int", "out2 int", "out3 int", "out4 date", "out5 date", "out6 date"] + data: | + NULL, NULL, NULL, NULL, NULL, NULL + - id: 11 + desc: null safe for timestamp + mode: procedure-unsupport + sql: | + select + month(cast(NULL as timestamp)) as out1, + month(timestamp(NULL)) as out2, + month(timestamp(-1)) as out3, + month(timestamp("abc")) as out4, + month(timestamp(date("abc"))) as out5 + expect: + columns: ["out1 int", "out2 int", "out3 int", "out4 int", "out5 int"] + data: | + NULL, NULL, NULL, NULL, NULL + - id: 12 + desc: null safe for string + mode: procedure-unsupport + sql: | + select + char_length(cast(NULL as string)) as out1, + char_length(string(int(NULL))) as out2, + char_length(string(bool(null))) as out3, + char_length(string(timestamp(null))) as out4, + char_length(string(date(null))) as out5 expect: - columns: ["out1 int", "out2 int", "out3 int"] + columns: ["out1 int", "out2 int", "out3 int", "out4 int", "out5 int"] data: | - NULL, NULL, NULL + NULL, NULL, NULL, NULL, NULL diff --git a/hybridse/src/codegen/array_ir_builder.cc b/hybridse/src/codegen/array_ir_builder.cc index 0788c1ba8aa..5bf1bf06e99 100644 --- a/hybridse/src/codegen/array_ir_builder.cc +++ b/hybridse/src/codegen/array_ir_builder.cc @@ -114,5 +114,21 @@ base::Status ArrayIRBuilder::NewEmptyArray(llvm::BasicBlock* bb, NativeValue* ou return base::Status::OK(); } +bool ArrayIRBuilder::CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) { + llvm::Value* array_alloca = nullptr; + if (!Create(block, &array_alloca)) { + return false; + } + + llvm::IRBuilder<> builder(block); + ::llvm::Value* array_sz = builder.getInt64(0); + if (!Set(block, array_alloca, 2, array_sz)) { + return false; + } + + *output = array_alloca; + return true; +} + } // namespace codegen } // namespace hybridse diff --git a/hybridse/src/codegen/array_ir_builder.h b/hybridse/src/codegen/array_ir_builder.h index 38eb6eda1ad..66ef2fe05da 100644 --- a/hybridse/src/codegen/array_ir_builder.h +++ b/hybridse/src/codegen/array_ir_builder.h @@ -49,12 +49,12 @@ class ArrayIRBuilder : public StructTypeIRBuilder { void InitStructType() override; - bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) override { return true; } + bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) override; bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist) override { return true; } base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, NativeValue* output) override { - return base::Status::OK(); + CHECK_TRUE(false, common::kCodegenError, "casting to array un-implemented"); }; private: diff --git a/hybridse/src/codegen/cast_expr_ir_builder.cc b/hybridse/src/codegen/cast_expr_ir_builder.cc index bdb6329c6c8..57e4103cba6 100644 --- a/hybridse/src/codegen/cast_expr_ir_builder.cc +++ b/hybridse/src/codegen/cast_expr_ir_builder.cc @@ -15,12 +15,15 @@ */ #include "codegen/cast_expr_ir_builder.h" + #include "codegen/date_ir_builder.h" #include "codegen/ir_base_builder.h" #include "codegen/string_ir_builder.h" #include "codegen/timestamp_ir_builder.h" +#include "codegen/type_ir_builder.h" #include "glog/logging.h" #include "node/node_manager.h" +#include "proto/fe_common.pb.h" using hybridse::common::kCodegenError; @@ -72,98 +75,73 @@ Status CastExprIRBuilder::Cast(const NativeValue& value, } return Status::OK(); } -Status CastExprIRBuilder::SafeCast(const NativeValue& value, ::llvm::Type* type, - NativeValue* output) { + +Status CastExprIRBuilder::SafeCast(const NativeValue& value, ::llvm::Type* dst_type, NativeValue* output) { ::llvm::IRBuilder<> builder(block_); - CHECK_TRUE(IsSafeCast(value.GetType(), type), kCodegenError, - "Safe cast fail: unsafe cast"); + CHECK_TRUE(IsSafeCast(value.GetType(), dst_type), kCodegenError, "Safe cast fail: unsafe cast"); Status status; if (value.IsConstNull()) { - if (TypeIRBuilder::IsStringPtr(type)) { - StringIRBuilder string_ir_builder(block_->getModule()); - CHECK_STATUS(string_ir_builder.CreateNull(block_, output)); - return base::Status::OK(); - } else { - *output = NativeValue::CreateNull(type); - } - } else if (TypeIRBuilder::IsTimestampPtr(type)) { + auto res = CreateSafeNull(block_, dst_type); + CHECK_TRUE(res.ok(), kCodegenError, res.status().ToString()); + *output = res.value(); + } else if (TypeIRBuilder::IsTimestampPtr(dst_type)) { TimestampIRBuilder timestamp_ir_builder(block_->getModule()); CHECK_STATUS(timestamp_ir_builder.CastFrom(block_, value, output)); return Status::OK(); - } else if (TypeIRBuilder::IsDatePtr(type)) { + } else if (TypeIRBuilder::IsDatePtr(dst_type)) { DateIRBuilder date_ir_builder(block_->getModule()); CHECK_STATUS(date_ir_builder.CastFrom(block_, value, output)); return Status::OK(); - } else if (TypeIRBuilder::IsStringPtr(type)) { + } else if (TypeIRBuilder::IsStringPtr(dst_type)) { StringIRBuilder string_ir_builder(block_->getModule()); CHECK_STATUS(string_ir_builder.CastFrom(block_, value, output)); return Status::OK(); - } else if (TypeIRBuilder::IsNumber(type)) { + } else if (TypeIRBuilder::IsNumber(dst_type)) { Status status; ::llvm::Value* output_value = nullptr; - CHECK_TRUE(SafeCastNumber(value.GetValue(&builder), type, &output_value, - status), - kCodegenError); + CHECK_TRUE(SafeCastNumber(value.GetValue(&builder), dst_type, &output_value, status), kCodegenError); if (value.IsNullable()) { - *output = NativeValue::CreateWithFlag(output_value, - value.GetIsNull(&builder)); + *output = NativeValue::CreateWithFlag(output_value, value.GetIsNull(&builder)); } else { *output = NativeValue::Create(output_value); } } else { - return Status(common::kCodegenError, - "Can't cast from " + - TypeIRBuilder::TypeName(value.GetType()) + " to " + - TypeIRBuilder::TypeName(type)); + return Status(common::kCodegenError, "Can't cast from " + TypeIRBuilder::TypeName(value.GetType()) + " to " + + TypeIRBuilder::TypeName(dst_type)); } return Status::OK(); } -Status CastExprIRBuilder::UnSafeCast(const NativeValue& value, - ::llvm::Type* type, NativeValue* output) { - ::llvm::IRBuilder<> builder(block_); - if (value.IsConstNull()) { - if (TypeIRBuilder::IsStringPtr(type)) { - StringIRBuilder string_ir_builder(block_->getModule()); - CHECK_STATUS(string_ir_builder.CreateNull(block_, output)); - return base::Status::OK(); - } else if (TypeIRBuilder::IsDatePtr(type)) { - DateIRBuilder date_ir(block_->getModule()); - CHECK_STATUS(date_ir.CreateNull(block_, output)); - return base::Status::OK(); - } else { - *output = NativeValue::CreateNull(type); - } - } else if (TypeIRBuilder::IsTimestampPtr(type)) { +Status CastExprIRBuilder::UnSafeCast(const NativeValue& value, ::llvm::Type* dst_type, NativeValue* output) { + ::llvm::IRBuilder<> builder(block_); + if (value.IsConstNull() || (TypeIRBuilder::IsNumber(dst_type) && TypeIRBuilder::IsDatePtr(value.GetType()))) { + // input is const null or (cast date to number) + auto res = CreateSafeNull(block_, dst_type); + CHECK_TRUE(res.ok(), kCodegenError, res.status().ToString()); + *output = res.value(); + } else if (TypeIRBuilder::IsTimestampPtr(dst_type)) { TimestampIRBuilder timestamp_ir_builder(block_->getModule()); CHECK_STATUS(timestamp_ir_builder.CastFrom(block_, value, output)); return Status::OK(); - } else if (TypeIRBuilder::IsDatePtr(type)) { + } else if (TypeIRBuilder::IsDatePtr(dst_type)) { DateIRBuilder date_ir_builder(block_->getModule()); CHECK_STATUS(date_ir_builder.CastFrom(block_, value, output)); return Status::OK(); - } else if (TypeIRBuilder::IsStringPtr(type)) { + } else if (TypeIRBuilder::IsStringPtr(dst_type)) { StringIRBuilder string_ir_builder(block_->getModule()); CHECK_STATUS(string_ir_builder.CastFrom(block_, value, output)); return Status::OK(); - } else if (TypeIRBuilder::IsNumber(type) && - TypeIRBuilder::IsStringPtr(value.GetType())) { + } else if (TypeIRBuilder::IsNumber(dst_type) && TypeIRBuilder::IsStringPtr(value.GetType())) { StringIRBuilder string_ir_builder(block_->getModule()); - CHECK_STATUS( - string_ir_builder.CastToNumber(block_, value, type, output)); + CHECK_STATUS(string_ir_builder.CastToNumber(block_, value, dst_type, output)); return Status::OK(); - } else if (TypeIRBuilder::IsNumber(type) && - TypeIRBuilder::IsDatePtr(value.GetType())) { - *output = NativeValue::CreateNull(type); } else { Status status; ::llvm::Value* output_value = nullptr; - CHECK_TRUE(UnSafeCastNumber(value.GetValue(&builder), type, - &output_value, status), - kCodegenError, status.msg); + CHECK_TRUE(UnSafeCastNumber(value.GetValue(&builder), dst_type, &output_value, status), kCodegenError, + status.msg); if (value.IsNullable()) { - *output = NativeValue::CreateWithFlag(output_value, - value.GetIsNull(&builder)); + *output = NativeValue::CreateWithFlag(output_value, value.GetIsNull(&builder)); } else { *output = NativeValue::Create(output_value); } diff --git a/hybridse/src/codegen/cast_expr_ir_builder.h b/hybridse/src/codegen/cast_expr_ir_builder.h index bb487ed1466..5adfca2bdcf 100644 --- a/hybridse/src/codegen/cast_expr_ir_builder.h +++ b/hybridse/src/codegen/cast_expr_ir_builder.h @@ -18,9 +18,6 @@ #define HYBRIDSE_SRC_CODEGEN_CAST_EXPR_IR_BUILDER_H_ #include "base/fe_status.h" #include "codegen/cond_select_ir_builder.h" -#include "codegen/scope_var.h" -#include "llvm/IR/IRBuilder.h" -#include "proto/fe_type.pb.h" namespace hybridse { namespace codegen { @@ -32,26 +29,19 @@ class CastExprIRBuilder { explicit CastExprIRBuilder(::llvm::BasicBlock* block); ~CastExprIRBuilder(); - Status Cast(const NativeValue& value, ::llvm::Type* cast_type, - NativeValue* output); // NOLINT - Status SafeCast(const NativeValue& value, ::llvm::Type* type, - NativeValue* output); // NOLINT - Status UnSafeCast(const NativeValue& value, ::llvm::Type* type, - NativeValue* output); // NOLINT + Status Cast(const NativeValue& value, ::llvm::Type* cast_type, NativeValue* output); + Status SafeCast(const NativeValue& value, ::llvm::Type* dst_type, NativeValue* output); + Status UnSafeCast(const NativeValue& value, ::llvm::Type* dst_type, NativeValue* output); static bool IsSafeCast(::llvm::Type* lhs, ::llvm::Type* rhs); - static Status InferNumberCastTypes(::llvm::Type* left_type, - ::llvm::Type* right_type); + static Status InferNumberCastTypes(::llvm::Type* left_type, ::llvm::Type* right_type); static bool IsIntFloat2PointerCast(::llvm::Type* src, ::llvm::Type* dist); bool BoolCast(llvm::Value* pValue, llvm::Value** pValue1, base::Status& status); // NOLINT - bool SafeCastNumber(::llvm::Value* value, ::llvm::Type* type, - ::llvm::Value** output, + bool SafeCastNumber(::llvm::Value* value, ::llvm::Type* type, ::llvm::Value** output, base::Status& status); // NOLINT - bool UnSafeCastNumber(::llvm::Value* value, ::llvm::Type* type, - ::llvm::Value** output, + bool UnSafeCastNumber(::llvm::Value* value, ::llvm::Type* type, ::llvm::Value** output, base::Status& status); // NOLINT - bool UnSafeCastDouble(::llvm::Value* value, ::llvm::Type* type, - ::llvm::Value** output, + bool UnSafeCastDouble(::llvm::Value* value, ::llvm::Type* type, ::llvm::Value** output, base::Status& status); // NOLINT private: diff --git a/hybridse/src/codegen/date_ir_builder.cc b/hybridse/src/codegen/date_ir_builder.cc index 3a60147bd9a..19bf319d7c3 100644 --- a/hybridse/src/codegen/date_ir_builder.cc +++ b/hybridse/src/codegen/date_ir_builder.cc @@ -45,14 +45,6 @@ void DateIRBuilder::InitStructType() { return; } -base::Status DateIRBuilder::CreateNull(::llvm::BasicBlock* block, NativeValue* output) { - ::llvm::Value* value = nullptr; - CHECK_TRUE(CreateDefault(block, &value), common::kCodegenError, "Fail to construct string") - ::llvm::IRBuilder<> builder(block); - *output = NativeValue::CreateWithFlag(value, builder.getInt1(true)); - return base::Status::OK(); -} - bool DateIRBuilder::CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) { return NewDate(block, output); diff --git a/hybridse/src/codegen/date_ir_builder.h b/hybridse/src/codegen/date_ir_builder.h index b44b039d57d..d9004d48da1 100644 --- a/hybridse/src/codegen/date_ir_builder.h +++ b/hybridse/src/codegen/date_ir_builder.h @@ -27,16 +27,14 @@ class DateIRBuilder : public StructTypeIRBuilder { public: explicit DateIRBuilder(::llvm::Module* m); ~DateIRBuilder(); - void InitStructType() override; - base::Status CreateNull(::llvm::BasicBlock* block, NativeValue* output); + void InitStructType() override; bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) override; + bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist) override; + base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, NativeValue* output) override; bool NewDate(::llvm::BasicBlock* block, ::llvm::Value** output); - bool NewDate(::llvm::BasicBlock* block, ::llvm::Value* date, - ::llvm::Value** output); - bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist); - base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, NativeValue* output); + bool NewDate(::llvm::BasicBlock* block, ::llvm::Value* date, ::llvm::Value** output); bool GetDate(::llvm::BasicBlock* block, ::llvm::Value* date, ::llvm::Value** output); diff --git a/hybridse/src/codegen/expr_ir_builder.cc b/hybridse/src/codegen/expr_ir_builder.cc index 1bccb6deef3..6b95bfb8ce1 100644 --- a/hybridse/src/codegen/expr_ir_builder.cc +++ b/hybridse/src/codegen/expr_ir_builder.cc @@ -26,10 +26,8 @@ #include "codegen/cond_select_ir_builder.h" #include "codegen/context.h" #include "codegen/date_ir_builder.h" -#include "codegen/fn_ir_builder.h" #include "codegen/ir_base_builder.h" #include "codegen/list_ir_builder.h" -#include "codegen/struct_ir_builder.h" #include "codegen/timestamp_ir_builder.h" #include "codegen/type_ir_builder.h" #include "codegen/udf_ir_builder.h" @@ -217,8 +215,7 @@ Status ExprIRBuilder::BuildConstExpr( ::llvm::IRBuilder<> builder(ctx_->GetCurrentBlock()); switch (const_node->GetDataType()) { case ::hybridse::node::kNull: { - *output = NativeValue::CreateNull( - llvm::Type::getTokenTy(builder.getContext())); + *output = NativeValue(nullptr, nullptr, llvm::Type::getTokenTy(builder.getContext())); break; } case ::hybridse::node::kBool: { diff --git a/hybridse/src/codegen/ir_base_builder.cc b/hybridse/src/codegen/ir_base_builder.cc index d1c7e153dd6..992d41d0998 100644 --- a/hybridse/src/codegen/ir_base_builder.cc +++ b/hybridse/src/codegen/ir_base_builder.cc @@ -17,7 +17,6 @@ #include "codegen/ir_base_builder.h" #include -#include #include #include @@ -625,21 +624,25 @@ bool GetBaseType(::llvm::Type* type, ::hybridse::node::DataType* output) { return false; } - if (pointee_ty->getStructName().startswith("fe.list_ref_")) { + auto struct_name = pointee_ty->getStructName(); + if (struct_name.startswith("fe.list_ref_")) { *output = hybridse::node::kList; return true; - } else if (pointee_ty->getStructName().startswith("fe.iterator_ref_")) { + } else if (struct_name.startswith("fe.iterator_ref_")) { *output = hybridse::node::kIterator; return true; - } else if (pointee_ty->getStructName().equals("fe.string_ref")) { + } else if (struct_name.equals("fe.string_ref")) { *output = hybridse::node::kVarchar; return true; - } else if (pointee_ty->getStructName().equals("fe.timestamp")) { + } else if (struct_name.equals("fe.timestamp")) { *output = hybridse::node::kTimestamp; return true; - } else if (pointee_ty->getStructName().equals("fe.date")) { + } else if (struct_name.equals("fe.date")) { *output = hybridse::node::kDate; return true; + } else if (struct_name.startswith("fe.array_")) { + *output = hybridse::node::kArray; + return true; } LOG(WARNING) << "no mapping pointee_ty for llvm pointee_ty " << pointee_ty->getStructName().str(); diff --git a/hybridse/src/codegen/native_value.h b/hybridse/src/codegen/native_value.h index 52b0453c743..4bb756e3c3b 100644 --- a/hybridse/src/codegen/native_value.h +++ b/hybridse/src/codegen/native_value.h @@ -21,9 +21,7 @@ #include #include -#include "glog/logging.h" #include "llvm/IR/IRBuilder.h" -#include "llvm/IR/Module.h" namespace hybridse { namespace codegen { @@ -93,9 +91,9 @@ class NativeValue { NativeValue WithFlag(::llvm::Value*) const; NativeValue() : raw_(nullptr), flag_(nullptr), type_(nullptr) {} + NativeValue(::llvm::Value* raw, ::llvm::Value* flag, ::llvm::Type* type); private: - NativeValue(::llvm::Value* raw, ::llvm::Value* flag, ::llvm::Type* type); ::llvm::Value* raw_; ::llvm::Value* flag_; ::llvm::Type* type_; diff --git a/hybridse/src/codegen/string_ir_builder.cc b/hybridse/src/codegen/string_ir_builder.cc index bb69f529f2b..8c41d326ee0 100644 --- a/hybridse/src/codegen/string_ir_builder.cc +++ b/hybridse/src/codegen/string_ir_builder.cc @@ -63,17 +63,7 @@ bool StringIRBuilder::CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) { return NewString(block, output); } -/// Create Const String Null -/// \param block -/// \param output -/// \return -base::Status StringIRBuilder::CreateNull(::llvm::BasicBlock* block, NativeValue* output) { - ::llvm::Value* value = nullptr; - CHECK_TRUE(NewString(block, &value), kCodegenError, "Fail to construct string") - ::llvm::IRBuilder<> builder(block); - *output = NativeValue::CreateWithFlag(value, builder.getInt1(true)); - return base::Status::OK(); -} + bool StringIRBuilder::NewString(::llvm::BasicBlock* block, ::llvm::Value** output) { if (!Create(block, output)) { diff --git a/hybridse/src/codegen/string_ir_builder.h b/hybridse/src/codegen/string_ir_builder.h index fb81872599a..84f73d2822d 100644 --- a/hybridse/src/codegen/string_ir_builder.h +++ b/hybridse/src/codegen/string_ir_builder.h @@ -16,14 +16,12 @@ #ifndef HYBRIDSE_SRC_CODEGEN_STRING_IR_BUILDER_H_ #define HYBRIDSE_SRC_CODEGEN_STRING_IR_BUILDER_H_ + #include #include + #include "base/fe_status.h" -#include "codegen/cast_expr_ir_builder.h" -#include "codegen/scope_var.h" #include "codegen/struct_ir_builder.h" -#include "llvm/IR/IRBuilder.h" -#include "proto/fe_type.pb.h" namespace hybridse { namespace codegen { @@ -32,16 +30,18 @@ class StringIRBuilder : public StructTypeIRBuilder { public: explicit StringIRBuilder(::llvm::Module* m); ~StringIRBuilder(); + void InitStructType() override; - bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output); - base::Status CreateNull(::llvm::BasicBlock* block, NativeValue* output); + bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) override; + bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist) override; + base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, NativeValue* output) override; + base::Status CastFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value** output); + bool NewString(::llvm::BasicBlock* block, ::llvm::Value** output); bool NewString(::llvm::BasicBlock* block, const std::string& str, ::llvm::Value** output); bool NewString(::llvm::BasicBlock* block, ::llvm::Value* size, ::llvm::Value* data, ::llvm::Value** output); - bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, - ::llvm::Value* dist); bool GetSize(::llvm::BasicBlock* block, ::llvm::Value* str, ::llvm::Value** output); bool SetSize(::llvm::BasicBlock* block, ::llvm::Value* str, @@ -50,8 +50,6 @@ class StringIRBuilder : public StructTypeIRBuilder { ::llvm::Value** output); bool SetData(::llvm::BasicBlock* block, ::llvm::Value* str, ::llvm::Value* data); - base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, - NativeValue* output); base::Status Compare(::llvm::BasicBlock* block, const NativeValue& s1, const NativeValue& s2, NativeValue* output); @@ -62,8 +60,6 @@ class StringIRBuilder : public StructTypeIRBuilder { const std::vector& strs, NativeValue* output); - base::Status CastFrom(::llvm::BasicBlock* block, ::llvm::Value* src, - ::llvm::Value** output); base::Status CastToNumber(::llvm::BasicBlock* block, const NativeValue& src, ::llvm::Type* type, NativeValue* output); }; diff --git a/hybridse/src/codegen/struct_ir_builder.cc b/hybridse/src/codegen/struct_ir_builder.cc index 3a8e3336936..7adfb5d950f 100644 --- a/hybridse/src/codegen/struct_ir_builder.cc +++ b/hybridse/src/codegen/struct_ir_builder.cc @@ -25,17 +25,14 @@ StructTypeIRBuilder::StructTypeIRBuilder(::llvm::Module* m) : TypeIRBuilder(), m_(m), struct_type_(nullptr) {} StructTypeIRBuilder::~StructTypeIRBuilder() {} -bool StructTypeIRBuilder::StructCopyFrom(::llvm::BasicBlock* block, - ::llvm::Value* src, - ::llvm::Value* dist) { - StructTypeIRBuilder* struct_builder = - CreateStructTypeIRBuilder(block->getModule(), src->getType()); +bool StructTypeIRBuilder::StructCopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist) { + StructTypeIRBuilder* struct_builder = CreateStructTypeIRBuilder(block->getModule(), src->getType()); bool ok = struct_builder->CopyFrom(block, src, dist); delete struct_builder; return ok; } -StructTypeIRBuilder* StructTypeIRBuilder::CreateStructTypeIRBuilder( - ::llvm::Module* m, ::llvm::Type* type) { + +StructTypeIRBuilder* StructTypeIRBuilder::CreateStructTypeIRBuilder(::llvm::Module* m, ::llvm::Type* type) { node::DataType base_type; if (!GetBaseType(type, &base_type)) { return nullptr; @@ -49,14 +46,24 @@ StructTypeIRBuilder* StructTypeIRBuilder::CreateStructTypeIRBuilder( case node::kVarchar: return new StringIRBuilder(m); default: { - LOG(WARNING) << "fail to create struct type ir builder for " - << DataTypeName(base_type); + LOG(WARNING) << "fail to create struct type ir builder for " << DataTypeName(base_type); return nullptr; } } return nullptr; } + +absl::StatusOr StructTypeIRBuilder::CreateNull(::llvm::BasicBlock* block) { + ::llvm::Value* value = nullptr; + if (!CreateDefault(block, &value)) { + return absl::InternalError(absl::StrCat("fail to construct ", GetLlvmObjectString(GetType()))); + } + ::llvm::IRBuilder<> builder(block); + return NativeValue::CreateWithFlag(value, builder.getInt1(true)); +} + ::llvm::Type* StructTypeIRBuilder::GetType() { return struct_type_; } + bool StructTypeIRBuilder::Create(::llvm::BasicBlock* block, ::llvm::Value** output) const { if (block == NULL || output == NULL) { diff --git a/hybridse/src/codegen/struct_ir_builder.h b/hybridse/src/codegen/struct_ir_builder.h index e306dfe869e..e197665855b 100644 --- a/hybridse/src/codegen/struct_ir_builder.h +++ b/hybridse/src/codegen/struct_ir_builder.h @@ -17,6 +17,7 @@ #ifndef HYBRIDSE_SRC_CODEGEN_STRUCT_IR_BUILDER_H_ #define HYBRIDSE_SRC_CODEGEN_STRUCT_IR_BUILDER_H_ +#include "absl/status/statusor.h" #include "base/fe_status.h" #include "codegen/native_value.h" #include "codegen/type_ir_builder.h" @@ -28,15 +29,18 @@ class StructTypeIRBuilder : public TypeIRBuilder { public: explicit StructTypeIRBuilder(::llvm::Module*); ~StructTypeIRBuilder(); - static StructTypeIRBuilder* CreateStructTypeIRBuilder(::llvm::Module*, - ::llvm::Type*); - static bool StructCopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, - ::llvm::Value* dist); + + static StructTypeIRBuilder* CreateStructTypeIRBuilder(::llvm::Module*, ::llvm::Type*); + static bool StructCopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist); + virtual void InitStructType() = 0; + virtual bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist) = 0; + virtual base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, NativeValue* output) = 0; + virtual bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) = 0; + + absl::StatusOr CreateNull(::llvm::BasicBlock* block); ::llvm::Type* GetType(); bool Create(::llvm::BasicBlock* block, ::llvm::Value** output) const; - virtual bool CreateDefault(::llvm::BasicBlock* block, - ::llvm::Value** output) = 0; // Load the 'idx' th field into ''*output' // NOTE: not all types are loaded correctly, e.g for array type @@ -46,12 +50,6 @@ class StructTypeIRBuilder : public TypeIRBuilder { // Get the address of 'idx' th field bool Get(::llvm::BasicBlock* block, ::llvm::Value* struct_value, unsigned int idx, ::llvm::Value** output) const; - virtual bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, - ::llvm::Value* dist) = 0; - virtual base::Status CastFrom(::llvm::BasicBlock* block, - const NativeValue& src, - NativeValue* output) = 0; - protected: ::llvm::Module* m_; ::llvm::Type* struct_type_; diff --git a/hybridse/src/codegen/timestamp_ir_builder.cc b/hybridse/src/codegen/timestamp_ir_builder.cc index f14952f455c..c3a8054e1cd 100644 --- a/hybridse/src/codegen/timestamp_ir_builder.cc +++ b/hybridse/src/codegen/timestamp_ir_builder.cc @@ -44,9 +44,7 @@ void TimestampIRBuilder::InitStructType() { return; } stype = ::llvm::StructType::create(m_->getContext(), name); - ::llvm::Type* ts_ty = (::llvm::Type::getInt64Ty(m_->getContext())); - std::vector<::llvm::Type*> elements; - elements.push_back(ts_ty); + std::vector<::llvm::Type*> elements = {::llvm::Type::getInt64Ty(m_->getContext())}; stype->setBody(::llvm::ArrayRef<::llvm::Type*>(elements)); struct_type_ = stype; return; @@ -61,10 +59,6 @@ base::Status TimestampIRBuilder::CastFrom(::llvm::BasicBlock* block, return Status::OK(); } - if (src.IsConstNull()) { - *output = NativeValue::CreateNull(GetType()); - return Status::OK(); - } ::llvm::IRBuilder<> builder(block); NativeValue ts; CastExprIRBuilder cast_builder(block); diff --git a/hybridse/src/codegen/type_ir_builder.cc b/hybridse/src/codegen/type_ir_builder.cc index bbdf1346995..07adfb21855 100644 --- a/hybridse/src/codegen/type_ir_builder.cc +++ b/hybridse/src/codegen/type_ir_builder.cc @@ -16,8 +16,11 @@ #include "codegen/type_ir_builder.h" +#include "absl/status/status.h" +#include "codegen/date_ir_builder.h" #include "codegen/ir_base_builder.h" -#include "glog/logging.h" +#include "codegen/string_ir_builder.h" +#include "codegen/timestamp_ir_builder.h" #include "node/node_manager.h" namespace hybridse { @@ -102,13 +105,7 @@ bool TypeIRBuilder::IsStringPtr(::llvm::Type* type) { bool TypeIRBuilder::IsStructPtr(::llvm::Type* type) { if (type->getTypeID() == ::llvm::Type::PointerTyID) { type = reinterpret_cast<::llvm::PointerType*>(type)->getElementType(); - if (type->isStructTy()) { - DLOG(INFO) << "Struct Name " << type->getStructName().str(); - return true; - } else { - DLOG(INFO) << "Isn't Struct Type"; - return false; - } + return type->isStructTy(); } return false; } @@ -139,5 +136,37 @@ base::Status TypeIRBuilder::BinaryOpTypeInfer( return base::Status::OK(); } +absl::StatusOr CreateSafeNull(::llvm::BasicBlock* block, ::llvm::Type* type) { + node::DataType data_type; + if (!GetBaseType(type, &data_type)) { + return absl::InvalidArgumentError(absl::StrCat("can't get base type for: ", GetLlvmObjectString(type))); + } + + if (TypeIRBuilder::IsStructPtr(type)) { + std::unique_ptr builder = nullptr; + + switch (data_type) { + case node::DataType::kTimestamp: { + builder.reset(new TimestampIRBuilder(block->getModule())); + break; + } + case node::DataType::kDate: { + builder.reset(new DateIRBuilder(block->getModule())); + break; + } + case node::DataType::kVarchar: { + builder.reset(new StringIRBuilder(block->getModule())); + break; + } + default: + return absl::InvalidArgumentError(absl::StrCat("invalid struct type: ", GetLlvmObjectString(type))); + } + + return builder->CreateNull(block); + } + + return NativeValue(nullptr, nullptr, type); +} + } // namespace codegen } // namespace hybridse diff --git a/hybridse/src/codegen/type_ir_builder.h b/hybridse/src/codegen/type_ir_builder.h index ad7d5f225b9..e68d7f0233b 100644 --- a/hybridse/src/codegen/type_ir_builder.h +++ b/hybridse/src/codegen/type_ir_builder.h @@ -19,7 +19,9 @@ #include +#include "absl/status/statusor.h" #include "base/fe_status.h" +#include "codegen/native_value.h" #include "llvm/IR/Module.h" #include "llvm/IR/Type.h" #include "node/sql_node.h" @@ -90,6 +92,10 @@ class BoolIRBuilder : public TypeIRBuilder { } }; +// construct a safe null value for type +// returns NativeValue{raw, is_null=true} on success, raw is ensured to be not nullptr +absl::StatusOr CreateSafeNull(::llvm::BasicBlock* block, ::llvm::Type* type); + } // namespace codegen } // namespace hybridse #endif // HYBRIDSE_SRC_CODEGEN_TYPE_IR_BUILDER_H_ diff --git a/hybridse/src/udf/default_udf_library.cc b/hybridse/src/udf/default_udf_library.cc index fef776d3ffd..e6a546095ec 100644 --- a/hybridse/src/udf/default_udf_library.cc +++ b/hybridse/src/udf/default_udf_library.cc @@ -2190,11 +2190,7 @@ void DefaultUdfLibrary::InitTypeUdf() { .args(v1::string_to_date); RegisterExternal("timestamp") - .args(reinterpret_cast( - static_cast( - v1::date_to_timestamp))) - .return_by_arg(true) - .returns>() + .args(v1::date_to_timestamp) .doc(R"( @brief Cast int64, date or string expression to timestamp @@ -2217,11 +2213,7 @@ void DefaultUdfLibrary::InitTypeUdf() { @endcode @since 0.1.0)"); RegisterExternal("timestamp") - .args(reinterpret_cast( - static_cast( - v1::string_to_timestamp))) - .return_by_arg(true) - .returns>(); + .args(v1::string_to_timestamp); } void DefaultUdfLibrary::InitTimeAndDateUdf() { From 5c6b40c6c0d02cbc2164ceec34d2e91f8a896fba Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Fri, 27 Oct 2023 11:16:53 +0800 Subject: [PATCH 26/32] build: upgrade thirdparty to 0.6.0 (#3557) * build: upgrade thirdparty to 0.6.0 * fix: dockerfile * fix(single_tablet_test): pure virtual method call called --- Makefile | 44 +++++++++++++++++++------------ docker/Dockerfile | 6 ++--- src/nameserver/name_server_impl.h | 7 ++++- src/sdk/mini_cluster.h | 10 ++++--- third-party/CMakeLists.txt | 8 +++--- 5 files changed, 45 insertions(+), 30 deletions(-) diff --git a/Makefile b/Makefile index 697b12923af..bf6c95054dd 100644 --- a/Makefile +++ b/Makefile @@ -139,29 +139,39 @@ THIRD_PARTY_BUILD_DIR ?= $(MAKEFILE_DIR)/.deps THIRD_PARTY_SRC_DIR ?= $(MAKEFILE_DIR)/thirdsrc THIRD_PARTY_DIR ?= $(THIRD_PARTY_BUILD_DIR)/usr -# trick: for those compile inside hybridsql docker image, thirdparty is pre-installed in /deps/usr. -# we check this by asserting if the environment variable '$THIRD_PARTY_DIR' is defined to '/deps/usr', -# if true, thirdparty download is skipped -# zetasql check separately since it update more frequently: -# it will updated if the variable '$ZETASQL_VERSION' (defined in docker) not equal to that defined in current code -override GREP_PATTERN = "set(ZETASQL_VERSION" +override ZETASQL_PATTERN = "set(ZETASQL_VERSION" +override THIRD_PATTERN = "set(HYBRIDSQL_ASSERTS_VERSION" +new_zetasql_version := $(shell grep $(ZETASQL_PATTERN) third-party/cmake/FetchZetasql.cmake | sed 's/[^0-9.]*\([0-9.]*\).*/\1/') +new_third_version := $(shell grep $(THIRD_PATTERN) third-party/CMakeLists.txt | sed 's/[^0-9.]*\([0-9.]*\).*/\1/') + thirdparty-fast: @if [ $(THIRD_PARTY_DIR) != "/deps/usr" ] ; then \ echo "[deps]: install thirdparty and zetasql"; \ $(MAKE) thirdparty; \ - elif [ -n "$(ZETASQL_VERSION)" ]; then \ - new_zetasql_version=$(shell grep $(GREP_PATTERN) third-party/cmake/FetchZetasql.cmake | sed 's/[^0-9.]*\([0-9.]*\).*/\1/'); \ - if [ "$$new_zetasql_version" != "$(ZETASQL_VERSION)" ] ; then \ - echo "[deps]: thirdparty up-to-date. reinstall zetasql from $(ZETASQL_VERSION) to $$new_zetasql_version"; \ - $(MAKE) thirdparty-configure; \ - $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target zetasql; \ - else \ - echo "[deps]: all up-to-date. zetasql already installed with version: $(ZETASQL_VERSION)"; \ - fi; \ else \ - echo "[deps]: install zetasql only"; \ $(MAKE) thirdparty-configure; \ - $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target zetasql; \ + if [ -n "$(ZETASQL_VERSION)" ] ; then \ + if [ "$(new_zetasql_version)" != "$(ZETASQL_VERSION)" ] ; then \ + echo "[deps]: installing zetasql from $(ZETASQL_VERSION) to $(new_zetasql_version)"; \ + $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target zetasql; \ + else \ + echo "[deps]: zetasql up-to-date with version: $(ZETASQL_VERSION)"; \ + fi; \ + else \ + echo "[deps]: installing latest zetasql"; \ + $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target zetasql; \ + fi; \ + if [ -n "$(THIRDPARTY_VERSION)" ]; then \ + if [ "$(new_third_version)" != "$(THIRDPARTY_VERSION)" ] ; then \ + echo "[deps]: installing thirdparty from $(THIRDPARTY_VERSION) to $(new_third_version)"; \ + $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target hybridsql-asserts; \ + else \ + echo "[deps]: thirdparty up-to-date: $(THIRDPARTY_VERSION)"; \ + fi ; \ + else \ + echo "[deps]: installing latest thirdparty"; \ + $(CMAKE_PRG) --build $(THIRD_PARTY_BUILD_DIR) --target hybridsql-asserts; \ + fi ; \ fi # third party compiled code install to 'OpenMLDB/.deps/usr', source code install to 'OpenMLDB/thirdsrc' diff --git a/docker/Dockerfile b/docker/Dockerfile index d478a84d87f..9faef4db550 100644 --- a/docker/Dockerfile +++ b/docker/Dockerfile @@ -15,8 +15,8 @@ FROM centos:7 -ARG ZETASQL_VERSION=0.3.0 -ARG THIRDPARTY_VERSION=0.5.2 +ARG ZETASQL_VERSION=0.3.1 +ARG THIRDPARTY_VERSION=0.6.0 ARG TARGETARCH LABEL org.opencontainers.image.source https://github.com/4paradigm/OpenMLDB @@ -28,8 +28,6 @@ RUN yum update -y && yum install -y centos-release-scl epel-release && \ curl -Lo lcov-1.15-1.noarch.rpm https://github.com/linux-test-project/lcov/releases/download/v1.15/lcov-1.15-1.noarch.rpm && \ yum localinstall -y lcov-1.15-1.noarch.rpm && \ yum clean all && rm -v lcov-1.15-1.noarch.rpm && \ - curl -Lo apache-maven-3.6.3-bin.tar.gz https://mirrors.ocf.berkeley.edu/apache/maven/maven-3/3.6.3/binaries/apache-maven-3.6.3-bin.tar.gz && \ - tar xzf apache-maven-3.6.3-bin.tar.gz -C /usr/local --strip-components=1 && \ curl -Lo zookeeper.tar.gz https://archive.apache.org/dist/zookeeper/zookeeper-3.4.14/zookeeper-3.4.14.tar.gz && \ mkdir -p /deps/src && \ tar xzf zookeeper.tar.gz -C /deps/src && \ diff --git a/src/nameserver/name_server_impl.h b/src/nameserver/name_server_impl.h index 4bfe84ad5f4..b9755c4aa1c 100644 --- a/src/nameserver/name_server_impl.h +++ b/src/nameserver/name_server_impl.h @@ -111,7 +111,12 @@ class NameServerImpl : public NameServer { NameServerImpl(); ~NameServerImpl() override; - + void CloseThreadpool() { + running_.store(false, std::memory_order_release); + thread_pool_.Stop(true); + task_thread_pool_.Stop(true); + UpdateTableStatus(); + } bool Init(const std::string& real_endpoint); bool Init(const std::string& zk_cluster, const std::string& zk_path, const std::string& endpoint, const std::string& real_endpoint); diff --git a/src/sdk/mini_cluster.h b/src/sdk/mini_cluster.h index 321df05b761..439a311f243 100644 --- a/src/sdk/mini_cluster.h +++ b/src/sdk/mini_cluster.h @@ -105,7 +105,7 @@ class MiniCluster { } } sleep(4); - ::openmldb::nameserver::NameServerImpl* nameserver = new ::openmldb::nameserver::NameServerImpl(); + nameserver = new ::openmldb::nameserver::NameServerImpl(); bool ok = nameserver->Init(zk_cluster_, zk_path_, ns_endpoint, ""); if (!ok) { return false; @@ -135,6 +135,7 @@ class MiniCluster { } void Close() { + nameserver->CloseThreadpool(); ns_.Stop(10); ns_.Join(); @@ -207,7 +208,7 @@ class MiniCluster { tb_clients_.emplace(tb_endpoint, client); return true; } - + ::openmldb::nameserver::NameServerImpl* nameserver; int32_t zk_port_; brpc::Server ns_; int32_t tablet_num_; @@ -250,7 +251,7 @@ class StandaloneEnv { FLAGS_sync_deploy_stats_timeout = 2000; ns_port_ = GenRand(); std::string ns_endpoint = "127.0.0.1:" + std::to_string(ns_port_); - ::openmldb::nameserver::NameServerImpl* nameserver = new ::openmldb::nameserver::NameServerImpl(); + nameserver = new ::openmldb::nameserver::NameServerImpl(); bool ok = nameserver->Init("", "", ns_endpoint, ""); if (!ok) { return false; @@ -278,6 +279,7 @@ class StandaloneEnv { } void Close() { + nameserver->CloseThreadpool(); ns_.Stop(10); ns_.Join(); tb_server_.Stop(10); @@ -323,7 +325,7 @@ class StandaloneEnv { tb_client_ = client; return true; } - + ::openmldb::nameserver::NameServerImpl* nameserver; brpc::Server ns_; brpc::Server tb_server_; std::string ns_endpoint_; diff --git a/third-party/CMakeLists.txt b/third-party/CMakeLists.txt index 88fc0a877dc..6a7f8cb0e07 100644 --- a/third-party/CMakeLists.txt +++ b/third-party/CMakeLists.txt @@ -68,7 +68,7 @@ set(MAKEOPTS "$ENV{MAKEOPTS}" CACHE STRING "Extra options to make") message(STATUS "Install bundled dependencies into ${DEPS_INSTALL_DIR}") set(HYBRIDSQL_ASSERTS_HOME https://github.com/4paradigm/hybridsql-asserts) -set(HYBRIDSQL_ASSERTS_VERSION 0.5.2) +set(HYBRIDSQL_ASSERTS_VERSION 0.6.0) function(get_linux_lsb_release_information) execute_process(COMMAND bash ${CMAKE_SOURCE_DIR}/get-lsb-release.sh @@ -90,17 +90,17 @@ function(init_hybridsql_thirdparty_urls) else() if (LSB_RELEASE_ID_SHORT STREQUAL "centos") set(HYBRIDSQL_ASSERTS_URL "${HYBRIDSQL_ASSERTS_HOME}/releases/download/v${HYBRIDSQL_ASSERTS_VERSION}/thirdparty-${HYBRIDSQL_ASSERTS_VERSION}-linux-gnu-x86_64-centos.tar.gz" PARENT_SCOPE) - set(HYBRIDSQL_ASSERTS_HASH 919ee7aee4c89846f4e242530519b3c34a34567ddcf9f4361d413a44e2f7408c PARENT_SCOPE) + set(HYBRIDSQL_ASSERTS_HASH c415dfdc95a127cdce888aec84c7fa3c02f3c9cb973805dcf23b54517e422e36 PARENT_SCOPE) elseif(LSB_RELEASE_ID_SHORT STREQUAL "ubuntu") set(HYBRIDSQL_ASSERTS_URL "${HYBRIDSQL_ASSERTS_HOME}/releases/download/v${HYBRIDSQL_ASSERTS_VERSION}/thirdparty-${HYBRIDSQL_ASSERTS_VERSION}-linux-gnu-x86_64-ubuntu.tar.gz" PARENT_SCOPE) - set(HYBRIDSQL_ASSERTS_HASH 8bb1f7685bf778539e1f4ba499020504ebc89e8cefa9a294aa0122578ca70716 PARENT_SCOPE) + set(HYBRIDSQL_ASSERTS_HASH 8c95b5fd539c8362d934ae58879d9ae1c27bc0977ca09cc8316ba207e8aaaf1e PARENT_SCOPE) else() message(FATAL_ERROR "no pre-compiled thirdparty for your operation system, try compile thirdparty from source with '-DBUILD_BUNDLED=ON'") endif() endif() elseif(CMAKE_SYSTEM_NAME STREQUAL "Darwin") set(HYBRIDSQL_ASSERTS_URL "${HYBRIDSQL_ASSERTS_HOME}/releases/download/v${HYBRIDSQL_ASSERTS_VERSION}/thirdparty-${HYBRIDSQL_ASSERTS_VERSION}-darwin-i386.tar.gz" PARENT_SCOPE) - set(HYBRIDSQL_ASSERTS_HASH 663b0d945c95034b1e17411f3e795f98053bf248860a60025c7802634ce526d8 PARENT_SCOPE) + set(HYBRIDSQL_ASSERTS_HASH 062e606f1d76fe27003bdc23e643305bfa032eadec8c075e7ce6dc22d70f5044 PARENT_SCOPE) endif() endfunction() From 4f49313490ed99e6a0124fd8798fa0ba9457ef8b Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Tue, 31 Oct 2023 16:48:40 +0800 Subject: [PATCH 27/32] docs: update-quickstart-concepts-folder (#3536) * Docs: Update-quickstart-concepts-folder * Docs: update-quickstart-concepts-index-file * Delete docs/en/quickstart/concepts/images/desktop.ini * Update modes.md * Delete modes-request.png * Update modes.md * Docs: Update-quickstart-concept-modesflow-image * Docs: Update-quickstart-concept-modesflow-image --------- Co-authored-by: Siqi Wang --- 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zo~=cx@7G&#IUjpTEZHm9e*$yku-EiwTZb_3;hO;D|L?0{ar=x3^m}yLx~hu_tIR+9 N@ksFDnuF)l{tqT=w+R3M diff --git a/docs/en/quickstart/concepts/index.rst b/docs/en/quickstart/concepts/index.rst index d02cca2378f..27542f7f2f7 100644 --- a/docs/en/quickstart/concepts/index.rst +++ b/docs/en/quickstart/concepts/index.rst @@ -5,4 +5,4 @@ Concept .. toctree:: :maxdepth: 1 - workflow + modes diff --git a/docs/en/quickstart/concepts/workflow.md b/docs/en/quickstart/concepts/modes.md similarity index 79% rename from docs/en/quickstart/concepts/workflow.md rename to docs/en/quickstart/concepts/modes.md index 2ce5c58ff19..d27f33ab001 100644 --- a/docs/en/quickstart/concepts/workflow.md +++ b/docs/en/quickstart/concepts/modes.md @@ -6,7 +6,7 @@ OpenMLDB supports different execution modes at different stages of the feature e The following diagram illustrates the typical process of using OpenMLDB for feature engineering development and deployment, as well as the execution modes used in the process: -![image-20220310170024349](https://openmldb.ai/docs/zh/main/_images/modes-flow.png) +![image-20220310170024349](images/modes-flow.png) 1. Offline Data Import: Import offline data for offline feature engineering development and debugging. 2. Offline Feature Development: Develop feature engineering scripts and debug them until satisfactory results are achieved. This step involves joint debugging of machine learning models (such as XGBoost, LightGBM, etc.), but this article mainly focuses on feature engineering development related to OpenMLDB. @@ -16,57 +16,54 @@ The following diagram illustrates the typical process of using OpenMLDB for feat 6. Online Data Preview (optional): Preview and check online data using supported SQL commands. This step is not mandatory. 7. Real-time Feature Calculation: After the feature scheme is deployed and the data is correctly accessed, a real-time feature calculation service that can respond to online requests will be obtained. -## Overview of execution mode +## Overview of Execution Mode -As the data objects for offline and online scenarios are different, their underlying storage and computing nodes are also different. Therefore, OpenMLDB provides several built-in execution modes to support completing the above steps. The following table summarizes the execution modes and development tools used for each step, and three execution modes will be discussed in detail later. +As the data objects for offline and online scenarios are different, their underlying storage and computing nodes are also different. Therefore, OpenMLDB provides several built-in execution modes to support the above steps. The following table summarizes the execution modes and development tools used for each step, and three execution modes will be discussed in detail later. | Steps | Execution Mode | Development Tool | | ------------------------------ | ------------------- | ------------------------------------------------------------ | | 1. Offline Data Import | Offline Mode | OpenMLDB CLI, SDKs | -| Offline Feature Development | Offline Mode | OpenMLDB CLI, SDKs | -| Feature Deployment | Offline Mode | OpenMLDB CLI, SDKs | -| Cold Start Online Data Import | Online Preview Mode | OpenMLDB CLI, SDKs, [Data Import Tool](https://openmldb.ai/docs/zh/main/tutorial/data_import.html) | -| Real-time Data Integration | Online Preview Mode | Connectors, SDKs | -| Online Data Preview (optional) | Online Preview Mode | OpenMLDB CLI, SDKs, [Data Export Tool](https://openmldb.ai/docs/zh/main/tutorial/data_export.html) | -| Real-time Feature Calculation | Online Request Mode | CLI (REST APIs), SDKs | +| 2. Offline Feature Development | Offline Mode | OpenMLDB CLI, SDKs | +| 3. Feature Deployment | Offline Mode | OpenMLDB CLI, SDKs | +| 4. Cold Start Online Data Import | Online Preview Mode | OpenMLDB CLI, SDKs, [Data Import Tool](../../tutorial/data_import.md) | +| 5. Real-time Data Integration | Online Preview Mode | Connectors, SDKs | +| 6. Online Data Preview (optional) | Online Preview Mode | OpenMLDB CLI, SDKs, [Data Export Tool](../../tutorial/data_export.md) | +| 7. Real-time Feature Calculation | Online Request Mode | CLI (REST APIs), SDKs | ### Offline Mode -After starting OpenMLDB CLI, the **default mode is offline mode**. Offline data import, offline feature development, and feature deployment are all executed in offline mode. The purpose of offline mode is to manage and compute offline data. The computing nodes involved are supported by OpenMLDB Spark optimized for feature engineering, and the storage nodes support commonly used storage systems such as HDFS. +After starting OpenMLDB CLI, the **default mode is offline mode**. Offline data import, offline feature development, and feature deployment are all executed in offline mode. The purpose of offline mode is to manage and compute offline data. The computing nodes involved are supported by [OpenMLDB Spark Distribution](../../tutorial/openmldbspark_distribution.md) optimized for feature engineering, and the storage nodes support commonly used storage systems such as HDFS. Offline mode has the following main features: -- The offline mode supports most of the SQL syntax provided by OpenMLDB, including complex SQL syntaxes such as `LAST JOIN` and `WINDOW UNION`, which are optimized for feature engineering. - -- In offline mode, some SQL commands are executed asynchronously, such as `LOAD DATA`, `SELECT`, and `SELECT INTO` commands. Other SQL commands are executed synchronously. - +- The offline mode supports most of the SQL syntax provided by OpenMLDB, including complex SQL syntax such as `LAST JOIN` and `WINDOW UNION`. +- In offline mode, some SQL commands are executed asynchronously, such as `LOAD DATA`, `SELECT`, and `SELECT INTO`. Other SQL commands are executed synchronously. - The asynchronous SQL is managed by the internal TaskManager and can be viewed and managed through commands such as `SHOW JOBS`, `SHOW JOB`, and `STOP JOB`. -```{tip} -::: +:::{tip} Unlike many relational database systems, the `SELECT` command in offline mode is executed asynchronously by default. If you need to set it to synchronous execution, refer to setting the command to run synchronously in offline mode. During offline feature development, if asynchronous execution is used, it is strongly recommended to use the `SELECT INTO` statement for development and debugging, which can export the results to a file for easy viewing. ::: -``` -The `DEPLOY` command for feature deployment is also executed in offline mode. Its specification can refer to the OpenMLDB SQL online specification and requirements. + +The `DEPLOY` command for feature deployment is also executed in offline mode. Its specification can refer to the [OpenMLDB SQL online specification and requirements](../../openmldb_sql/deployment_manage/ONLINE_REQUEST_REQUIREMENTS.md). Offline mode setting command (OpenMLDB CLI): `SET @@execute_mode='offline'`. -### Online preview mode +### Online Preview Mode Cold start online data import, real-time data access, and online data preview are executed in online preview mode. The purpose of the online preview mode is to manage and preview online data. Storage and computation of online data are supported by the tablet component. The main features of the online preview mode are: - `LOAD DATA`, used for online data import, can be done either locally (load_mode='local') or on the cluster (load_mode='cluster'). Local import is synchronous, while cluster import is asynchronous (same as in offline mode). Other operations are synchronous. -- Online preview mode is mainly used for previewing limited data. Selecting and viewing data directly through SELECT in OpenMLDB CLI or SDKs may result in data truncation. If the data volume is large, it is recommended to use an [export tool](https://openmldb.ai/docs/zh/main/tutorial/data_export.html) to view the complete data. -- SELECT statements in online preview mode currently do not support more complex queries such as `LAST JOIN` and `ORDER BY`. Refer to [SELECT](https://openmldb.ai/docs/zh/main/openmldb_sql/dql/SELECT_STATEMENT.html). +- Online preview mode is mainly used for previewing limited data. Selecting and viewing data directly through SELECT in OpenMLDB CLI or SDKs may result in data truncation. If the data volume is large, it is recommended to use an [export tool](../../tutorial/data_export.html) to view the complete data. +- SELECT statements in online preview mode currently do not support more complex queries such as `LAST JOIN` and `ORDER BY`. Refer to [SELECT](../../openmldb_sql/dql/SELECT_STATEMENT.html). - The server in the online preview mode executes SQL statements on a single thread. For large data processing, it may be slow and may trigger a timeout. To increase the timeout period, the `--request_timeout` can be configured on the client. -- To prevent impact on online services, online preview mode limits the maximum number of accessed records and the number of different keys. This can be configured using `--max_traverse_cnt` and `--max_traverse_key_cnt`. Similarly, the maximum result size can be set using `--scan_max_bytes_size`. For detailed configuration, refer to the configuration file. +- To prevent impact on online services, online preview mode limits the maximum number of accessed records and the number of different keys. This can be configured using `--max_traverse_cnt` and `--max_traverse_key_cnt`. Similarly, the maximum result size can be set using `--scan_max_bytes_size`. For detailed configuration, refer to the [configuration file](../../deploy/conf.md). The command for setting online preview mode in OpenMLDB CLI: `SET @@execute_mode='online'` -### Online request mode +### Online Request Mode After deploying feature scripts and accessing online data, the real-time feature computing service is ready to use, and real-time feature extraction can be performed through the online request mode. REST APIs and SDKs support the online request mode. The online request mode is a unique mode in OpenMLDB that supports real-time online computing and is very different from common SQL queries in databases. @@ -78,7 +75,7 @@ The online request mode requires three inputs: Based on the above inputs, for each real-time request row, the online request mode will return a feature extraction result. The computing logic is as follows: The request row is virtually inserted into the correct position of the online data table based on the logic in the SQL script (such as `PARTITION BY`, `ORDER BY`, etc.), and then only the feature aggregation computing is performed on that row, returning the unique corresponding extraction result. The following diagram intuitively explains the operation process of the online request mode. -![modes-request](https://openmldb.ai/docs/zh/main/_images/modes-request.png) +![modes-request](images/modes-request.png) Online request mode is supported in the following ways: From eeb37b6912f9d42acc2d4dd438a96b4c98fcf734 Mon Sep 17 00:00:00 2001 From: HuangWei Date: Tue, 31 Oct 2023 17:05:34 +0800 Subject: [PATCH 28/32] fix: recoverdata and log print (#3545) * fix: ops log print * fix log and try recover all table --- tools/openmldb_ops.py | 9 +++++---- tools/tool.py | 8 +++++--- 2 files changed, 10 insertions(+), 7 deletions(-) diff --git a/tools/openmldb_ops.py b/tools/openmldb_ops.py index c7ae0663b52..543c0bbfbf9 100644 --- a/tools/openmldb_ops.py +++ b/tools/openmldb_ops.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. import logging - +# for Python 2, don't use f-string log = logging.getLogger(__name__) import os import sys @@ -118,8 +118,8 @@ def RecoverPartition(executor, db, partitions, endpoint_status): db=db, table_name=table_name, pid=pid, leader_endpoint=leader_endpoint)) status = executor.LoadTable(leader_endpoint, table_name, tid, pid) if not status.OK(): - log.error("load table failed. db {db} name {table_name} tid {tid} pid {pid} endpoint {leader_endpoint} msg {status.GetMsg()}".format( - db=db, table_name=table_name, tid=tid, pid=pid, leader_endpoint=leader_endpoint, status=status)) + log.error("load table failed. db {db} name {table_name} tid {tid} pid {pid} endpoint {leader_endpoint} msg {status}".format( + db=db, table_name=table_name, tid=tid, pid=pid, leader_endpoint=leader_endpoint, status=status.GetMsg())) return Status(-1, "recover partition failed") if not partitions[leader_pos].IsAlive(): status = executor.UpdateTableAlive(db, table_name, pid, leader_endpoint, "yes") @@ -204,8 +204,9 @@ def RecoverData(executor): log.error("get all table failed") return for name in tables: + # if recover failed, continue to recover next table if not RecoverTable(executor, db, name).OK(): - return + log.error("recover table failed. db {db} name {name}, check log for detail".format(db=db, name=name)) def ChangeLeader(db, partition, src_endpoint, desc_endpoint, one_replica, restore = True): log.info( diff --git a/tools/tool.py b/tools/tool.py index e64b172b49b..cff6eb1db98 100644 --- a/tools/tool.py +++ b/tools/tool.py @@ -16,6 +16,7 @@ import subprocess import sys import time +# for Python 2, don't use f-string log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format = '%(levelname)s: %(message)s') @@ -276,6 +277,7 @@ def LoadTable(self, endpoint, name, tid, pid, sync = True): cmd = list(self.tablet_base_cmd) cmd.append("--endpoint=" + self.endpoint_map[endpoint]) cmd.append("--cmd=loadtable {} {} {} 0 8".format(name, tid, pid)) + log.info("run {cmd}".format(cmd = cmd)) status, output = self.RunWithRetuncode(cmd) time.sleep(1) if status.OK() and output.find("LoadTable ok") != -1: @@ -289,12 +291,12 @@ def LoadTable(self, endpoint, name, tid, pid, sync = True): if table_stat == "kTableNormal": return Status() elif table_stat == "kTableLoading" or table_stat == "kTableUndefined": - log.info("table is loading... tid {tid} pid {pid}".format(tid, pid)) + log.info("table is loading... tid {tid} pid {pid}".format(tid = tid, pid = pid)) else: - return Status(-1, "table stat is {table_stat}".format(table_stat)) + return Status(-1, "table stat is {table_stat}".format(table_stat = table_stat)) time.sleep(2) - return Status(-1, "execute load table failed") + return Status(-1, "execute load table failed, status {msg}, output {output}".format(msg = status.GetMsg(), output = output)) def GetLeaderFollowerOffset(self, endpoint, tid, pid): cmd = list(self.tablet_base_cmd) From f864f8c83d0ec002e86dcede2b6825086f5618a2 Mon Sep 17 00:00:00 2001 From: HuangWei Date: Tue, 31 Oct 2023 17:06:34 +0800 Subject: [PATCH 29/32] feat: full inspect (#3559) * feat: full inspect * docs: diag and must read --- docs/zh/maintain/diagnose.md | 117 ++++- docs/zh/quickstart/beginner_must_read.md | 24 +- python/openmldb_tool/README.md | 16 +- .../openmldb_tool/diagnostic_tool/diagnose.py | 66 ++- .../openmldb_tool/diagnostic_tool/inspect.py | 410 ++++++++++++++++++ python/openmldb_tool/diagnostic_tool/pb.py | 118 +++++ python/openmldb_tool/diagnostic_tool/rpc.py | 124 ++---- .../diagnostic_tool/table_checker.py | 116 +++-- python/openmldb_tool/setup.py | 6 +- python/openmldb_tool/tests/inspect_test.py | 355 +++++++++++++++ src/proto/tablet.proto | 2 +- 11 files changed, 1165 insertions(+), 189 deletions(-) create mode 100644 python/openmldb_tool/diagnostic_tool/inspect.py create mode 100644 python/openmldb_tool/diagnostic_tool/pb.py create mode 100644 python/openmldb_tool/tests/inspect_test.py diff --git a/docs/zh/maintain/diagnose.md b/docs/zh/maintain/diagnose.md index eef7db5b5a1..cb5d7a30f74 100644 --- a/docs/zh/maintain/diagnose.md +++ b/docs/zh/maintain/diagnose.md @@ -8,14 +8,76 @@ 安装方式与使用： ```bash -pip install openmldb-tool # openmldb-tool[rpc] +pip install openmldb-tool # openmldb-tool[pb] openmldb_tool # 注意下划线 ``` 有以下几个子命令可选择执行： ```bash -usage: openmldb_tool [-h] [--helpfull] {status,inspect,test,static-check} ... +usage: openmldb_tool [-h] [--helpfull] {status,inspect,rpc,test,static-check} ... ``` -只有`static-check`静态检查命令需要指定`--dist_conf`参数，该参数指定OpenMLDB节点分布的配置文件。其他命令只需要`--cluster`参数，格式为`/`，默认为镜像中的OpenMLDB集群地址`127.0.0.1:2181/openmldb`。如果是自行设置的OpenMLDB集群，请配置此参数。 + +注意`-c/--cluster`参数，格式为`/`，默认将访问`127.0.0.1:2181/openmldb`。如果是自行设置的OpenMLDB集群，请配置此参数。其他参数根据子命令不同而不同，可以使用`-h`查看，或查看各个子命令的详细文档。 + +### 一键inspect + +`openmldb_tool inspect [--cluster=0.0.0.0:2181/openmldb]`可以一键查询，得到完整的集群状态报告。如果需要局部视角或额外的诊断功能，才需要其他子命令。 + +报告分为几个板块，其中如果所有表都是健康的，不会展示Ops和Partitions板块。用户首先看报告末尾的总结 summary & hint，如果存在server offline（红色），需先重启server，保证server尤其是TabletServer都在线。server重启后，集群可能会尝试自动修复，自动修复也可能会失败，所以，用户有必要等待一定时间后再次inspect。此时如果仍然有不健康的表，可以检查它们的状态，Fatal表需要尽快修复，它们可能会读写失败，Warn表，用户可以考虑推迟修复。修复方式见报告末尾提供的文档。 + +`inspect`可配置参数除了`--cluster/-c`，还可配置不显示彩色`--nocolor/-noc`方便复制，以及`--table_width/-tw n`配置表格宽度，`--offset_diff_thresh/-od n`配置offset diff的报警阈值。 + +``` +diagnosing cluster xxx + + +Server Detail +{server map} +{server online/offline report} + + +Table Partitions Detail +tablet server order: {tablet ip -> idx} +{partition tables of unhealthy tables} +Example: +{a detailed description of partition table} + + +Ops Detail +> failed ops do not mean cluster is unhealthy, just for reference +last one op(check time): {} +last 10 ops != finished: +{op list} + + + +================== +Summary & Hint +================== +Server: + +{online | offline servers ['[tablet]xxx'], restart them first} + +Table: +{all healthy | unhealthy tables desc} +[]Fatal/Warn table, {read/write may fail or still work}, {repair immediatly or not} +{partition detail: if leader healthy, if has unhealthy replicas, if offset too large, related ops} + + Make sure all servers online, and no ops for the table is running. + Repair table manually, run recoverdata, check https://openmldb.ai/docs/zh/main/maintain/openmldb_ops.html. + Check 'Table Partitions Detail' above for detail. +``` + +### 其他常用命令 + +除了一键inspect，在这样几个场景中，我们推荐使用诊断工具的子命令来帮助用户判断集群状态、简化运维。 + +- 部署好集群后，可以使用`test`测试集群是否能正常工作，不需要用户手动测试。如果发现问题，再使用`inspect`诊断。 +- 组件都在线，但出现超时或错误提示某组件无法连接时，可以使用`status --conn`检查与各组件的连接，会打印出简单访问的耗时。也可以用它来测试客户端主机与集群的连接情况，及时发现网络隔离。 +- 离线job如果出现问题，`SHOW JOBLOG id`可以查看日志，但经验较少的用户可能会被日志中的无关信息干扰，可以使用`inspect job`来提取job日志中的关键信息。 +- 离线job太多时，CLI中的展示会不容易读，可以使用`inspect offline`筛选所有failed的job，或者`inspect job --state `来筛选出特定状态的job。 +- 在一些棘手的问题中，可能需要用户通过RPC来获得一些信息，帮助定位问题。`openmldb_tool rpc`可以帮助用户简单快速地调用RPC，降低运维门槛。 +- 没有Prometheus监控时，可以通过`inspect online --dist`获得数据分布信息。 +- 如果你的操作节点到各个组件的机器是ssh免密的，那么，可以使用`static-check`检查配置文件是否正确，版本是否统一，避免部署失败。还可以一键收集整个集群的日志，方便打包并提供给开发人员分析。 ## 子命令详情 @@ -29,7 +91,8 @@ usage: openmldb_tool status [-h] [--helpfull] [--diff] optional arguments: -h, --help show this help message and exit --helpfull show full help message and exit - --diff check if all endpoints in conf are in cluster. If set, need to set `--conf_file` + --diff check if all endpoints in conf are in cluster. If set, need to set `-f,--conf_file` + --conn check network connection of all servers ``` - 简单查询集群状态： @@ -48,6 +111,11 @@ optional arguments: +-----------------+-------------+---------------+--------+---------+ ``` +- 检查并测试集群链接与版本： + ``` + openmldb_tool status --conn + ``` + #### 检查配置文件与集群状态是否一致 如果指定`--diff`参数，会检查配置文件中的所有节点是否都在已经启动的集群中，如果有节点不在集群中，会输出异常信息。如果集群中有节点不在配置文件中，不会输出异常信息。需要配置`-f,--conf_file`，例如，你可以在镜像里这样检查： @@ -57,7 +125,8 @@ openmldb_tool status --diff -f=/work/openmldb/conf/hosts ### inspect 检查 -`inspect`用于检查集群的在线和离线两个部分是否正常工作，可以选择单独检查`online`或`offline`，不指定则都检查。可以定期执行检查，以便及时发现异常。 +如果是为了检查集群状态，更推荐一键`inspect`获取集群完整检查报告，`inspect`子命令是更具有针对性的检查。 + ``` openmldb_tool inspect -h usage: openmldb_tool inspect [-h] [--helpfull] {online,offline,job} ... @@ -68,19 +137,26 @@ positional arguments: offline only inspect offline jobs. job show jobs by state, show joblog or parse joblog by id. ``` -在线检查会检查集群中的表状态（包括系统表），并输出有异常的表，包括表的状态，分区信息，副本信息等，等价于`SHOW TABLE STATUS`并筛选出有异常的表。如果发现集群表现不正常，请先检查下是否有异常表。例如，`SHOW JOBS`无法正常输出历史任务时，可以`inspect online`检查一下是否是job系统表出现问题。 + +#### online在线检查 + +`inspect online`检查在线表的健康状态，并输出有异常的表，包括表的状态，分区信息，副本信息等，等价于`SHOW TABLE STATUS`并筛选出有异常的表。 ##### 检查在线数据分布 -在线检查中，可以使用`inspect online --dist`检查在线数据分布，默认检查所有数据库，可以使用`--db`指定要检查的数据库。若要查询多个数据库，请使用 ',' 分隔数据库名称。会输出数据库在各个节点上的数据分布情况。 +可以使用`inspect online --dist`检查在线数据分布，默认检查所有数据库，可以使用`--db`指定要检查的数据库。若要查询多个数据库，请使用 ',' 分隔数据库名称。会输出数据库在各个节点上的数据分布情况。 -#### 离线检查 +#### offline离线检查 -离线检查会输出最终状态为失败的任务（不检查“运行中”的任务），等价于`SHOW JOBS`并筛选出失败任务。 +`inspect offline`离线检查会输出最终状态为失败的任务（不检查“运行中”的任务），等价于`SHOW JOBS`并筛选出失败任务。更多功能待补充。 #### JOB 检查 -JOB 检查会检查集群中的离线任务，可以使用`inspect job`或`inspect job --state all`查询所有任务，等价于`SHOW JOBS`并按job_id排序。使用`inspect job --state `可以筛选出特定状态的日志，可以使用 ',' 分隔，同时查询不同状态的日志。例如：`inspect offline` 相当于`inspect job --state failed,killed,lost`即筛选出所有失败的任务。 +JOB 检查是更灵活的离线任务检查命令，可以按条件筛选job，或针对单个job日志进行分析。 + +##### 按state筛选 + +可以使用`inspect job`或`inspect job --state all`查询所有任务，等价于`SHOW JOBS`并按job_id排序。使用`inspect job --state `可以筛选出特定状态的日志，可以使用 ',' 分隔，同时查询不同状态的日志。例如：`inspect offline` 相当于`inspect job --state failed,killed,lost`即筛选出所有失败的任务。 以下是一些常见的state: @@ -93,8 +169,13 @@ JOB 检查会检查集群中的离线任务，可以使用`inspect job`或`inspe 更多state信息详见[Spark State]( https://spark.apache.org/docs/3.2.1/api/java/org/apache/spark/launcher/SparkAppHandle.State.html)，[Yarn State](https://hadoop.apache.org/docs/current/api/org/apache/hadoop/yarn/api/records/YarnApplicationState.html) +##### 解析单个JOB日志 -使用`inspect job --id `查询指定任务的log日志，其结果会使用配置文件筛选出主要错误信息。如需更新配置文件，可以添加`--conf-update`，并且可以使用`--conf-url`配置镜像源，例如使用`--conf-url https://openmldb.ai/download/diag/common_err.yml`配置国内镜像。如果需要完整的日志信息，可以添加`--detail`获取详细信息。 +使用`inspect job --id `查询指定任务的log日志，其结果会使用配置文件筛选出主要错误信息。 + +解析依靠配置文件，默认情况会自动下载。如需更新配置文件，可以`--conf-update`，它将会在解析前强制下载一次配置文件。如果默认下载源不合适，可以同时配置`--conf-url`配置镜像源，例如使用`--conf-url https://openmldb.ai/download/diag/common_err.yml`配置国内镜像。 + +如果只需要完整的日志信息而不是解析日志的结果，可以使用`--detail`获取详细信息，不会打印解析结果。 ### test 测试 @@ -185,7 +266,6 @@ nameserver: 如果检查配置文件或日志，将会把收集到的文件保存在`--collect_dir`中，默认为`/tmp/diag_collect`。你也也可以访问此目录查看收集到的配置或日志，进行更多的分析。 - #### 检查示例 在镜像容器中可以这样静态检查： @@ -193,14 +273,15 @@ nameserver: openmldb_tool static-check --conf_file=/work/openmldb/conf/hosts -VCL --local ``` -### rpc +### RPC 接口 + +`openmldb_tool`还提供了一个RPC接口，它可以让我们发送RPC更容易，不需要定位Server的IP，拼接RPC方法URL路径，也可以提示所有RPC方法和RPC方法的输入结构。使用方式是`openmldb_tool rpc`，例如，`openmldb_tool rpc ns ShowTable --field '{"show_all":true}'`可以调用`nameserver`的`ShowTable`接口，获取表的状态信息。 -`openmldb_tool`还提供了一个RPC接口，但它是一个额外组件，需要通过`pip install openmldb-tool[rpc]`安装。使用方式是`openmldb_tool rpc`，例如，`openmldb_tool rpc ns ShowTable --field '{"show_all":true}'`可以调用`nameserver`的`ShowTable`接口，获取表的状态信息。 +其中组件不使用ip，可以直接使用角色名。NameServer与TaskManager只有一个活跃，所以我们用ns和tm来代表这两个组件。而TabletServer有多个，我们用`tablet1`，`tablet2`等来指定某个TabletServer，从1开始，顺序可通过`openmldb_tool rpc`或`openmldb_tool status`来查看。 -NameServer与TaskManager只有一个活跃，所以我们用ns和tm来代表这两个组件。 -而TabletServer有多个，我们用`tablet1`，`tablet2`等来指定某个TabletServer，顺序可通过`openmldb_tool rpc`或`openmldb_tool status`来查看。 +如果对RPC服务的方法或者输入参数不熟悉，可以通过`openmldb_tool rpc [method] --hint`查看帮助信息。但它是一个额外组件，需要通过`pip install openmldb-tool[pb]`安装。hint还需要额外的pb文件，帮助解析输入参数，默认是从`/tmp/diag_cache`中读取，如果不存在则自动下载。如果你已有相应的文件，或者已经手动下载，可以通过`--pbdir`指定该目录。自行编译pb文件，见[openmldb tool开发文档](https://github.com/4paradigm/OpenMLDB/blob/main/python/openmldb_tool/README.md#rpc)。 -如果对RPC服务的方法或者输入参数不熟悉，可以通过`openmldb_tool rpc [method] --hint`查看帮助信息。例如： +例如： ```bash $ openmldb_tool rpc ns ShowTable --hint ... @@ -212,9 +293,7 @@ You should input json like this, ignore round brackets in the key and double quo "(optional)show_all": "bool" }' ``` -hint还需要额外的pb文件，帮助解析输入参数，默认是从`/tmp/diag_cache`中读取，如果不存在则自动下载。如果你已有相应的文件，或者已经手动下载，可以通过`--pbdir`指定该目录。 ## 附加 可使用`openmldb_tool --helpfull`查看所有配置项。例如，`--sdk_log`可以打印sdk的日志（zk，glog），可用于调试。 - \ No newline at end of file diff --git a/docs/zh/quickstart/beginner_must_read.md b/docs/zh/quickstart/beginner_must_read.md index f5ba729613f..def0e3728d1 100644 --- a/docs/zh/quickstart/beginner_must_read.md +++ b/docs/zh/quickstart/beginner_must_read.md @@ -2,6 +2,20 @@ 由于OpenMLDB是分布式系统，多种模式，客户端丰富，初次使用可能会有很多疑问，或者遇到一些运行、使用问题，本文从新手使用的角度，讲解如何进行诊断调试，需求帮助时如何提供有效信息给技术人员等等。 +## 错误诊断 + +在使用OpenMLDB的过程中，除了SQL语法错误，其他错误信息可能不够直观，但很可能与集群状态有关。所以，错误诊断需要**先确认集群状态**。在发现错误时，请先使用诊断工具的一键诊断功能。一键诊断可以输出全面直观的诊断报告，如果不能使用此工具，可以手动执行`SHOW COMPONENTS;`和`SHOW TABLE STATUS LIKE '%';`提供部分信息。 + +报告将展示集群的组件、在线表等状态，也会提示用户如何修复，请按照报告内容进行操作，详情见[一键inspect](../maintain/diagnose.md#一键inspect)。 + +``` +openmldb_tool inspect [-c=0.0.0.0:2181/openmldb] +``` + +需要注意，由于离线存储只会在执行离线job时被读取，而离线job也不是一个持续的状态，所以，一键诊断只能展示TaskManager组件状态，不会诊断离线存储，也无法诊断离线job的执行错误，离线job诊断见[离线SQL执行](#离线)。 + +如果诊断报告认为集群健康，但仍然无法解决问题，请提供错误和诊断报告给我们。 + ## 创建OpenMLDB与连接 首先，我们建议不熟悉分布式多进程管理的新手使用docker创建OpenMLDB，方便快速上手。熟悉OpenMLDB各组件之后，再尝试分布式部署。 @@ -71,12 +85,14 @@ create table t1(c1 int; 如果是集群离线命令，默认异步模式下，发送命令会得到job id的返回。可使用`show job `来查询job执行情况。 -离线job如果是异步SELECT（并不INTO保存结果），也不会将结果打印在客户端（同步SELECT将会打印结果）。可以通过`show joblog `来获得结果，结果中包含stdout和stderr两部分，stdout为查询结果，stderr为job运行日志。如果发现job failed或者其他状态，不符合你的预期，请仔细查看job运行日志。 +离线job如果是异步SELECT（并不INTO保存结果），也不会将结果打印在客户端，而同步SELECT将会打印结果到控制台。可以通过`show joblog `来获得结果，结果中包含stdout和stderr两部分，stdout为查询结果，stderr为job运行日志。如果发现job failed或者其他状态，不符合你的预期，请仔细查看job运行日志。 -```{note} -日志地址由taskmanager.properties的`job.log.path`配置，如果你改变了此配置项，需要到配置的目的地寻找日志。stdout日志默认在`/work/openmldb/taskmanager/bin/logs/job_x.log`，job运行日志默认在`/work/openmldb/taskmanager/bin/logs/job_x_error.log`(注意有error后缀)， +离线job日志中可能有一定的干扰日志，用户可以使用`openmldb_tool inspect job --id x`进行日志的解析提取，帮助定位错误，更多信息请参考[诊断工具job检查](../maintain/diagnose.md#job-检查)。 -如果taskmanager是yarn模式，而不是local模式，`job_x_error.log`中的信息会较少，不会有job错误的详细信息。需要通过`job_x_error.log`中记录的yarn app id，去yarn系统中查询job的真正错误原因。 +如果taskmanager是yarn模式，而不是local模式，`job_x_error.log`中的信息会较少，只会打印异常。如果异常不直观，需要更早时间的执行日志，执行日志不在`job_x_error.log`中，需要通过`job_x_error.log`中记录的yarn app id，去yarn系统中查询yarn app的container的日志。yarn app container里，执行日志也保存在stderr中。 + +```{note} +如果你无法通过show joblog获得日志，或者想要直接拿到日志文件，可以直接在TaskManager机器上获取。日志地址由taskmanager.properties的`job.log.path`配置，如果你改变了此配置项，需要到配置的目录中寻找日志。stdout查询结果默认在`/work/openmldb/taskmanager/bin/logs/job_x.log`，stderr job运行日志默认在`/work/openmldb/taskmanager/bin/logs/job_x_error.log`(注意有error后缀)。 ``` #### 在线 diff --git a/python/openmldb_tool/README.md b/python/openmldb_tool/README.md index 3381751edf9..d5168a4bf25 100644 --- a/python/openmldb_tool/README.md +++ b/python/openmldb_tool/README.md @@ -48,21 +48,27 @@ status [-h] [--helpfull] [--diff DIFF] optional arguments: -h, --help show this help message and exit --helpfull show full help message and exit - --diff check if all endpoints in conf are in cluster. If set, need to set `--conf_file` + --diff check if all endpoints in conf are in cluster. If set, need to set `-f,--conf_file` ``` Use `show components` to show servers(no apiserver now). +--conn: +- ping all servers, brpc /health to check ok，and +- online servers version and cost time, we can get from brpc http:///version. (ns,tablet, apiserver set_version in brpc server) + TODO: -- ping all servers, brpc /health to check ok -- online servers version, we can get from brpc http:///version. (ns,tablet, apiserver set_version in brpc server) - brpc /flags to get all gflags(including openmldb), `--enable_flags_service=true` required ## Inspect -Use `show table status like '%';` in all dbs, even the hidden db(system db). +`inspect` for full report, no offline diag now. + +inspect online: Use `show table status like '%';` in all dbs, even the hidden db(system db). + +inspect offline: failed jobs, no more info. TODO: check register table? -If you found some online tables are not behaving properly, do inspect online. +inspect job: full support of offline job, select jobs, parse job log ## Test diff --git a/python/openmldb_tool/diagnostic_tool/diagnose.py b/python/openmldb_tool/diagnostic_tool/diagnose.py index 8bd67719489..21ee2961421 100644 --- a/python/openmldb_tool/diagnostic_tool/diagnose.py +++ b/python/openmldb_tool/diagnostic_tool/diagnose.py @@ -31,13 +31,15 @@ import diagnostic_tool.server_checker as checker from diagnostic_tool.table_checker import TableChecker from diagnostic_tool.parser import LogParser +from .inspect import server_ins, table_ins, partition_ins, ops_ins, ops_hint, inspect_hint +from .rpc import RPC from absl import app from absl import flags from absl.flags import argparse_flags from absl import logging # --verbosity --log_dir -# only some sub cmd needs dist file +# only some sub cmd needs dist file TODO(hw): better to move then to other py file, to avoid -h show them flags.DEFINE_string( "conf_file", "", @@ -81,7 +83,7 @@ def status(args): # --diff with dist conf file, conf_file is required if args.diff: - assert flags.FLAGS.conf_file, "need --conf_file" + assert flags.FLAGS.conf_file, "need -f,--conf_file" print( "only check components in conf file, if cluster has more components, ignore them" ) @@ -96,39 +98,56 @@ def status(args): def inspect(args): - insepct_online(args) - inspect_offline(args) + # report all + # 1. server level + connect = Connector() + status_checker = checker.StatusChecker(connect) + server_map = status_checker._get_components() + offlines = server_ins(server_map) + + # 3. ns ops level, but show only if has unhealthy tables, so hint later + last_one, should_warn, related_ops = ops_ins(connect) + + # 2. partition level: show unhealthy tables and get some hints about table + hints = partition_ins(server_map, related_ops) + if hints: + # show 3 here + ops_hint(last_one, should_warn) + # 4. hint + # let user know what to do + # 1) start offline servers + # 2) let user know the warning table is fatal or not, related ops, warn if offset is too large + # 3) if table not healthy and no related ops, use recoverdata + inspect_hint(offlines, hints) def insepct_online(args): - """show table status""" - conn = Connector() + """inspect online""" + connect = Connector() # scan all db include system db - fails = [] - rs = conn.execfetch("show table status like '%';") - rs.sort(key=lambda x: x[0]) - print(f"inspect {len(rs)} online tables(including system tables)") - for t in rs: + fails = table_ins(connect) + for t in fails: if t[13]: print(f"unhealthy table {t[2]}.{t[1]}:\n {t[:13]}") # sqlalchemy truncated ref https://github.com/sqlalchemy/sqlalchemy/commit/591e0cf08a798fb16e0ee9b56df5c3141aa48959 # so we print warnings alone print(f"full warnings:\n{t[13]}") - fails.append(f"{t[2]}.{t[1]}") - - assert not fails, f"unhealthy tables: {fails}" - print(f"all tables are healthy") + # if has fails, summary will print in table_ins + if not fails: + print(f"all tables are healthy") if getattr(args, "dist", False): - table_checker = TableChecker(conn) - table_checker.check_distribution(dbs=flags.FLAGS.db.split(",")) + table_checker = TableChecker(connect) + dbs = flags.FLAGS.db + db_list = dbs.split(",") if dbs else None + table_checker.check_distribution(dbs=db_list) def inspect_offline(args): """scan jobs status, show job log if failed""" final_failed = ["failed", "killed", "lost"] total, num, jobs = _get_jobs(final_failed) - # TODO some failed jobs are known, what if we want skip them? + # TODO some failed jobs are known or too old, what if we want skip them? print(f"inspect {total} offline jobs") if num: failed_jobs_str = "\n".join(jobs) @@ -241,7 +260,6 @@ def rpc(args): tm: taskmanager""" ) return - from diagnostic_tool.rpc import RPC # use status connction to get version conns_with_version = { @@ -301,7 +319,7 @@ def parse_arg(argv): status_parser.add_argument( "--diff", action="store_true", - help="check if all endpoints in conf are in cluster. If set, need to set `--conf_file`", + help="check if all endpoints in conf are in cluster. If set, need to set `-f,--conf_file`", ) # TODO action support in all python 3.x? status_parser.add_argument( "--conn", @@ -313,10 +331,10 @@ def parse_arg(argv): # sub inspect inspect_parser = subparsers.add_parser( "inspect", - help="Inspect online and offline. Use `inspect [online/offline]` to inspect one.", + help="Get full inspect report, --nocolor for batch mode, --table_width for partition tables display", ) - # inspect online & offline inspect_parser.set_defaults(command=inspect) + inspect_sub = inspect_parser.add_subparsers() # inspect online online = inspect_sub.add_parser("online", help="only inspect online table.") @@ -325,7 +343,9 @@ def parse_arg(argv): "--dist", action="store_true", help="Inspect online distribution." ) # inspect offline - offline = inspect_sub.add_parser("offline", help="only inspect offline jobs.") + offline = inspect_sub.add_parser( + "offline", help="only inspect offline jobs, show failed jobs." + ) offline.set_defaults(command=inspect_offline) # inspect job ins_job = inspect_sub.add_parser( diff --git a/python/openmldb_tool/diagnostic_tool/inspect.py b/python/openmldb_tool/diagnostic_tool/inspect.py new file mode 100644 index 00000000000..288f819bb78 --- /dev/null +++ b/python/openmldb_tool/diagnostic_tool/inspect.py @@ -0,0 +1,410 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# Copyright 2021 4Paradigm +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" gen multi-level readable reports for cluster devops """ +from absl import flags +import json +from collections import defaultdict +from prettytable import PrettyTable + +from .rpc import RPC + +# ANSI escape codes +flags.DEFINE_bool("nocolor", False, "disable color output", short_name="noc") +flags.DEFINE_integer( + "table_width", + 12, + "max columns in one row, 1 partition use r+1 cols, set k*(r+1)", + short_name="tw", +) +flags.DEFINE_integer( + "offset_diff_thresh", 100, "offset diff threshold", short_name="od" +) + +# color: red, green +RED = "\033[31m" +GREEN = "\033[32m" +BLUE = "\033[34m" +YELLOW = "\033[1;33m" +RESET = "\033[0m" + + +# switch by nocolor flag +def cr_print(color, obj): + if flags.FLAGS.nocolor or color == None: + print(obj) + else: + print(f"{color}{obj}{RESET}") + + +def server_ins(server_map): + print("\n\nServer Detail") + print(server_map) + offlines = [] + for component, value_list in server_map.items(): + for endpoint, status in value_list: + if status != "online": + offlines.append(f"[{component}]{endpoint}") + continue # offline tablet is needlessly to rpc + if offlines: + s = "\n".join(offlines) + cr_print(RED, f"offline servers:\n{s}") + else: + cr_print(GREEN, "all servers online (no backup tm and apiserver)") + return offlines + + +# support nocolor +def light(color, symbol, detail): + if flags.FLAGS.nocolor: + return f"{symbol} {detail}" + else: + return f"{color}{symbol}{RESET} {detail}" + + +def state2light(state): + state = state.ljust(15) # state str should be less than 15 + if not state.startswith("k"): + # meta mismatch status, all red + return light(RED, "X", state) + else: + # meta match, get the real state + state = state[1:] + if state.startswith("TableNormal"): + # green + return light(GREEN, "O", state) + else: + # ref https://github.com/4paradigm/OpenMLDB/blob/0462f8a9682f8d232e8d44df7513cff66870d686/tools/tool.py#L291 + # undefined is loading too: state == "kTableLoading" or state == "kTableUndefined" + # snapshot doesn't mean unhealthy: state == "kMakingSnapshot" or state == "kSnapshotPaused" + return light(YELLOW, "=", state) + + +# similar with `show table status` warnings field, but easier to read +# prettytable.colortable just make table border and header lines colorful, so we color the value +def check_table_info(t, replicas_on_tablet, tablet2idx): + pnum, rnum = t["partition_num"], t["replica_num"] + assert pnum == len(t["table_partition"]) + # multi-line for better display, max display columns in one row + valuable_cols = pnum * (rnum + 1) + display_width = min(flags.FLAGS.table_width, valuable_cols) + # if real multi-line, the last line may < width, padding with empty string + rest = valuable_cols % display_width + total_cols = valuable_cols + (0 if rest == 0 else display_width - rest) + + idx_row = [""] * total_cols + leader_row = [""] * total_cols + followers_row = [""] * total_cols + + table_mark = 0 + hint = "" + for i, p in enumerate(t["table_partition"]): + # each partition add 3 row, and rnum + 1 columns + # tablet idx pid | 1 | 4 | 5 + # leader 1 o + # followers o o + pid = p["pid"] + assert pid == i + + # sort by list tablets + replicas = [] + for r in p["partition_meta"]: + tablet = r["endpoint"] + # tablet_has_partition useless + # print(r["endpoint"], r["is_leader"], r["tablet_has_partition"]) + replicas_on_t = replicas_on_tablet[t["tid"]][p["pid"]] + # may can't find replica on tablet, e.g. tablet server is not ready + info_on_tablet = {} + if r["endpoint"] not in replicas_on_t: + info_on_tablet = {"state": "Miss", "mode": "Miss", "offset": -1} + else: + info_on_tablet = replicas_on_t[r["endpoint"]] + # print(info_on_tablet) + m = { + "role": "leader" if r["is_leader"] else "follower", + "state": info_on_tablet["state"], + "acrole": info_on_tablet["mode"], + "offset": info_on_tablet["offset"], + } + replicas.append((tablet2idx[tablet], m)) + + assert len(replicas) == rnum + replicas.sort(key=lambda x: x[0]) + leader_ind = [i for i, r in enumerate(replicas) if r[1]["role"] == "leader"] + # replica on offline tablet is still in the ns meta, so leader may > 1 + # assert len(ind) <= 1, f"should be only one leader or miss leader in {replicas}" + + # show partition idx and tablet server idx + cursor = i * (rnum + 1) + idx_row[cursor : cursor + rnum + 1] = ["p" + str(pid)] + [ + r[0] for r in replicas + ] + + # fulfill leader line + if leader_ind: + for leader in leader_ind: + # leader state + lrep = replicas[leader][1] + if lrep["state"] != "Miss" and lrep["acrole"] != "kTableLeader": + lrep["state"] = "NotLeaderOnT" # modify the state + leader_row[cursor + leader + 1] = state2light(lrep["state"]) + else: + # can't find leader in nameserver metadata, set in the first column(we can't find leader on any tablet) + leader_row[cursor] = state2light("NotFound") + + # fulfill follower line + for i, r in enumerate(replicas): + idx = cursor + i + 1 + if i in leader_ind: + continue + frep = r[1] + if frep["state"] != "Miss" and frep["acrole"] != "kTableFollower": + frep["state"] = "NotFollowerOnT" + followers_row[idx] = state2light(frep["state"]) + + # after state adjust, diag table + replicas = [r[1] for r in replicas] # tablet server is needless now + # fatal: leader replica is not normal, may read/write fail + # get one normal leader, the partition can work + if not leader_ind or not any( + [replicas[i]["state"] == "kTableNormal" for i in leader_ind] + ): + table_mark = max(4, table_mark) + hint += f"partition {pid} leader replica is not normal\n" + # warn: need repair(may auto repair by auto_failover), but not in emergency + # follower replica is not normal + if any([r["state"] != "kTableNormal" for r in replicas]): + table_mark = max(3, table_mark) + hint += f"partition {pid} has unhealthy replicas\n" + + # offset is not consistent, only check normal replicas + offsets = [r["offset"] for r in replicas if r["state"] == "kTableNormal"] + if offsets and max(offsets) - min(offsets) > flags.FLAGS.offset_diff_thresh: + table_mark = max(3, table_mark) + hint += ( + f"partition {pid} has offset diff > {flags.FLAGS.offset_diff_thresh}\n" + ) + + x = PrettyTable(align="l") + + x.field_names = [i for i in range(display_width)] + step = display_width + for i in range(0, len(idx_row), step): + x.add_row(idx_row[i : i + step]) + x.add_row(leader_row[i : i + step]) + x.add_row(followers_row[i : i + step], divider=True) + + table_summary = "" + if table_mark >= 4: + table_summary = light( + RED, + "X", + f"Fatal table {t['db']}.{t['name']}, read/write may fail, need repair immediately", + ) + elif table_mark >= 3: + table_summary = light( + YELLOW, "=", f"Warn table {t['db']}.{t['name']}, still work, but need repair" + ) + if table_summary: + table_summary += "\n" + hint + return x, table_summary + + +def show_table_info(t, replicas_on_tablet, tablet2idx): + """check table info and display for ut""" + print( + f"Table {t['tid']} {t['db']}.{t['name']} {t['partition_num']} partitions {t['replica_num']} replicas" + ) + table, _ = check_table_info(t, replicas_on_tablet, tablet2idx) + print(table.get_string(border=True, header=False)) + + +def table_ins(connect): + print("\n\nTable Healthy Detail") + rs = connect.execfetch("show table status like '%';") + rs.sort(key=lambda x: x[0]) + print(f"summary: {len(rs)} tables(including system tables)") + warn_tables = [] + for t in rs: + # any warning means unhealthy, partition_unalive may be 0 but already unhealthy, warnings is accurate? + if t[13]: + warn_tables.append(t) + if warn_tables: + # only show tables name + s = "\n".join([f"{t[2]}.{t[1]}" for t in warn_tables]) + cr_print(RED, f"unhealthy tables:\n{s}") + else: + cr_print(GREEN, "all tables are healthy") + return warn_tables + + +def partition_ins(server_map, related_ops): + print("\n\nTable Partition Detail") + # ns table info + rpc = RPC("ns") + res = rpc.rpc_exec("ShowTable", {"show_all": True}) + if not res: + cr_print(RED, "get table info failed or empty from nameserver") + return + res = json.loads(res) + all_table_info = res["table_info"] + + # get table info from tablet server + # >> + replicas = defaultdict(lambda: defaultdict(dict)) + tablets = server_map["tablet"] # has status + invalid_tablets = set() + for tablet, status in tablets: + if status == "offline": + invalid_tablets.add(tablet) + continue + # GetTableStatusRequest empty field means get all + rpc = RPC(tablet) + res = None + try: + res = json.loads(rpc.rpc_exec("GetTableStatus", {})) + except Exception as e: + print(f"rpc {tablet} failed") + # may get empty when tablet server is not ready + if not res or res["code"] != 0: + cr_print(RED, f"get table status failed or empty from {tablet}(online)") + invalid_tablets.add(tablet) + continue + if "all_table_status" not in res: + # just empty replica on tablet, skip + continue + for rep in res["all_table_status"]: + rep["tablet"] = tablet + # tid, pid are int + tid, pid = rep["tid"], rep["pid"] + replicas[tid][pid][tablet] = rep + + tablet2idx = {tablet[0]: i + 1 for i, tablet in enumerate(tablets)} + print(f"tablet server order: {tablet2idx}") + if invalid_tablets: + cr_print( + RED, + f"some tablet servers are offline/bad, can't get table info(exclude empty table server): {invalid_tablets}", + ) + + # display, depends on table info, replicas are used to check + all_table_info.sort(key=lambda x: x["tid"]) + # related op map + related_ops_map = {} + for op in related_ops: + db = op[9] + table = op[10] + if db not in related_ops_map: + related_ops_map[db] = {} + if table not in related_ops_map[db]: + related_ops_map[db][table] = [] + related_ops_map[db][table].append(op) + # print(f"related ops: {related_ops_map}") + print("") # for better display + diag_result = [] + for t in all_table_info: + # no need to print healthy table + table, diag_hint = check_table_info(t, replicas, tablet2idx) + if diag_hint: + print( + f"Table {t['tid']} {t['db']}.{t['name']} {t['partition_num']} partitions {t['replica_num']} replicas" + ) + print(table.get_string(header=False)) + if t["db"] in related_ops_map and t["name"] in related_ops_map[t["db"]]: + diag_hint += f"related op: {sorted(related_ops_map[t['db']][t['name']], key=lambda x: x[11])}" # 11 is pid + diag_result.append(diag_hint) + # comment for table info display, only for unhealthy table TODO: draw a example + if diag_result: + print( + """ +Example: +tablet server order: {'xxx': 1, 'xxx': 2, 'xxx': 3} -> get real tablet addr by idx ++----+-------------------+------------------+------------------+ +| p0 | 1 | 2 | 3 | -> p0: partition 0, 1-3: tablet server idx +| | [light] status | | | -> leader replica is on tablet 1 +| | | [light] status | [light] status | -> follower replicas are on tablet 2, 3 ++----+-------------------+------------------+------------------+ +light: +Green O -> OK +Yellow = -> replica meta is ok but state is not normal +Red X -> NotFound/Miss/NotFollowerOnT/NotLeaderOnT""" + ) + return diag_result + + +def ops_ins(connect): + # op sorted by id TODO: detail to show all include succ op? + rs = connect.execfetch("show jobs from NameServer;") + should_warn = [] + from datetime import datetime + # already in order + ops = [list(op) for op in rs] + for i in range(len(ops)): + op = ops[i] + op[3] = str(datetime.fromtimestamp(int(op[3]) / 1000)) if op[4] else "..." + op[4] = str(datetime.fromtimestamp(int(op[4]) / 1000)) if op[4] else "..." + if op[2] != "FINISHED": + should_warn.append(op) + + recover_type = ["kRecoverTableOP", "kChangeLeaderOP", "kReAddReplicaOP", "kOfflineReplicaOP"] + related_ops = [ + op + for op in should_warn + if op[1] in recover_type and op[2] in ["Submitted", "RUNNING"] + ] + return ops[-1] if ops else None, should_warn, related_ops + +def ops_hint(last_one, should_warn): + print("\n\nOps Detail") + print("> failed ops do not mean cluster is unhealthy, just for reference") + # peek last one to let user know if cluster has tried to recover, or we should wait + if last_one: + print("last one op(check time): ", last_one) + else: + print("no ops in nameserver") + if not should_warn: + print("all nameserver ops are finished") + else: + print("last 10 ops != finished:") + print(*should_warn[-10:], sep="\n") + +def inspect_hint(server_hint, table_hints): + print( + """ + +================== +Summary & Hint +================== +Server: +""" + ) + if server_hint: + cr_print(RED, f"offline servers {server_hint}, restart them first") + else: + cr_print(GREEN, "all servers online") + print("\nTable:\n") + for h in table_hints: + print(h) + if table_hints: + print( + """ + Make sure all servers online, and no ops for the table is running. + Repair table manually, run recoverdata, check https://openmldb.ai/docs/zh/main/maintain/openmldb_ops.html. + Check 'Table Partitions Detail' above for detail. + """ + ) + else: + cr_print(GREEN, "all tables are healthy") diff --git a/python/openmldb_tool/diagnostic_tool/pb.py b/python/openmldb_tool/diagnostic_tool/pb.py new file mode 100644 index 00000000000..06219d00b61 --- /dev/null +++ b/python/openmldb_tool/diagnostic_tool/pb.py @@ -0,0 +1,118 @@ +# Copyright 2021 4Paradigm +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from google.protobuf.descriptor import Descriptor, FieldDescriptor +from absl import flags + + +class DescriptorHelper: + def __init__(self, service): + # lazy import + assert flags.FLAGS.pbdir, "pbdir not set" + import sys + from pathlib import Path + + sys.path.append(Path(flags.FLAGS.pbdir).as_posix()) + import tablet_pb2 + import name_server_pb2 + import taskmanager_pb2 + + # google.protobuf.symbol_database can get service desc by name, but we have already included all pb2 files we need + # just use one file + pb_map = { + "TabletServer": tablet_pb2, + "NameServer": name_server_pb2, + "TaskManagerServer": taskmanager_pb2, + # "ApiServer": api_server_pb2, + # "DataSync": data_sync_pb2, + } + self.descriptor = pb_map[service].DESCRIPTOR.services_by_name[service] + # from google.protobuf import symbol_database + # self.sym_db = symbol_database.Default() + + def get_input_json(self, method): + m = self.descriptor.FindMethodByName(method) + if not m: + return False, f"method {method} not found" + if not m.input_type.fields: # e.g. ShowTabletRequest is emtpy + return False, f"method {method} has no input" + # GeneratedProtocolMessageType __dict__ is complex, can't use it directly + # cl = self.sym_db.GetSymbol(m.input_type.full_name) + + # fields build a map, message is Descriptor, fields in msg is FieldDescriptor + return True, Field.to_json(m.input_type) + + +class Field: + def to_str(typ): + typ2str = { + FieldDescriptor.TYPE_DOUBLE: "double", + FieldDescriptor.TYPE_FLOAT: "float", + FieldDescriptor.TYPE_INT64: "int64", + FieldDescriptor.TYPE_UINT64: "uint64", + FieldDescriptor.TYPE_INT32: "int32", + FieldDescriptor.TYPE_FIXED64: "fixed64", + FieldDescriptor.TYPE_FIXED32: "fixed32", + FieldDescriptor.TYPE_BOOL: "bool", + FieldDescriptor.TYPE_STRING: "string", + FieldDescriptor.TYPE_GROUP: "group", + FieldDescriptor.TYPE_MESSAGE: "message", + FieldDescriptor.TYPE_BYTES: "bytes", + FieldDescriptor.TYPE_UINT32: "uint32", + } + return typ2str[typ] + + def to_json(field): + # label optional, required, or repeated. + label = {1: "optional", 2: "required", 3: "repeated"} + + def is_map(f): + # I'm a map(containing_type = who includes me and my fields name are key-value) + # e.g. tm RunBatchSql --hint the conf field is map + return f.containing_type and [ff.name for ff in f.fields] == [ + "key", + "value", + ] + + if isinstance(field, FieldDescriptor): + if field.message_type: + # message_type is a Descriptor, check if it's a map + if is_map(field.message_type): + m = field.message_type + # treat key-value as map type, can't figure out custom type, no nested, so just generate here + return { + f"<{m.fields[0].name}>": f"<{m.fields[1].name}>", + "...": "...", + } + else: + # normal nested message + return Field.to_json(field.message_type) + elif field.type == FieldDescriptor.TYPE_ENUM: + return "/".join([n.name for n in field.enum_type.values]) + else: + return f"<{Field.to_str(field.type)}>" + + elif isinstance(field, Descriptor): + d = {} + for f in field.fields: + # each one is FieldDescriptor + # map is repeated too, but it's not a list + if f.label == 3 and not is_map(f.message_type): + # json list style + d[f"({label[f.label]})" + f.name] = [Field.to_json(f), "..."] + else: + d[f"({label[f.label]})" + f.name] = Field.to_json(f) + return d + else: + raise ValueError(f"unknown type {type(field)}") diff --git a/python/openmldb_tool/diagnostic_tool/rpc.py b/python/openmldb_tool/diagnostic_tool/rpc.py index 686734e7641..8e3f8efc660 100644 --- a/python/openmldb_tool/diagnostic_tool/rpc.py +++ b/python/openmldb_tool/diagnostic_tool/rpc.py @@ -12,103 +12,44 @@ # See the License for the specific language governing permissions and # limitations under the License. -from absl import flags import json import requests -from bs4 import BeautifulSoup -from google.protobuf.descriptor import FieldDescriptor from .server_checker import StatusChecker from .connector import Connector +from absl import flags + +# used by pb.py but set here for simplicity, we will check pbdir before call hint(import pb) flags.DEFINE_string( "pbdir", "/tmp/diag_cache", "pb2 root dir, if not set, will use the /pb2 directory in the same directory as this script", ) +def validate_ip_address(ip_string): + return not any(c.isalpha() for c in ip_string) -class DescriptorHelper: - def __init__(self, service): - # TODO(hw): symbol_database is useful? - # lazy import - assert flags.FLAGS.pbdir, "pbdir not set" - import sys - from pathlib import Path - sys.path.append(Path(flags.FLAGS.pbdir).as_posix()) - import tablet_pb2 - import name_server_pb2 - import taskmanager_pb2 - - pb_map = { - "TabletServer": tablet_pb2, - "NameServer": name_server_pb2, - "TaskManagerServer": taskmanager_pb2, - # "ApiServer": api_server_pb2, - # "DataSync": data_sync_pb2, - } - self.descriptor = pb_map[service].DESCRIPTOR.services_by_name[service] - - def get_input_json(self, method): - inp = self.descriptor.FindMethodByName(method).input_type - return Field.to_json(inp) - - -class Field: - def to_str(typ): - typ2str = { - FieldDescriptor.TYPE_DOUBLE: "double", - FieldDescriptor.TYPE_FLOAT: "float", - FieldDescriptor.TYPE_INT64: "int64", - FieldDescriptor.TYPE_UINT64: "uint64", - FieldDescriptor.TYPE_INT32: "int32", - FieldDescriptor.TYPE_FIXED64: "fixed64", - FieldDescriptor.TYPE_FIXED32: "fixed32", - FieldDescriptor.TYPE_BOOL: "bool", - FieldDescriptor.TYPE_STRING: "string", - FieldDescriptor.TYPE_GROUP: "group", - FieldDescriptor.TYPE_MESSAGE: "message", - FieldDescriptor.TYPE_BYTES: "bytes", - FieldDescriptor.TYPE_UINT32: "uint32", - } - return typ2str[typ] - - def to_json(field): - # label optional, required, or repeated. - label = {1: "optional", 2: "required", 3: "repeated"} - if isinstance(field, FieldDescriptor): - key = f"({label[field.label]})" + field.name - if field.type == FieldDescriptor.TYPE_MESSAGE: - value = Field.to_json(field.message_type) - elif field.type == FieldDescriptor.TYPE_ENUM: - value = "/".join([n.name for n in field.enum_type.values]) - else: - value = Field.to_str(field.type) - if field.label == 3: - # json list style - return {key: [value, "..."]} - else: - return {key: value} - else: - # field is a message - if field.containing_type and [f.name for f in field.fields] == [ - "key", - "value", - ]: - # treat key-value as map type, can't figure out custom type - # TODO(hw): it's ok to pass a json list to proto map? - return {"k": "v", "...": "..."} - d = {} - for f in field.fields: - d.update(Field.to_json(f)) - return d + +host2service = { + "nameserver": "NameServer", + "taskmanager": "openmldb.taskmanager.TaskManagerServer", + "tablet": "TabletServer", +} class RPC: """rpc service""" def __init__(self, host) -> None: - self.host, self.endpoint, self.service = RPC.get_endpoint_service(host.lower()) + if validate_ip_address(host): + self.endpoint = host + self.host = "tablet" # TODO: you can get ns/tm by name, it's not necessary to input ip + self.service = host2service[self.host] + else: + self.host, self.endpoint, self.service = RPC.get_endpoint_service( + host.lower() + ) def rpc_help(self): if self.host == "taskmanager": @@ -123,26 +64,31 @@ def rpc_exec(self, operation, field): ) return r.text - def hint(self, info): - if not info: + def hint(self, method): + if not method: # show service name and all rpc methods print(self.rpc_help()) return - # input message to json style - # if taskmanager, service in pb2 is TaskManagerServer service = ( self.service if not self.service.endswith("TaskManagerServer") else "TaskManagerServer" ) + from .pb import DescriptorHelper - helper = DescriptorHelper(service) - json_str = json.dumps(helper.get_input_json(info), indent=4) + ok, input_json = DescriptorHelper(service).get_input_json(method) + if not ok: + print(input_json) # if not ok, it's message + return + # input message to json style + json_str = json.dumps(input_json, indent=4) print( - f"You should input json like this, ignore round brackets in the key and double quotation marks in the value: --field '{json_str}'" + f"You should input json like this:\n --field '{json_str}'" ) + print("ignore round brackets in the key, e.g. (required)") + print('"<>" shows the data type, e.g. "" means you should set string') def search_in(self, typ, info): for item in typ: @@ -168,14 +114,12 @@ def get_endpoint_service(host): host = "nameserver" if host == "ns" else "taskmanager" assert host in components_map, f"{host} not found in cluster" endpoint = components_map[host][num][0] - host2service = { - "nameserver": "NameServer", - "taskmanager": "openmldb.taskmanager.TaskManagerServer", - "tablet": "TabletServer", - } + service = host2service[host] return host, endpoint, service def parse_html(html): + from bs4 import BeautifulSoup + soup = BeautifulSoup(html, "html.parser") return soup.get_text("\n") diff --git a/python/openmldb_tool/diagnostic_tool/table_checker.py b/python/openmldb_tool/diagnostic_tool/table_checker.py index 969e7d110e4..f9703054d5c 100644 --- a/python/openmldb_tool/diagnostic_tool/table_checker.py +++ b/python/openmldb_tool/diagnostic_tool/table_checker.py @@ -24,11 +24,11 @@ class TableChecker: def __init__(self, conn: Connector): self.conn = conn - def check_distribution(self, dbs: list): + def check_distribution(self, dbs: list = None): exist_dbs = [db[0] for db in self.conn.execfetch("SHOW DATABASES")] if not exist_dbs: return - if dbs == ['']: + if not dbs or len(dbs) == 0: dbs = exist_dbs assert all([db in exist_dbs for db in dbs]), "some databases are not exist" @@ -36,67 +36,87 @@ def check_distribution(self, dbs: list): url = f"http://{ns_leader}/NameServer/ShowTable" res = requests.get(url, json={"show_all": True}) tables = res.json()["table_info"] - + if not tables or len(tables) == 0: + print("no table") + return tablet2partition = {} tablet2count = {} tablet2mem = {} tablet2dused = {} table_infos = [] - max_values = {'mp': 0, 'mc': 0, 'mm': 0, 'md': 0} + max_values = {"mp": 0, "mc": 0, "mm": 0, "md": 0} for table in tables: - if table['db'] not in dbs: + if table["db"] not in dbs: continue t = {} - t['name'] = table['db'] + "." + table['name'] - parts = table['table_partition'] - part_dist = self._collect(parts, '') - count_dist = self._collect(parts, 'record_cnt') - mem_dist = self._collect(parts, 'record_byte_size') - dused_dist = self._collect(parts, 'diskused') - max_values['mp'] = max(max_values['mp'], *part_dist.values()) - max_values['mc'] = max(max_values['mc'], *count_dist.values()) - max_values['mm'] = max(max_values['mm'], *mem_dist.values()) - max_values['md'] = max(max_values['md'], *dused_dist.values()) - t['part_size'] = len(parts) - t['part_dist'] = part_dist - t['count_dist'] = count_dist - t['mem_dist'] = mem_dist - t['dused_dist'] = dused_dist + t["name"] = table["db"] + "." + table["name"] + parts = table["table_partition"] + part_dist = self._collect(parts, "") + count_dist = self._collect(parts, "record_cnt") + mem_dist = self._collect(parts, "record_byte_size") + dused_dist = self._collect(parts, "diskused") + t["part_size"] = len(parts) + t["part_dist"] = part_dist + t["count_dist"] = count_dist + t["mem_dist"] = mem_dist + t["dused_dist"] = dused_dist table_infos.append(t) self._add_merge(tablet2partition, part_dist) self._add_merge(tablet2count, count_dist) self._add_merge(tablet2mem, mem_dist) self._add_merge(tablet2dused, dused_dist) - max_values['mm'] = round(max_values['mm'] / 1024 / 1024, 4) - max_values['md'] = round(max_values['md'] / 1024 / 1024, 4) + def get_max(di): + return max(di.values()) + + max_values["mp"] = get_max(tablet2partition) + max_values["mc"] = get_max(tablet2count) + max_values["mm"] = round(get_max(tablet2mem) / 1024 / 1024, 4) + max_values["md"] = round(get_max(tablet2dused) / 1024 / 1024, 4) + max_width = 40 for t in table_infos: print() - print(t['name']) - print('partition size:', t['part_size']) - print('partition dist(include replica)') - self._show_dist(t['part_dist'], max_width=max_width * max(*t['part_dist'].values()) / max_values['mp']) - print('record count dist(include replica)') - self._show_dist(t['count_dist'], max_width=0 if max_values['mc'] == 0 else max_width * max(*t['count_dist'].values()) / max_values['mc']) - print('mem dist(include replica)(MB)') - self._byte2mb(t['mem_dist']) - self._show_dist(t['mem_dist'], max_width=0 if max_values['mm'] == 0 else max_width * max(*t['mem_dist'].values()) / max_values['mm']) - print('diskused dist(include replica)(MB)') - self._byte2mb(t['dused_dist']) - self._show_dist(t['dused_dist'], max_width=max_width * max(*t['dused_dist'].values()) / max_values['md']) + print(t["name"], "distribution") + print("partition size:", t["part_size"]) + print("partition dist(include replica)") + self._show_dist( + t["part_dist"], + max_width=max_width * get_max(t["part_dist"]) / max_values["mp"], + ) + print("record count dist(include replica)") + self._show_dist( + t["count_dist"], + max_width=0 + if max_values["mc"] == 0 + else max_width * get_max(t["count_dist"]) / max_values["mc"], + ) + print("mem dist(include replica)(MB)") + self._byte2mb(t["mem_dist"]) + self._show_dist( + t["mem_dist"], + max_width=0 + if max_values["mm"] == 0 + else max_width * get_max(t["mem_dist"]) / max_values["mm"], + ) + print("diskused dist(include replica)(MB)") + self._byte2mb(t["dused_dist"]) + self._show_dist( + t["dused_dist"], + max_width=max_width * get_max(t["dused_dist"]) / max_values["md"], + ) print() - print('total') - print('tablet2partition') + print("tablet server load distribution") + print("tablet2partition") self._show_dist(tablet2partition) - print('tablet2count') + print("tablet2count(row)") self._show_dist(tablet2count) - print('tablet2mem(MB)') + print("tablet2mem(MB)") self._byte2mb(tablet2mem) self._show_dist(tablet2mem) - print('tablet2diskused(MB)') + print("tablet2diskused(MB)") self._byte2mb(tablet2dused) self._show_dist(tablet2dused) @@ -106,16 +126,24 @@ def _byte2mb(self, dist: dict): def _show_dist(self, dist: dict, max_width=40): figc = tpl.figure() - figc.barh(list(dist.values()), labels=list(dist.keys()), max_width=max_width) + if not dist: # protect barh args + print("no data") + return + figc.barh( + list(dist.values()), + labels=list(dist.keys()), + max_width=max_width, + force_ascii=True, + ) figc.show() def _collect(self, parts, field): dist = {} for part in parts: - for replica in part['partition_meta']: - if replica['endpoint'] not in dist: - dist[replica['endpoint']] = 0 - dist[replica['endpoint']] += replica[field] if field else 1 + for replica in part["partition_meta"]: + if replica["endpoint"] not in dist: + dist[replica["endpoint"]] = 0 + dist[replica["endpoint"]] += replica[field] if field else 1 return dist def _add_merge(self, dist, dist2): diff --git a/python/openmldb_tool/setup.py b/python/openmldb_tool/setup.py index 7b9a8dcf27f..555e5b51153 100644 --- a/python/openmldb_tool/setup.py +++ b/python/openmldb_tool/setup.py @@ -28,7 +28,7 @@ "Programming Language :: Python :: 3", ], install_requires=[ - "openmldb >= 0.6.9", + "openmldb >= 0.8.1", "absl-py", "pyyaml", "paramiko", @@ -36,12 +36,12 @@ "requests", ], extras_require={ - "rpc": [ + "pb": [ "protobuf==3.6.1", "beautifulsoup4", ], "test": [ - "openmldb-tool[rpc]", + "openmldb-tool[pb]", "pytest", ], }, diff --git a/python/openmldb_tool/tests/inspect_test.py b/python/openmldb_tool/tests/inspect_test.py new file mode 100644 index 00000000000..6f5ece39c05 --- /dev/null +++ b/python/openmldb_tool/tests/inspect_test.py @@ -0,0 +1,355 @@ +import pytest +from diagnostic_tool.inspect import show_table_info +from absl import flags + +flags.FLAGS["nocolor"].parse(False) +flags.FLAGS["table_width"].parse(12) + + +def test_show(): + # assume 3 tablet server + tablets = ["0.0.0.0:1111", "0.0.0.0:2222", "0.0.0.0:3333"] + tablet2idx = {tablet: i + 1 for i, tablet in enumerate(tablets)} + # simple + t_info = { + "name": "TABLE_A", + "table_partition": [ + { + "pid": 0, + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": True, + # "offset": 0, + # "record_cnt": 0, + # "record_byte_size": 0, + # "tablet_has_partition": true, + # "diskused": 9025, + }, + { + "endpoint": tablets[1], + "is_leader": False, + }, + ], + # "term_offset": [{"term": 1, "offset": 0}], + # "record_cnt": 0, + # "record_byte_size": 0, + # "diskused": 9025, + } + ], + "tid": 0, + "partition_num": 1, + "replica_num": 2, + "db": "DB_A", + } + + replicas = { + 0: { + 0: { + tablets[0]: { + "tid": 0, # actually not used in show_table_info + "pid": 0, # not used in show_table_info + "offset": 5, # check offset on tablet, not ns + "mode": "kTableLeader", + "state": "kTableNormal", + # "is_expire": True, + # "record_cnt": 1, + # "idx_cnt": 1, + # "ts_idx_status": [ + # {"idx_name": "id", "seg_cnts": [0, 0, 0, 0, 0, 0, 1, 0]} + # ], + "name": "Foo", + # "record_byte_size": 127, + # "record_idx_byte_size": 177, + # "record_pk_cnt": 1, + # "compress_type": "kNoCompress", + # "skiplist_height": 1, + # "diskused": 10074, + # "storage_mode": "kMemory", + "tablet": tablets[0], + }, + tablets[1]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[1], + }, + } + } + } + + show_table_info(t_info, replicas, tablet2idx) + + print("healthy ns meta, but replicas on tablet are all follower") + t_info = { + "name": "TABLE_A", + "table_partition": [ + { + "pid": 0, + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": True, + }, + { + "endpoint": tablets[1], + "is_leader": False, + }, + { + "endpoint": tablets[2], + "is_leader": False, + }, + ], + } + ], + "tid": 0, + "partition_num": 1, + "replica_num": 3, + "db": "DB_A", + } + replicas = { + 0: { + 0: { + tablets[0]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[0], + }, + tablets[1]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[1], + }, + tablets[2]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[2], + }, + } + } + } + show_table_info(t_info, replicas, tablet2idx) + + print("ns meta all followers, no leader") + t_info = { + "name": "TABLE_A", + "table_partition": [ + { + "pid": 0, + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": False, + }, + { + "endpoint": tablets[1], + "is_leader": False, + }, + { + "endpoint": tablets[2], + "is_leader": False, + }, + ], + } + ], + "tid": 0, + "partition_num": 1, + "replica_num": 3, + "db": "DB_A", + } + replicas = { + 0: { + 0: { + tablets[0]: { + "mode": "kTableLeader", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[0], + }, + tablets[1]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[1], + }, + tablets[2]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[2], + }, + } + } + } + show_table_info(t_info, replicas, tablet2idx) + + print("no corresponding replica on tablet server") + t_info = { + "name": "TABLE_A", + "table_partition": [ + { + "pid": 0, + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": True, + }, + { + "endpoint": tablets[1], + "is_leader": False, + }, + { + "endpoint": tablets[2], + "is_leader": False, + }, + ], + } + ], + "tid": 0, + "partition_num": 1, + "replica_num": 3, + "db": "DB_A", + } + replicas = { + 0: { + 0: { + tablets[1]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[1], + }, + tablets[2]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[2], + }, + } + } + } + show_table_info(t_info, replicas, tablet2idx) + + print("meta match, but state is not normal") + t_info = { + "name": "TABLE_A", + "table_partition": [ + { + "pid": 0, + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": True, + }, + { + "endpoint": tablets[1], + "is_leader": False, + }, + { + "endpoint": tablets[2], + "is_leader": False, + }, + ], + }, + { + "pid": 1, + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": True, + }, + { + "endpoint": tablets[1], + "is_leader": False, + }, + { + "endpoint": tablets[2], + "is_leader": False, + }, + ], + }, + ], + "tid": 0, + "partition_num": 2, + "replica_num": 3, + "db": "DB_A", + } + replicas = { + 0: { + 0: { + tablets[0]: { + "mode": "kTableFollower", + "state": "kTableLoading", + "offset": 0, + "tablet": tablets[0], + }, + tablets[1]: { + "mode": "kTableFollower", + "state": "kMakingSnapshot", + "offset": 0, + "tablet": tablets[1], + }, + tablets[2]: { + "mode": "kTableFollower", + "state": "kSnapshotPaused", + "offset": 0, + "tablet": tablets[2], + }, + }, + 1: { + tablets[1]: { + "mode": "kTableFollower", + "state": "kTableUndefined", + "offset": 0, + }, + tablets[2]: { + "mode": "kTableFollower", + "state": "kTableNormal", + "offset": 0, + }, + }, + } + } + show_table_info(t_info, replicas, tablet2idx) + + print("more partitions, display well") + partnum = 13 + meta_pattern = { + "partition_meta": [ + { + "endpoint": tablets[0], + "is_leader": True, + }, + ], + } + t_info = { + "name": "TABLE_A", + "table_partition": [], + "tid": 0, + "partition_num": partnum, + "replica_num": 1, + "db": "DB_A", + } + replicas = {0: {}} + + for i in range(partnum): + t_info["table_partition"].append({"pid": i, **meta_pattern}) + + for i in range(partnum): + replicas[0][i] = { + tablets[0]: { + "mode": "kTableLeader", + "state": "kTableNormal", + "offset": 0, + "tablet": tablets[0], + } + } + print(t_info, replicas) + show_table_info(t_info, replicas, tablet2idx) + + print("nocolor") + flags.FLAGS["nocolor"].parse(True) + show_table_info(t_info, replicas, tablet2idx) diff --git a/src/proto/tablet.proto b/src/proto/tablet.proto index 2944794b0d9..0938c9d965c 100755 --- a/src/proto/tablet.proto +++ b/src/proto/tablet.proto @@ -829,7 +829,7 @@ message BulkLoadInfoResponse { required uint32 key = 1; // TODO(hw): java will use int, cpp uses uint32. Not good? required uint32 value = 2; } - repeated MapFieldEntry ts_idx_map = 2; // TODO(hw): proto3 supports map + repeated MapFieldEntry ts_idx_map = 2; // TODO(hw): proto3 can build map in proto2 syntax } repeated Segment segment = 1; } From 5dea9a373583e054ca66455a92b9eb56996b6c1a Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 31 Oct 2023 17:08:59 +0800 Subject: [PATCH 30/32] build(deps-dev): bump urllib3 from 1.26.17 to 1.26.18 in /docs (#3558) --- docs/poetry.lock | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/poetry.lock b/docs/poetry.lock index fa522bb44da..724b4f19340 100644 --- a/docs/poetry.lock +++ b/docs/poetry.lock @@ -670,13 +670,13 @@ test = ["coverage", "pytest", "pytest-cov"] [[package]] name = "urllib3" -version = "1.26.17" +version = "1.26.18" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" files = [ - {file = "urllib3-1.26.17-py2.py3-none-any.whl", hash = "sha256:94a757d178c9be92ef5539b8840d48dc9cf1b2709c9d6b588232a055c524458b"}, - {file = "urllib3-1.26.17.tar.gz", hash = "sha256:24d6a242c28d29af46c3fae832c36db3bbebcc533dd1bb549172cd739c82df21"}, + {file = "urllib3-1.26.18-py2.py3-none-any.whl", hash = "sha256:34b97092d7e0a3a8cf7cd10e386f401b3737364026c45e622aa02903dffe0f07"}, + {file = "urllib3-1.26.18.tar.gz", hash = "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0"}, ] [package.extras] From d00449d92173eaff0c28bcd8d28c68ee1e155323 Mon Sep 17 00:00:00 2001 From: dl239 Date: Tue, 31 Oct 2023 18:48:16 +0800 Subject: [PATCH 31/32] fix: desc (#3567) --- src/cmd/display.h | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/cmd/display.h b/src/cmd/display.h index 6f01549bada..518d68463de 100644 --- a/src/cmd/display.h +++ b/src/cmd/display.h @@ -106,13 +106,14 @@ __attribute__((unused)) static void PrintColumnKey( t.add("ttl"); t.add("ttl_type"); t.end_of_row(); - + int index_pos = 1; for (int i = 0; i < column_key_field.size(); i++) { const auto& column_key = column_key_field.Get(i); if (column_key.flag() == 1) { continue; } - t.add(std::to_string(i + 1)); + t.add(std::to_string(index_pos)); + index_pos++; t.add(column_key.index_name()); std::string key; for (const auto& name : column_key.col_name()) { From 23d7c50f7881715753888832b05d6745d18024ff Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Thu, 9 Nov 2023 16:26:27 +0800 Subject: [PATCH 32/32] feat(sql): WINDOW without ORDER BY (#3554) Rules: - ALLOWED for ROWS-type WINDOW - NOT ALLOWED for RANGE-type WINDOW with offset PRECEDING/FOLLOWING - NOT ALLOWED for WINDOW with attribute EXCLUDE CURRENT_TIME Without ORDER BY, rows are processed in an unspecified order. --- cases/function/window/error_window.yaml | 32 +++- cases/query/window_query.yaml | 231 +++++++++++++++++++++++ hybridse/include/node/sql_node.h | 3 + hybridse/include/vm/physical_op.h | 12 +- hybridse/src/node/sql_node.cc | 5 + hybridse/src/plan/planner.cc | 1 - hybridse/src/testing/engine_test_base.cc | 20 +- hybridse/src/vm/runner.cc | 37 ++-- hybridse/src/vm/transform.cc | 28 ++- 9 files changed, 326 insertions(+), 43 deletions(-) diff --git a/cases/function/window/error_window.yaml b/cases/function/window/error_window.yaml index 9e9419bc74f..8b41d1ff0bf 100644 --- a/cases/function/window/error_window.yaml +++ b/cases/function/window/error_window.yaml @@ -17,15 +17,17 @@ debugs: [] version: 0.5.0 cases: - id: 0 - desc: no order by + desc: RANGE-type WINDOW with offset PRECEDING/FOLLOWING requires ORDER BY inputs: - columns: [ "id int","c1 string","c3 int","c4 bigint","c5 float","c6 double","c7 timestamp","c8 date" ] indexs: [ "index1:c8:c4" ] rows: - [1,"aa",20,30,1.1,2.1,1590738990000,"2020-05-01"] sql: | - SELECT id, c1, c4, count(c4) OVER w1 as w1_c4_count FROM {0} WINDOW w1 AS (PARTITION BY {0}.c8 ROWS BETWEEN 2 PRECEDING AND CURRENT ROW); + SELECT id, c1, c4, count(c4) OVER w1 as w1_c4_count FROM {0} + WINDOW w1 AS (PARTITION BY {0}.c8 ROWS_RANGE BETWEEN 2 PRECEDING AND CURRENT ROW); expect: + msg: RANGE/ROWS_RANGE-type FRAME with offset PRECEDING/FOLLOWING requires exactly one ORDER BY column success: false - id: 1 desc: no partition by @@ -301,3 +303,29 @@ cases: SELECT id, c1, c3, sum(c4) OVER w1 as w1_c4_sum FROM {0} WINDOW w1 AS (PARTITION BY {0}.c33 ORDER BY {0}.c7 ROWS_RANGE BETWEEN 2s PRECEDING AND CURRENT ROW); expect: success: false + - id: 17 + desc: ROWS WINDOW + EXCLUDE CURRENT_TIME requires order by + inputs: + - columns: [ "id int","c1 string","c3 int","c4 bigint","c5 float","c6 double","c7 timestamp","c8 date" ] + indexs: [ "index1:c8:c4" ] + rows: + - [1,"aa",20,30,1.1,2.1,1590738990000,"2020-05-01"] + sql: | + SELECT id, c1, c4, count(c4) OVER w1 as w1_c4_count FROM {0} + WINDOW w1 AS (PARTITION BY {0}.c8 ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW EXCLUDE CURRENT_TIME); + expect: + msg: WINDOW with EXCLUDE CURRENT_TIME requires exactly one ORDER BY column + success: false + - id: 18 + desc: RANGE WINDOW + EXCLUDE CURRENT_TIME requires order by + inputs: + - columns: [ "id int","c1 string","c3 int","c4 bigint","c5 float","c6 double","c7 timestamp","c8 date" ] + indexs: [ "index1:c8:c4" ] + rows: + - [1,"aa",20,30,1.1,2.1,1590738990000,"2020-05-01"] + sql: | + SELECT id, c1, c4, count(c4) OVER w1 as w1_c4_count FROM {0} + WINDOW w1 AS (PARTITION BY {0}.c8 ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW EXCLUDE CURRENT_TIME); + expect: + msg: WINDOW with EXCLUDE CURRENT_TIME requires exactly one ORDER BY column + success: false diff --git a/cases/query/window_query.yaml b/cases/query/window_query.yaml index 84365be97f7..3c64259d8c5 100644 --- a/cases/query/window_query.yaml +++ b/cases/query/window_query.yaml @@ -901,3 +901,234 @@ cases: 200, 1, 1 300, 0, 0 400, 2, 2 + + # ====================================================================== + # WINDOW without ORDER BY + # ====================================================================== + - id: 24 + desc: ROWS WINDOW WITHOUT ORDER BY + mode: batch-unsupport + inputs: + - name: t1 + columns: + - id int + - gp int + - ts timestamp + indexs: + - idx:gp:ts + data: | + 1, 100, 20000 + 2, 100, 10000 + 3, 400, 20000 + 4, 400, 10000 + 5, 400, 15000 + 6, 400, 40000 + sql: | + select id, count(ts) over w as agg + from t1 + window w as ( + partition by gp + rows between 2 open preceding and current row + ) + request_plan: | + PROJECT(type=Aggregation) + REQUEST_UNION(partition_keys=(), orders=, rows=(, 2 OPEN PRECEDING, 0 CURRENT), index_keys=(gp)) + DATA_PROVIDER(request=t1) + DATA_PROVIDER(type=Partition, table=t1, index=idx) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(id, agg)) + REQUEST_JOIN(type=kJoinTypeConcat) + SIMPLE_PROJECT(sources=(id)) + DATA_PROVIDER(request=t1) + PROJECT(type=Aggregation) + REQUEST_UNION(partition_keys=(), orders=, rows=(, 2 OPEN PRECEDING, 0 CURRENT), index_keys=(gp)) + DATA_PROVIDER(request=t1) + DATA_PROVIDER(type=Partition, table=t1, index=idx) + expect: + columns: ["id int", "agg int64"] + order: id + data: | + 1, 1 + 2, 2 + 3, 1 + 4, 2 + 5, 2 + 6, 2 + - id: 25 + desc: RANGE WINDOW WITHOUT ORDER BY + mode: batch-unsupport + inputs: + - name: t1 + columns: + - id int + - gp int + - ts timestamp + indexs: + - idx:gp:ts + data: | + 1, 100, 20000 + 2, 100, 10000 + 3, 400, 20000 + 4, 400, 10 + 5, 400, 15000 + sql: | + select id, count(ts) over w as agg + from t1 + window w as ( + partition by gp + rows_range between unbounded preceding and current row + ) + request_plan: | + PROJECT(type=Aggregation) + REQUEST_UNION(partition_keys=(), orders=, range=(, 0 PRECEDING UNBOUND, 0 CURRENT), index_keys=(gp)) + DATA_PROVIDER(request=t1) + DATA_PROVIDER(type=Partition, table=t1, index=idx) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(id, agg)) + REQUEST_JOIN(type=kJoinTypeConcat) + SIMPLE_PROJECT(sources=(id)) + DATA_PROVIDER(request=t1) + PROJECT(type=Aggregation) + REQUEST_UNION(partition_keys=(), orders=, range=(, 0 PRECEDING UNBOUND, 0 CURRENT), index_keys=(gp)) + DATA_PROVIDER(request=t1) + DATA_PROVIDER(type=Partition, table=t1, index=idx) + expect: + columns: ["id int", "agg int64"] + order: id + data: | + 1, 1 + 2, 2 + 3, 1 + 4, 2 + 5, 3 + - id: 26 + desc: RANGE-type WINDOW WITHOUT ORDER BY + WINDOW attributes + mode: batch-unsupport + inputs: + - name: t1 + columns: + - id int + - gp int + - ts timestamp + indexs: + - idx:gp:ts + data: | + 1, 100, 20000 + 2, 100, 10000 + 3, 400, 20000 + 4, 400, 10000 + 5, 400, 15000 + - name: t2 + columns: + - id int + - gp int + - ts timestamp + indexs: + - idx:gp:ts + data: | + 1, 100, 20000 + 2, 100, 10000 + 3, 400, 20000 + 4, 400, 10000 + 5, 400, 15000 + sql: | + select id, + count(ts) over w1 as agg1, + count(ts) over w2 as agg2, + count(ts) over w3 as agg3, + count(ts) over w4 as agg4, + count(ts) over w5 as agg5, + count(ts) over w6 as agg6, + count(ts) over w7 as agg7, + from t1 + window w1 as ( + PARTITION by gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW), + w2 as (partition by gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW EXCLUDE CURRENT_ROW), + w3 as (PARTITION BY gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW MAXSIZE 1), + w4 as ( + UNION (select * from t2) + PARTITION BY gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW INSTANCE_NOT_IN_WINDOW), + w5 as ( + UNION (select * from t2) + PARTITION BY gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW INSTANCE_NOT_IN_WINDOW EXCLUDE CURRENT_ROW), + w6 as ( + UNION (select * from t2) + PARTITION BY gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW MAXSIZE 2 INSTANCE_NOT_IN_WINDOW EXCLUDE CURRENT_ROW), + w7 as ( + UNION (select * from t2) + PARTITION BY gp + ROWS_RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW EXCLUDE CURRENT_ROW) + expect: + columns: ["id int", "agg1 int64", "agg2 int64", "agg3 int64", "agg4 int64", "agg5 int64", "agg6 int64", "agg7 int64"] + order: id + data: | + 1, 1, 0, 1, 3, 2, 2, 2 + 2, 2, 1, 1, 3, 2, 2, 3 + 3, 1, 0, 1, 4, 3, 2, 3 + 4, 2, 1, 1, 4, 3, 2, 4 + 5, 3, 2, 1, 4, 3, 2, 5 + - id: 27 + desc: ROWS-type WINDOW WITHOUT ORDER BY + WINDOW attributes + mode: batch-unsupport + inputs: + - name: t1 + columns: + - id int + - gp int + - ts timestamp + indexs: + - idx:gp:ts + data: | + 1, 100, 20000 + 2, 100, 10000 + 3, 400, 20000 + 4, 400, 10000 + 5, 400, 15000 + - name: t2 + columns: + - id int + - gp int + - ts timestamp + indexs: + - idx:gp:ts + data: | + 1, 100, 20000 + 2, 100, 10000 + 3, 400, 20000 + 4, 400, 10000 + 5, 400, 15000 + sql: | + select id, + count(ts) over w1 as agg1, + count(ts) over w2 as agg2, + count(ts) over w3 as agg3, + count(ts) over w4 as agg4, + from t1 + window w1 as ( + PARTITION by gp + ROWS BETWEEN 2 PRECEDING AND CURRENT ROW), + w2 as (partition by gp + ROWS BETWEEN 2 PRECEDING AND CURRENT ROW EXCLUDE CURRENT_ROW), + w3 as ( + UNION (select * from t2) + PARTITION BY gp + ROWS BETWEEN 2 PRECEDING AND CURRENT ROW INSTANCE_NOT_IN_WINDOW), + w4 as ( + UNION (select * from t2) + PARTITION BY gp + ROWS BETWEEN 3 PRECEDING AND CURRENT ROW INSTANCE_NOT_IN_WINDOW EXCLUDE CURRENT_ROW) + expect: + columns: ["id int", "agg1 int64", "agg2 int64", "agg3 int64", "agg4 int64"] + order: id + data: | + 1, 1, 0, 3, 2 + 2, 2, 1, 3, 2 + 3, 1, 0, 3, 3 + 4, 2, 1, 3, 3 + 5, 3, 2, 3, 3 diff --git a/hybridse/include/node/sql_node.h b/hybridse/include/node/sql_node.h index bbdfc83313f..dcf162a96ab 100644 --- a/hybridse/include/node/sql_node.h +++ b/hybridse/include/node/sql_node.h @@ -1166,6 +1166,9 @@ class FrameBound : public SqlNode { int64_t GetOffset() const { return offset_; } void SetOffset(int64_t v) { offset_ = v; } + // is offset [OPEN] PRECEDING/FOLLOWING + bool is_offset_bound() const; + /// \brief get the inclusive frame bound offset value that has signed symbol /// diff --git a/hybridse/include/vm/physical_op.h b/hybridse/include/vm/physical_op.h index ee3634615c8..d2fdafb5349 100644 --- a/hybridse/include/vm/physical_op.h +++ b/hybridse/include/vm/physical_op.h @@ -200,9 +200,9 @@ class Range : public FnComponent { const bool Valid() const { return nullptr != range_key_; } const std::string ToString() const { std::ostringstream oss; - if (nullptr != range_key_ && nullptr != frame_) { + if (nullptr != frame_) { if (nullptr != frame_->frame_range()) { - oss << "range=(" << range_key_->GetExprString() << ", " + oss << "range=(" << node::ExprString(range_key_) << ", " << frame_->frame_range()->start()->GetExprString() << ", " << frame_->frame_range()->end()->GetExprString(); @@ -216,7 +216,7 @@ class Range : public FnComponent { if (nullptr != frame_->frame_range()) { oss << ", "; } - oss << "rows=(" << range_key_->GetExprString() << ", " + oss << "rows=(" << node::ExprString(range_key_) << ", " << frame_->frame_rows()->start()->GetExprString() << ", " << frame_->frame_rows()->end()->GetExprString() << ")"; } @@ -578,7 +578,7 @@ class PhysicalRequestProviderNode : public PhysicalDataProviderNode { PhysicalOpNode **out) override; virtual ~PhysicalRequestProviderNode() {} - virtual void Print(std::ostream &output, const std::string &tab) const; + void Print(std::ostream &output, const std::string &tab) const override; }; class PhysicalRequestProviderNodeWithCommonColumn @@ -846,9 +846,7 @@ class WindowOp { std::ostringstream oss; oss << "partition_" << partition_.ToString(); oss << ", " << sort_.ToString(); - if (range_.Valid()) { - oss << ", " << range_.ToString(); - } + oss << ", " << range_.ToString(); return oss.str(); } const std::string FnDetail() const { diff --git a/hybridse/src/node/sql_node.cc b/hybridse/src/node/sql_node.cc index 16b88cd51ba..6fa2a82d42a 100644 --- a/hybridse/src/node/sql_node.cc +++ b/hybridse/src/node/sql_node.cc @@ -2100,6 +2100,11 @@ void FrameBound::Print(std::ostream &output, const std::string &org_tab) const { } } +bool FrameBound::is_offset_bound() const { + return bound_type_ == kPreceding || bound_type_ == kOpenPreceding || bound_type_ == kFollowing || + bound_type_ == kOpenFollowing; +} + int FrameBound::Compare(const FrameBound *bound1, const FrameBound *bound2) { if (SqlEquals(bound1, bound2)) { return 0; diff --git a/hybridse/src/plan/planner.cc b/hybridse/src/plan/planner.cc index c0a68e3104e..1584d76acbb 100644 --- a/hybridse/src/plan/planner.cc +++ b/hybridse/src/plan/planner.cc @@ -18,7 +18,6 @@ #include #include -#include #include #include #include diff --git a/hybridse/src/testing/engine_test_base.cc b/hybridse/src/testing/engine_test_base.cc index ca1af237936..2c3134d1257 100644 --- a/hybridse/src/testing/engine_test_base.cc +++ b/hybridse/src/testing/engine_test_base.cc @@ -240,8 +240,7 @@ void DoEngineCheckExpect(const SqlCase& sql_case, std::shared_ptr se if (!output_common_column_indices.empty() && output_common_column_indices.size() != static_cast(schema.size()) && sql_ctx.is_batch_request_optimized) { - LOG(INFO) << "Reorder batch request outputs for non-trival common " - "columns"; + DLOG(INFO) << "Reorder batch request outputs for non-trival columns"; auto& expect_common_column_indices = sql_case.expect().common_column_indices_; if (!expect_common_column_indices.empty()) { @@ -375,7 +374,7 @@ Status EngineTestRunner::Compile() { std::string placeholder = "{" + std::to_string(j) + "}"; boost::replace_all(sql_str, placeholder, sql_case_.inputs_[j].name_); } - LOG(INFO) << "Compile SQL:\n" << sql_str; + DLOG(INFO) << "Compile SQL:\n" << sql_str; CHECK_TRUE(session_ != nullptr, common::kTestEngineError, "Session is not set"); if (hybridse::sqlcase::SqlCase::IsDebug() || sql_case_.debug()) { session_->EnableDebug(); @@ -395,22 +394,23 @@ Status EngineTestRunner::Compile() { bool ok = engine_->Get(sql_str, sql_case_.db(), *session_, status); gettimeofday(&et, nullptr); double mill = (et.tv_sec - st.tv_sec) * 1000 + (et.tv_usec - st.tv_usec) / 1000.0; - LOG(INFO) << "SQL Compile take " << mill << " milliseconds"; + DLOG(INFO) << "SQL Compile take " << mill << " milliseconds"; if (!ok || !status.isOK()) { - LOG(INFO) << status; + DLOG(INFO) << status; + if (!sql_case_.expect().msg_.empty()) { + EXPECT_EQ(sql_case_.expect().msg_, status.msg); + } return_code_ = ENGINE_TEST_RET_COMPILE_ERROR; } else { - LOG(INFO) << "SQL output schema:"; + DLOG(INFO) << "SQL output schema:"; std::ostringstream oss; std::dynamic_pointer_cast(session_->GetCompileInfo())->GetPhysicalPlan()->Print(oss, ""); - LOG(INFO) << "Physical plan:"; - std::cerr << oss.str() << std::endl; + DLOG(INFO) << "Physical plan:\n" << oss.str(); std::ostringstream runner_oss; std::dynamic_pointer_cast(session_->GetCompileInfo())->GetClusterJob().Print(runner_oss, ""); - LOG(INFO) << "Runner plan:"; - std::cerr << runner_oss.str() << std::endl; + DLOG(INFO) << "Runner plan:\n" << runner_oss.str(); } return status; } diff --git a/hybridse/src/vm/runner.cc b/hybridse/src/vm/runner.cc index be954653b91..586f75c6187 100644 --- a/hybridse/src/vm/runner.cc +++ b/hybridse/src/vm/runner.cc @@ -2785,6 +2785,7 @@ std::shared_ptr RequestUnionRunner::Run( auto request = std::dynamic_pointer_cast(left)->GetValue(); + // ts_gen < 0 if there is no ORDER BY clause for WINDOW int64_t ts_gen = range_gen_.Valid() ? range_gen_.ts_gen_.Gen(request) : -1; // Prepare Union Window @@ -2798,31 +2799,35 @@ std::shared_ptr RequestUnionRunner::Run( std::shared_ptr RequestUnionRunner::RequestUnionWindow( const Row& request, std::vector> union_segments, int64_t ts_gen, const WindowRange& window_range, bool output_request_row, bool exclude_current_time) { - uint64_t start = 0; - // end is empty means end value < 0, that there is no effective window range + // range_start, range_end default to [0, MAX], so for the case without ORDER BY, + // RANGE-type WINDOW includes all rows in partition + uint64_t range_start = 0; + // range_end is empty means end value < 0, that there is no effective window range // this happend when `ts_gen` is 0 and exclude current_time needed - std::optional end = UINT64_MAX; - uint64_t rows_start_preceding = 0; - uint64_t max_size = 0; + std::optional range_end = UINT64_MAX; + uint64_t rows_start_preceding = window_range.start_row_; + uint64_t max_size = window_range.max_size_; if (ts_gen >= 0) { - start = (ts_gen + window_range.start_offset_) < 0 + range_start = (ts_gen + window_range.start_offset_) < 0 ? 0 : (ts_gen + window_range.start_offset_); if (exclude_current_time && 0 == window_range.end_offset_) { if (ts_gen == 0) { - end = {}; + range_end = {}; } else { - end = ts_gen - 1; + range_end = ts_gen - 1; } } else { - end = (ts_gen + window_range.end_offset_) < 0 + range_end = (ts_gen + window_range.end_offset_) < 0 ? 0 : (ts_gen + window_range.end_offset_); } - rows_start_preceding = window_range.start_row_; - max_size = window_range.max_size_; } - uint64_t request_key = ts_gen > 0 ? static_cast(ts_gen) : 0; + // INT64_MAX is the magic number as row key of input row, + // when WINDOW without ORDER BY + // + // DONT BELIEVE THE UNSIGNED TYPE, codegen still use int64_t as data type + uint64_t request_key = ts_gen >= 0 ? static_cast(ts_gen) : INT64_MAX; auto window_table = std::make_shared(); @@ -2841,7 +2846,7 @@ std::shared_ptr RequestUnionRunner::RequestUnionWindow( union_segment_status[i] = IteratorStatus(); continue; } - union_segment_iters[i]->Seek(end.value_or(0)); + union_segment_iters[i]->Seek(range_end.value_or(0)); if (!union_segment_iters[i]->Valid()) { union_segment_status[i] = IteratorStatus(); continue; @@ -2854,7 +2859,7 @@ std::shared_ptr RequestUnionRunner::RequestUnionWindow( uint64_t cnt = 0; auto range_status = window_range.GetWindowPositionStatus( cnt > rows_start_preceding, window_range.end_offset_ < 0, - request_key < start); + request_key < range_start); if (output_request_row) { window_table->AddRow(request_key, request); } @@ -2868,8 +2873,8 @@ std::shared_ptr RequestUnionRunner::RequestUnionWindow( } auto range_status = window_range.GetWindowPositionStatus( cnt > rows_start_preceding, - union_segment_status[max_union_pos].key_ > end, - union_segment_status[max_union_pos].key_ < start); + union_segment_status[max_union_pos].key_ > range_end, + union_segment_status[max_union_pos].key_ < range_start); if (WindowRange::kExceedWindow == range_status) { break; } diff --git a/hybridse/src/vm/transform.cc b/hybridse/src/vm/transform.cc index 8020c99741f..d52667dbc6f 100644 --- a/hybridse/src/vm/transform.cc +++ b/hybridse/src/vm/transform.cc @@ -25,8 +25,6 @@ #include "codegen/context.h" #include "codegen/fn_ir_builder.h" #include "codegen/fn_let_ir_builder.h" -#include "passes/expression/expr_pass.h" -#include "passes/lambdafy_projects.h" #include "passes/physical/batch_request_optimize.h" #include "passes/physical/cluster_optimized.h" #include "passes/physical/condition_optimized.h" @@ -2230,13 +2228,29 @@ Status BatchModeTransformer::CheckWindow( const node::WindowPlanNode* w_ptr, const vm::SchemasContext* schemas_ctx) { CHECK_TRUE(w_ptr != nullptr, common::kPlanError, "NULL Window"); CHECK_TRUE(!node::ExprListNullOrEmpty(w_ptr->GetKeys()), common::kPlanError, - "Invalid Window: Do not support window on non-partition"); - CHECK_TRUE(nullptr != w_ptr->GetOrders() && - !node::ExprListNullOrEmpty(w_ptr->GetOrders()->order_expressions_), - common::kPlanError, - "Invalid Window: Do not support window on non-order"); + "un-implemented: WINDOW without PARTITION BY clause"); CHECK_STATUS(CheckHistoryWindowFrame(w_ptr)); + // without ORDER BY clause: + if (w_ptr->GetOrders() == nullptr || node::ExprListNullOrEmpty(w_ptr->GetOrders()->order_expressions())) { + // 1. forbidden: RANGE/ROWS_RANGE WINDOW WITH offset PRECEDING/FOLLOWING + if (w_ptr->frame_node()->frame_type() != node::FrameType::kFrameRows) { + auto* range = w_ptr->frame_node()->frame_range(); + if ((range->start() && range->start()->is_offset_bound()) || + (range->end() && range->end()->is_offset_bound())) { + CHECK_TRUE( + false, common::kPlanError, + "RANGE/ROWS_RANGE-type FRAME with offset PRECEDING/FOLLOWING requires exactly one ORDER BY column") + } + } + + // 2. forbidden: WINDOW without ORDER BY + EXCLUDE CURRENT_TIME + if (w_ptr->exclude_current_time()) { + CHECK_TRUE(false, common::kPlanError, + "WINDOW with EXCLUDE CURRENT_TIME requires exactly one ORDER BY column"); + } + } + CHECK_STATUS(CheckTimeOrIntegerOrderColumn(w_ptr->GetOrders(), schemas_ctx)); return Status::OK();

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The basic usage process is shown in the following diagram: +![modes-flow](concepts/images/modes-flow.png) -![modes-flow](https://openmldb.ai/docs/zh/main/_images/modes-flow.png) +As shown, OpenMLDB covers the feature computing process in machine learning, from offline development to real-time serving online, providing a complete process. Please refer to the documentation for [The Usage Process and Execution Mode](./concepts/modes.html) in detail. This article will demonstrate a quickstart step by step, showing the process for basic usage. -As can be seen, OpenMLDB covers the feature computing process of machine learning, from offline development to real-time request service online, providing a complete process. Please refer to the documentation for [the usage process and execution mode](https://openmldb.ai/docs/zh/main/quickstart/concepts/modes.html) in detail. This article will demonstrate a quick start and understanding of OpenMLDB step by step, following the basic usage process. +## Preparation -## The preparation - -This article is developed and deployed based on OpenMLDB CLI, and it is necessary to download the sample data and start OpenMLDB CLI first. It is recommended to use Docker image for a quick experience (Note: due to some known issues of Docker on macOS, the sample program in this article may encounter problems in completing the operation smoothly on macOS. It is recommended to run it on **Linux or Windows**). +This sample program is developed and deployed based on OpenMLDB CLI, so you need to download the sample data and start OpenMLDB CLI first. It is recommended to use Docker image for a quick experience (Note: due to some known issues of Docker on macOS, the sample program in this article may encounter problems on macOS. It is recommended to run it on **Linux or Windows**). - Docker Version: >= 18.03 -### Pulls the image +### Pull the Image Execute the following command in the command line to pull the OpenMLDB image and start the Docker container: @@ -23,18 +22,10 @@ docker run -it 4pdosc/openmldb:0.8.3 bash ``` ``` {note} -After successfully starting the container, all subsequent commands in this tutorial are executed inside the container by default. If you need to access the OpenMLDB server inside the container from outside the container, please refer to the [CLI/SDK-container onebox documentation](https://openmldb.ai/docs/zh/main/reference/ip_tips.html#id3). -``` - -### Download sample data - -Execute the following command inside the container to download the sample data used in the subsequent process (**this step can be skipped for versions 0.7.0 and later**, as the data is already stored in the image): - -```bash -curl https://openmldb.ai/demo/data.parquet --output /work/taxi-trip/data/data.parquet +After successfully starting the container, all subsequent commands in this tutorial are executed inside the container by default. If you need to access the OpenMLDB server inside the container from outside the container, please refer to the [CLI/SDK-container onebox documentation](../reference/ip_tips.md#clisdk-containeronebox). ``` -### Start the server and client +### Start the Server and Client Start the OpenMLDB server: @@ -48,19 +39,19 @@ Start the OpenMLDB CLI client: /work/openmldb/bin/openmldb --zk_cluster=127.0.0.1:2181 --zk_root_path=/openmldb --role=sql_client ``` -After successfully starting OpenMLDB CLI, it will be displayed as shown in the following figure: +Successful started OpenMLDB CLI will look as shown in the following figure: -![image](https://openmldb.ai/docs/zh/main/_images/cli_cluster.png) +![image](./images/cli_cluster.png) -## Use process +## OpenMLDB Process -Referring to the core concepts, the process of using OpenMLDB generally includes six steps: creating databases and tables, importing offline data, offline feature computing, deploying SQL solutions, importing online data, and online real-time feature computing. +Referring to the core concepts, the process of using OpenMLDB generally includes six steps: create database and table, import offline data, compute offline feature, deploy SQL plan, import online data, and online real-time feature compute. ```{note} Unless otherwise specified, the commands demonstrated below are executed by default in OpenMLDB CLI. ``` -### Step 1: Create database and table +### Step 1: Create Database and Table Create `demo_db` and table `demo_table1`: @@ -71,7 +62,7 @@ USE demo_db; CREATE TABLE demo_table1(c1 string, c2 int, c3 bigint, c4 float, c5 double, c6 timestamp, c7 date); ``` -### Step 2: Importing offline data +### Step 2: Import Offline Data Switch to the offline execution mode, and import the sample data as offline data for offline feature calculation. @@ -90,17 +81,21 @@ Note that the `LOAD DATA` command is an asynchronous command by default. You can - To show the task logs: SHOW JOBLOG job_id -Here, we use `SHOW JOBS` to check the task status. Please wait for the task to be successfully completed (the `state` is changed to `FINISHED`), and then proceed to the next step. +Here, we use `SHOW JOBS` to check the task status. Please wait for the task to be successfully completed ( `state` changes to `FINISHED`), and then proceed to the next step. + +![image-20220111141358808](./images/state_finished.png) + +After the task is completed, if you wish to preview the data, you can execute the `SELECT * FROM demo_table1` statement in synchronous mode by setting `SET @@sync_job=true`. However, this approach has certain limitations, which are detailed in the [Offline Command Synchronous Mode](./function_boundary.md#offline-command-synchronous-mode) section. -![image-20220111141358808](https://openmldb.ai/docs/zh/main/_images/state_finished.png) +In the default asynchronous mode, executing `SELECT * FROM demo_table1` will initiate an asynchronous task, and the results will be stored in the log files of the Spark job, making them less convenient to access. If TaskManager is in local mode, you can use `SHOW JOBLOG ` to view the query print results in the stdout section. -After the task is completed, if you want to preview the data, you can use the `SELECT * FROM demo_table1` statement. It is recommended to first set the offline command to synchronous mode (`SET @@sync_job=true`); otherwise, the command will submit an asynchronous task, and the result will be saved in the log file of the Spark task, which is less convenient to view. +The most reliable way to access the data is to use the `SELECT INTO` command to export the data to a specified directory or directly examine the storage location after importing it. ```{note} -OpenMLDB also supports importing offline data through linked soft copies, without the need for hard data copying. Please refer to the parameter `deep_copy` in the [LOAD DATA INFILE documentation](https://openmldb.ai/docs/zh/main/openmldb_sql/dml/LOAD_DATA_STATEMENT.html) for more information. +OpenMLDB also supports importing offline data through linked soft copies, without the need for hard data copying. Please refer to the parameter `deep_copy` in the [LOAD DATA INFILE Documentation](../openmldb_sql/dml/LOAD_DATA_STATEMENT.md) for more information. ``` -### Step 3: Offline feature computing +### Step 3: Compute Offline Feature Assuming that we have determined the SQL script (`SELECT` statement) to be used for feature computation, we can use the following command for offline feature computation: @@ -120,7 +115,7 @@ Note: - The `SELECT` statement is used to perform SQL-based feature extraction and store the generated features in the directory specified by the `OUTFILE` parameter as `feature_data`, which can be used for subsequent machine learning model training. -### Step 4: Deploying SQL solutions +### Step 4: Deploy SQL plan Switch to online preview mode, and deploy the explored SQL plan to online. The SQL plan is named `demo_data_service`, and the online SQL used for feature extraction needs to be consistent with the corresponding offline feature calculation SQL. @@ -131,11 +126,11 @@ USE demo_db; DEPLOY demo_data_service SELECT c1, c2, sum(c3) OVER w1 AS w1_c3_sum FROM demo_table1 WINDOW w1 AS (PARTITION BY demo_table1.c1 ORDER BY demo_table1.c6 ROWS BETWEEN 2 PRECEDING AND CURRENT ROW); ``` -After the deployment, you can use the command `SHOW DEPLOYMENTS` to view the deployed SQL solutions. +After the deployment, you can use the command `SHOW DEPLOYMENTS` to view the deployed SQL. -### Step 5: Importing online data +### Step 5: Import Online Data -Import the downloaded sample data as online data for online feature computation in online preview mode. +Import the downloaded sample data as online data for online feature computation in online mode. ```sql -- OpenMLDB CLI @@ -161,9 +156,9 @@ Note that currently, it is required to successfully deploy the SQL plan before i The tutorial skips the step of real-time data access after importing data. In practical scenarios, as time progresses, the latest real-time data needs to be updated in the online database. This can be achieved through the OpenMLDB SDK or online data source connectors such as Kafka, Pulsar, etc. ``` -### Step 6: Online real-time feature computing +### Step 6: Online Real-Time Feature Computing -The development and deployment work based on OpenMLDB CLI is completed. Next, you can make real-time feature calculation requests in real-time request mode. First, exit OpenMLDB CLI and return to the command line of the operating system. +The development and deployment work is completed. Next, you can make real-time feature calculation requests in real-time request mode. First, exit OpenMLDB CLI and return to the command line of the operating system. ```sql -- OpenMLDB CLI @@ -176,10 +171,10 @@ According to the default deployment configuration, the http port for APIServer i http://127.0.0.1:9080/dbs/demo_db/deployments/demo_data_service \___________/ \____/ \_____________/ | | | - APIServer地址 Database名字 Deployment名字 + APIServerAddress Database Name Deployment Name ``` -Real-time requests accept input data in JSON format. Here are two examples: putting a row of data in the `input` field of the request. +Real-time requests accept input data in JSON format. Here are two examples: putting data in the `input` field of the request. **Example 1:** @@ -187,7 +182,7 @@ Real-time requests accept input data in JSON format. Here are two examples: putt curl http://127.0.0.1:9080/dbs/demo_db/deployments/demo_data_service -X POST -d'{"input": [["aaa", 11, 22, 1.2, 1.3, 1635247427000, "2021-05-20"]]}' ``` -Query the expected return result (the calculated features are stored in the `data` field): +Expected query result (the calculated features are stored in the `data` field): ```json {"code":0,"msg":"ok","data":{"data":[["aaa",11,22]]}} @@ -205,7 +200,7 @@ Expected query result: {"code":0,"msg":"ok","data":{"data":[["aaa",11,66]]}} ``` -### Description of real-time feature computing results +### Explanation of Real-Time Feature Computing Results The SQL execution for online real-time requests is different from batch processing mode. The request mode only performs SQL calculations on the data of the request row. In the previous example, it is the input of the POST request that serves as the request row. The specific process is as follows: Assuming that this row of data exists in the table `demo_table1`, and the following feature calculation SQL is executed on it: @@ -213,7 +208,7 @@ The SQL execution for online real-time requests is different from batch processi SELECT c1, c2, sum(c3) OVER w1 AS w1_c3_sum FROM demo_table1 WINDOW w1 AS (PARTITION BY demo_table1.c1 ORDER BY demo_table1.c6 ROWS BETWEEN 2 PRECEDING AND CURRENT ROW); ``` -**The calculation logic for Example 1 is as follows:** +**The Calculation Logic for Example 1 is as Follows:** 1. Filter rows in column c1 with the value "aaa" based on the `PARTITION BY` partition of the request row and window, and sort them in ascending order by column c6. Therefore, in theory, the intermediate data table sorted by partition should be as follows. The request row is the first row after sorting. @@ -227,7 +222,7 @@ aaa 12 22 2.200000 12.300000 1636097890000 1970-01-01 ----- ---- ---- ---------- ----------- --------------- ------------ ``` -2. The window range is `2 PRECEDING AND CURRENT ROW`, so in the above table, the actual window is extracted, and the request row is the smallest row with no preceding two rows, but the window includes the current row, so the window only contains the request row. +2. The window range is `2 PRECEDING AND CURRENT ROW`. In the above table, when the actual window is extracted, the request row is the smallest row with no preceding 2 rows. Therefore the window only contains the request row. 3. For window aggregation, the sum of column c3 for the data within the window (only one row) is calculated, resulting in 22. Therefore, the output result is: ```sql @@ -238,7 +233,7 @@ aaa 11 22 ----- ---- ----------- ``` -**The calculation logic for Example 2 is as follows:** +**The Calculation Logic for Example 2 is as Follows:** 1. According to the partition of the request line and window by `PARTITION BY`, select the rows where column c1 is "aaa" and sort them in ascending order by column c6. Therefore, theoretically, the intermediate data table after partition and sorting should be as shown in the table below. The request row is the last row after sorting. @@ -252,7 +247,7 @@ aaa 11 22 1.2 1.3 1637000000000 2021-11-16 ----- ---- ---- ---------- ----------- --------------- ------------ ``` -2. The window range is `2 PRECEDING AND CURRENT ROW`, so the actual window is extracted from the above table, and the two preceding rows of the request row exist, and the current row is also included. Therefore, there are three rows of data in the window. +2. The window range is `2 PRECEDING AND CURRENT ROW`. When the actual window is extracted from the above table, the two preceding 2 rows of the request row exist, together with the current row. Therefore, there are three rows of data in the window. 3. For window aggregation, the sum of column c3 for the data within the window (three rows) is calculated, resulting in 22 + 22 + 22 = 66. Therefore, the output result is: ```sql From ff58ddcdacf638c8ba472e152acd4bfceddd9333 Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Mon, 16 Oct 2023 19:44:24 +0800 Subject: [PATCH 15/32] build(brpc): upgrade to apache/brpc 1.6.0 (#3415) * build(brpc): upgrade to apache/brpc 1.6.0 * build: apply brpc patch from 4pd --- third-party/cmake/FetchBrpc.cmake | 15 ++- third-party/patches/brpc-1.6.0-2235.patch | 91 ++++++++++++++++ third-party/patches/brpc-1.6.0.patch | 120 ++++++++++++++++++++++ 3 files changed, 222 insertions(+), 4 deletions(-) create mode 100644 third-party/patches/brpc-1.6.0-2235.patch create mode 100644 third-party/patches/brpc-1.6.0.patch diff --git a/third-party/cmake/FetchBrpc.cmake b/third-party/cmake/FetchBrpc.cmake index f4318ac21b3..af7e3b910d1 100644 --- a/third-party/cmake/FetchBrpc.cmake +++ b/third-party/cmake/FetchBrpc.cmake @@ -12,16 +12,23 @@ # See the License for the specific language governing permissions and # limitations under the License. -set(BRPC_URL https://github.com/4paradigm/incubator-brpc/archive/a85d1bde8df3a3e2e59a64ea5a3ee3122f9c6daa.zip) -message(STATUS "build brpc from ${BRPC_URL}") +set(BRPC_URL https://github.com/apache/brpc) +set(BRPC_TAG d2b73ec955dd04b06ab55065d9f3b4de1e608bbd) +message(STATUS "build brpc from ${BRPC_URL}@${BRPC_TAG}") + +find_package(Git REQUIRED) ExternalProject_Add( brpc - URL ${BRPC_URL} - URL_HASH SHA256=ea86d39313bed981357d2669daf1a858fcf1ec363465eda2eec60a8504a2c38e + GIT_REPOSITORY ${BRPC_URL} + GIT_TAG ${BRPC_TAG} PREFIX ${DEPS_BUILD_DIR} DOWNLOAD_DIR ${DEPS_DOWNLOAD_DIR}/brpc INSTALL_DIR ${DEPS_INSTALL_DIR} + PATCH_COMMAND ${GIT_EXECUTABLE} checkout . + COMMAND ${GIT_EXECUTABLE} clean -dfx . + COMMAND ${GIT_EXECUTABLE} apply ${PROJECT_SOURCE_DIR}/patches/brpc-1.6.0.patch + COMMAND ${GIT_EXECUTABLE} apply ${PROJECT_SOURCE_DIR}/patches/brpc-1.6.0-2235.patch DEPENDS gflags glog protobuf snappy leveldb gperf openssl CONFIGURE_COMMAND ${CMAKE_COMMAND} -H -B . -DWITH_GLOG=ON -DCMAKE_PREFIX_PATH=${DEPS_INSTALL_DIR} -DCMAKE_INSTALL_PREFIX=${DEPS_INSTALL_DIR} ${CMAKE_OPTS} BUILD_COMMAND ${CMAKE_COMMAND} --build . --target brpc-static -- ${MAKEOPTS} diff --git a/third-party/patches/brpc-1.6.0-2235.patch b/third-party/patches/brpc-1.6.0-2235.patch new file mode 100644 index 00000000000..450b4c6f427 --- /dev/null +++ b/third-party/patches/brpc-1.6.0-2235.patch @@ -0,0 +1,91 @@ +diff --git a/src/brpc/builtin/prometheus_metrics_service.cpp b/src/brpc/builtin/prometheus_metrics_service.cpp +index 7bf8bbf359..88f675bb81 100644 +--- a/src/brpc/builtin/prometheus_metrics_service.cpp ++++ b/src/brpc/builtin/prometheus_metrics_service.cpp +@@ -82,6 +82,12 @@ class PrometheusMetricsDumper : public bvar::Dumper { + std::map _m; + }; + ++butil::StringPiece GetMetricsName(const std::string& name) { ++ auto pos = name.find_first_of('{'); ++ int size = (pos == std::string::npos) ? name.size() : pos; ++ return butil::StringPiece(name.data(), size); ++} ++ + bool PrometheusMetricsDumper::dump(const std::string& name, + const butil::StringPiece& desc) { + if (!desc.empty() && desc[0] == '"') { +@@ -93,8 +99,11 @@ bool PrometheusMetricsDumper::dump(const std::string& name, + // Leave it to DumpLatencyRecorderSuffix to output Summary. + return true; + } +- *_os << "# HELP " << name << '\n' +- << "# TYPE " << name << " gauge" << '\n' ++ ++ auto metrics_name = GetMetricsName(name); ++ ++ *_os << "# HELP " << metrics_name << '\n' ++ << "# TYPE " << metrics_name << " gauge" << '\n' + << name << " " << desc << '\n'; + return true; + } +diff --git a/src/brpc/builtin/prometheus_metrics_service.h b/src/brpc/builtin/prometheus_metrics_service.h +index c844e1e7a0..541b395c82 100644 +--- a/src/brpc/builtin/prometheus_metrics_service.h ++++ b/src/brpc/builtin/prometheus_metrics_service.h +@@ -31,6 +31,7 @@ class PrometheusMetricsService : public brpc_metrics { + ::google::protobuf::Closure* done) override; + }; + ++butil::StringPiece GetMetricsName(const std::string& name); + int DumpPrometheusMetricsToIOBuf(butil::IOBuf* output); + + } // namepace brpc +diff --git a/test/brpc_prometheus_metrics_service_unittest.cpp b/test/brpc_prometheus_metrics_service_unittest.cpp +new file mode 100644 +index 0000000000..b5b0bc10d5 +--- /dev/null ++++ b/test/brpc_prometheus_metrics_service_unittest.cpp +@@ -0,0 +1,42 @@ ++// Licensed to the Apache Software Foundation (ASF) under one ++// or more contributor license agreements. See the NOTICE file ++// distributed with this work for additional information ++// regarding copyright ownership. The ASF licenses this file ++// to you under the Apache License, Version 2.0 (the ++// "License"); you may not use this file except in compliance ++// with the License. You may obtain a copy of the License at ++// ++// http://www.apache.org/licenses/LICENSE-2.0 ++// ++// Unless required by applicable law or agreed to in writing, ++// software distributed under the License is distributed on an ++// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY ++// KIND, either express or implied. See the License for the ++// specific language governing permissions and limitations ++// under the License. ++ ++// Date: 2023/05/06 15:10:00 ++ ++#include ++ ++#include "butil/strings/string_piece.h" ++#include "butil/iobuf.h" ++#include "brpc/builtin/prometheus_metrics_service.h" ++ ++namespace { ++ ++class PrometheusMetricsDumperTest : public testing::Test { ++protected: ++ void SetUp() {} ++ void TearDown() {} ++}; ++ ++TEST_F(PrometheusMetricsDumperTest, GetMetricsName) { ++ EXPECT_EQ("", brpc::GetMetricsName("")); ++ ++ EXPECT_EQ("commit_count", brpc::GetMetricsName("commit_count")); ++ ++ EXPECT_EQ("commit_count", brpc::GetMetricsName("commit_count{region=\"1000\"}")); ++} ++ ++} diff --git a/third-party/patches/brpc-1.6.0.patch b/third-party/patches/brpc-1.6.0.patch new file mode 100644 index 00000000000..00dda45df47 --- /dev/null +++ b/third-party/patches/brpc-1.6.0.patch @@ -0,0 +1,120 @@ +diff --git a/src/brpc/builtin/status_service.cpp b/src/brpc/builtin/status_service.cpp +index a6f5a4dae8..67880ec1a3 100644 +--- a/src/brpc/builtin/status_service.cpp ++++ b/src/brpc/builtin/status_service.cpp +@@ -37,6 +37,8 @@ extern MethodStatus* g_client_msg_status; + extern MethodStatus* g_server_msg_status; + } + ++DECLARE_bool(enable_vars_service); ++ + // Defined in vars_service.cpp + void PutVarsHeading(std::ostream& os, bool expand_all); + +@@ -47,7 +49,7 @@ void StatusService::default_method(::google::protobuf::RpcController* cntl_base, + ClosureGuard done_guard(done); + Controller *cntl = static_cast(cntl_base); + const Server* server = cntl->server(); +- const bool use_html = UseHTML(cntl->http_request()); ++ const bool use_html = FLAGS_enable_vars_service ? UseHTML(cntl->http_request()) : false; + + // NOTE: the plain output also fits format of public/configure so that user + // can load values more easily. +diff --git a/src/brpc/server.cpp b/src/brpc/server.cpp +index ce5a0dd2a3..4e1fbbe424 100644 +--- a/src/brpc/server.cpp ++++ b/src/brpc/server.cpp +@@ -109,6 +109,13 @@ butil::static_atomic g_running_server_count = BUTIL_STATIC_ATOMIC_INIT(0); + // Following services may have security issues and are disabled by default. + DEFINE_bool(enable_dir_service, false, "Enable /dir"); + DEFINE_bool(enable_threads_service, false, "Enable /threads"); ++DEFINE_bool(enable_status_service, false, "Enable /status"); ++DEFINE_bool(enable_vars_service, false, "Enable /vars"); ++DEFINE_bool(enable_connections_service, false, "Enable /connections"); ++DEFINE_bool(enable_flags_service, false, "Enable /flags"); ++DEFINE_bool(enable_rpcz_service, false, "Enable /rpcz"); ++DEFINE_bool(enable_hotspots_service, false, "Enable /hotspots/cpu /hotspots/heap /hotspots/growth /hotspots/contention"); ++DEFINE_bool(enable_index_service, false, "Enable /index?as_more"); + + DECLARE_int32(usercode_backup_threads); + DECLARE_bool(usercode_in_pthread); +@@ -465,31 +472,31 @@ Server::~Server() { + + int Server::AddBuiltinServices() { + // Firstly add services shown in tabs. +- if (AddBuiltinService(new (std::nothrow) StatusService)) { ++ if (FLAGS_enable_status_service && AddBuiltinService(new (std::nothrow) StatusService)) { + LOG(ERROR) << "Fail to add StatusService"; + return -1; + } +- if (AddBuiltinService(new (std::nothrow) VarsService)) { ++ if (FLAGS_enable_vars_service && AddBuiltinService(new (std::nothrow) VarsService)) { + LOG(ERROR) << "Fail to add VarsService"; + return -1; + } +- if (AddBuiltinService(new (std::nothrow) ConnectionsService)) { ++ if (FLAGS_enable_connections_service && AddBuiltinService(new (std::nothrow) ConnectionsService)) { + LOG(ERROR) << "Fail to add ConnectionsService"; + return -1; + } +- if (AddBuiltinService(new (std::nothrow) FlagsService)) { ++ if (FLAGS_enable_flags_service && AddBuiltinService(new (std::nothrow) FlagsService)) { + LOG(ERROR) << "Fail to add FlagsService"; + return -1; + } +- if (AddBuiltinService(new (std::nothrow) RpczService)) { ++ if (FLAGS_enable_rpcz_service && AddBuiltinService(new (std::nothrow) RpczService)) { + LOG(ERROR) << "Fail to add RpczService"; + return -1; + } +- if (AddBuiltinService(new (std::nothrow) HotspotsService)) { ++ if (FLAGS_enable_hotspots_service && AddBuiltinService(new (std::nothrow) HotspotsService)) { + LOG(ERROR) << "Fail to add HotspotsService"; + return -1; + } +- if (AddBuiltinService(new (std::nothrow) IndexService)) { ++ if (FLAGS_enable_index_service && AddBuiltinService(new (std::nothrow) IndexService)) { + LOG(ERROR) << "Fail to add IndexService"; + return -1; + } +diff --git a/src/butil/errno.cpp b/src/butil/errno.cpp +index 9b964e114f..2e1c4d379d 100644 +--- a/src/butil/errno.cpp ++++ b/src/butil/errno.cpp +@@ -55,14 +55,19 @@ int DescribeCustomizedErrno( + #if defined(OS_MACOSX) + const int rc = strerror_r(error_code, tls_error_buf, ERROR_BUFSIZE); + if (rc != EINVAL) +-#else +- desc = strerror_r(error_code, tls_error_buf, ERROR_BUFSIZE); +- if (desc && strncmp(desc, "Unknown error", 13) != 0) +-#endif + { + fprintf(stderr, "WARNING: Fail to define %s(%d) which is already defined as `%s'", + error_name, error_code, desc); + } ++#else ++ desc = strerror_r(error_code, tls_error_buf, ERROR_BUFSIZE); ++ if (desc != tls_error_buf) ++ { ++ fprintf(stderr, ++ "%d is defined as `%s', probably is the system errno.\n", ++ error_code, desc); ++ } ++#endif + } + errno_desc[error_code - ERRNO_BEGIN] = description; + return 0; // must +diff --git a/src/bvar/default_variables.cpp b/src/bvar/default_variables.cpp +index be02c50a9a..f71f9dd7cf 100644 +--- a/src/bvar/default_variables.cpp ++++ b/src/bvar/default_variables.cpp +@@ -111,7 +111,7 @@ static bool read_proc_status(ProcStat &stat) { + } + const std::string& result = oss.str(); + if (sscanf(result.c_str(), "%d %d %d %d" +- "%d %u %ld %ld", ++ "%d %x %ld %ld", + &stat.pid, &stat.ppid, &stat.pgrp, &stat.session, + &stat.tpgid, &stat.flags, &stat.priority, &stat.nice) != 8) { + PLOG(WARNING) << "Fail to sscanf"; From 024a0d0f5cf4763f5a6a32c8bcffe231547a6f58 Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Mon, 16 Oct 2023 20:29:28 +0800 Subject: [PATCH 16/32] feat(sql): lazy last join (#3533) * feat(online): support lazy last join For SQL `A last join (B last join C)`, it'll optimize and run `B last join C` lazily. Both batch mode and request(batch-request) mode are considered. * fix: tests for `A join (B join C)` and also: - rm redundant code path in group_and_sort_optimized.cc * fix: comment * fix: lazy last join correct expr resolving in group_and_sort_optimized * fix(online): last join (where) with cluster optimized * fix(optimizer): skip cluster optimize for specific condition Skip for the case `JOIN(TABLE, ...)`. Cluster optimize only happen with `JOIN(ROW, TABLE)`. * fix(optimizer): distinct column name from different table Do not optimize target table if resolved column is from different table, even column name does be the same. * test: more cases for lazy last join * chore: rm mut_keys * fix(optimizer): KeysOptimizedImpl --- .gitignore | 7 + cases/query/last_join_query.yaml | 810 +++++++++++++++++- cases/query/last_join_where.yaml | 15 +- cases/query/last_join_window_query.yaml | 10 +- .../toydb/src/testing/toydb_engine_test.cc | 7 + hybridse/include/node/node_manager.h | 2 +- hybridse/include/node/sql_node.h | 20 +- .../include/passes/expression/expr_pass.h | 12 +- hybridse/include/vm/engine.h | 3 - hybridse/include/vm/physical_op.h | 28 +- hybridse/include/vm/schemas_context.h | 7 +- hybridse/src/node/node_manager.cc | 2 +- .../src/passes/physical/cluster_optimized.cc | 15 +- .../physical/group_and_sort_optimized.cc | 276 +++--- .../physical/group_and_sort_optimized.h | 29 +- hybridse/src/vm/engine.cc | 21 +- hybridse/src/vm/generator.cc | 4 + hybridse/src/vm/generator.h | 3 + hybridse/src/vm/internal/node_helper.cc | 42 + hybridse/src/vm/internal/node_helper.h | 5 + hybridse/src/vm/runner.cc | 93 +- hybridse/src/vm/runner.h | 22 +- hybridse/src/vm/schemas_context.cc | 24 +- hybridse/src/vm/transform.cc | 141 +-- hybridse/src/vm/transform.h | 13 +- 25 files changed, 1272 insertions(+), 339 deletions(-) create mode 100644 hybridse/src/vm/internal/node_helper.cc diff --git a/.gitignore b/.gitignore index e7e91890044..14fb8ee1485 100644 --- a/.gitignore +++ b/.gitignore @@ -108,3 +108,10 @@ allure-results/ /python/openmldb_autofe/*.egg-info/ # go sdk !go.mod + +# tag files +**/tags +**/GPATH +**/GRTAGS +**/GTAGS +**/cscope.out diff --git a/cases/query/last_join_query.yaml b/cases/query/last_join_query.yaml index e37d87a4044..2715bcf7341 100644 --- a/cases/query/last_join_query.yaml +++ b/cases/query/last_join_query.yaml @@ -12,10 +12,27 @@ # See the License for the specific language governing permissions and # limitations under the License. + #################################################################################################### + # LAST JOINs + # support modes: + # - online request (right source optimized) + # - batch request (right source optimized) + # - online preview (standalone) + # - offline mode + # unsupport: + # - online preview (in cluster) + # - online request (right source not optimized) + # - batch request (right source not optimized) + # + # Right source is optimized case: + # 1. Right source is ANYOP(T2): T2 optimized with a concret index + # 2. Right source is ANYOP(JOIN(T2, T3)): both T2 and T3 optimized with concret indexs + #################################################################################################### + cases: - id: 0 desc: LAST JOIN 右表未命中索引 - mode: rtidb-unsupport + mode: request-unsupport sql: | SELECT t1.col1 as id, t1.col0 as t1_col0, t1.col1 + t2.col1 + 1 as test_col1, t1.col2 as t1_col2, str1 FROM t1 last join t2 order by t2.col5 on t1.col1=t2.col1 and t1.col5 = t2.col5; @@ -178,6 +195,19 @@ cases: Z, 3, 3 U, 4, 4 V, 5, 5 + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.col1 -> id, t1.col0, t2.c0, t3.column0)) + REQUEST_JOIN(type=kJoinTypeConcat) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(#5)) + SIMPLE_PROJECT(sources=(#5 -> t1.col1)) + DATA_PROVIDER(request=t1) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(#5)) + SIMPLE_PROJECT(sources=(#5 -> t1.col1)) + DATA_PROVIDER(request=t1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) expect: schema: id:int32, col0:string, c0:string, column0:string order: id @@ -335,8 +365,6 @@ cases: 5, 2, 1590115423900 - id: 10 - desc: 右表没有匹配[FEX-903] - mode: offline-unsupport inputs: - name: t1 columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] @@ -361,3 +389,779 @@ cases: - ["aa",2,13,1590738989000] - ["bb",21,131,1590738990000] - ["cc",41,null,null] + + #################################################################################################### + # LAZY LAST JOINs + #################################################################################################### + - id: 11 + # t1------>(t2------->t3) + # │ └-(t3.c1)-┘ + # └-(t2.c1)-┘ + # Easiest path, t1 finally joins t2's column + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r + from t1 last join ( + select t2.*, t3.c1 as c1r, t3.c2 as c2r + from t2 last join t3 on t2.c1 = t3.c1 + ) tx + on t1.c1 = tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + data: | + aa, 2, aa, aa, 2 + bb, 3, bb, NULL, NULL + cc, 4, NULL, NULL, NULL + - id: 12 + # t1------>(t2------->t3) + # │ └-(t3.c1)-┘ + # └--(t2.c1)----------┘ + desc: unsupport join on t3 in request and batch(clusterd) + mode: request-unsupport + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1x string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1x:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r + from t1 last join ( + select t2.*, t3.c1x as c1r, t3.c2 as c2r + from t2 last join t3 on t2.c1 = t3.c1x + ) tx + on t1.c1 = tx.c1r + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + JOIN(type=LastJoin, condition=, left_keys=(t1.c1), right_keys=(tx.c1r), index_keys=) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1x -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(table=t2) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + data: | + aa, 2, aa, aa, 2 + bb, 3, NULL, NULL, NULL + cc, 4, NULL, NULL, NULL + - id: 13 + # t1------>(t2------->t3) + # │ └-(t3.c1)-┘ + # └-(t2.c1)-----------┘ + desc: t2 un-optimized, t2 & t3 has the same schema + # the case checks if optimizer can distinct same column name from two tables + mode: request-unsupport + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r + from t1 last join ( + select t2.*, t3.c1 as c1r, t3.c2 as c2r + from t2 last join t3 on t2.c1 = t3.c1 + ) tx + on t1.c1 = tx.c1r + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + JOIN(type=LastJoin, condition=, left_keys=(t1.c1), right_keys=(tx.c1r), index_keys=) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(table=t2) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + data: | + aa, 2, aa, aa, 2 + bb, 3, NULL, NULL, NULL + cc, 4, NULL, NULL, NULL + - id: 14 + # t1------>(t2------->t3) + # │ └-(t3.c1)-┘ + # └-(t2.c1)-┘ + desc: t2 un-optimized due to no equal expr + mode: request-unsupport + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r + from t1 last join ( + select t2.*, t3.c1 as c1r, t3.c2 as c2r + from t2 last join t3 on t2.c1 = t3.c1 + ) tx + on t1.c1 != tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + JOIN(type=LastJoin, condition=t1.c1 != tx.c1, left_keys=, right_keys=, index_keys=) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(table=t2) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + data: | + aa, 2, dd, dd, 41 + bb, 3, dd, dd, 41 + cc, 4, dd, dd, 41 + - id: 15 + # t1------>(t2------->t3) + # │ └-(t3.c1)-┘ + # └-(t2.c1)-┘ + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r + from t1 last join ( + select t2.*, t3.c1 as c1r, t3.c2 as c2r + from t2 last join t3 on t2.c1 = t3.c1 + ) tx + order by tx.c4 + on t1.c1 = tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + REQUEST_JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + data: | + aa, 2, aa, aa, 2 + bb, 3, bb, NULL, NULL + cc, 4, NULL, NULL, NULL + - id: 16 + # t1------>(t2------->t3) + # │ └-(t3.c1)-┘ + # └-(t2.c1)-┘ + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r + from t1 last join ( + select t2.c1, t2.c4 as c4l, t3.c1 as c1r, t3.c2 as c2r + from t2 last join t3 on t2.c1 = t3.c1 + ) tx + order by tx.c4l + on t1.c1 = tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + REQUEST_JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r)) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + data: | + aa, 2, aa, aa, 2 + bb, 3, bb, NULL, NULL + cc, 4, NULL, NULL, NULL + - id: 17 + # t1------>(t2------->(t3-------t4) + # │ │ └-(t4.c1)-┘ + # │ └-(t3.c1)--┘ + # └-(t2.c1)-┘ + desc: multiple lazy last join + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + - name: t4 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["bb",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r, c1rr + from t1 last join ( + select t2.c1, t2.c4 as c4l, t3.c1 as c1r, t3.c2 as c2r, t3.c1rr + from t2 last join ( + select t3.*, t4.c1 as c1rr + from t3 last join t4 + on t3.c1 = t4.c1 + ) t3 + on t2.c1 = t3.c1 + ) tx + order by tx.c4l + on t1.c1 = tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t3.c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + RENAME(name=t3) + SIMPLE_PROJECT(sources=(t3.c1, t3.c2, t3.c3, t3.c4, t4.c1 -> c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t3.c1)) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + REQUEST_JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t3.c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + RENAME(name=t3) + SIMPLE_PROJECT(sources=(t3.c1, t3.c2, t3.c3, t3.c4, t4.c1 -> c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t3.c1)) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t3.c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + RENAME(name=t3) + SIMPLE_PROJECT(sources=(t3.c1, t3.c2, t3.c3, t3.c4, t4.c1 -> c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t3.c1)) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + - c1rr string + data: | + aa, 2, aa, aa, 2, aa + bb, 3, bb, NULL, NULL, NULL + cc, 4, NULL, NULL, NULL, NULL + - id: 18 + # t1------>(t2------->(t3-------t4) + # │ │ └-(t4.c1)-┘ + # │ └-(t3.c1)--┘ + # └-(t2.c1)-┘ + mode: request-unsupport + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["bb",21,131,1590738990000] + - ["dd",41,151,1590738991000] + - name: t4 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r, c1rr + from t1 last join ( + select t2.c1, t2.c4 as c4l, t3.c1 as c1r, t3.c2 as c2r, t3.c1rr + from t2 last join ( + select t3.*, t4.c1 as c1rr + from t3 last join t4 + on t3.c1 = t4.c1 + ) t3 + on t2.c1 = t3.c1rr + ) tx + order by tx.c4l + on t1.c1 = tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + JOIN(type=LastJoin, right_sort=(ASC), condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t3.c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(t2.c1), right_keys=(t3.c1rr), index_keys=) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + RENAME(name=t3) + SIMPLE_PROJECT(sources=(t3.c1, t3.c2, t3.c3, t3.c4, t4.c1 -> c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t3.c1)) + DATA_PROVIDER(table=t3) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + - c1rr string + data: | + aa, 2, aa, aa, 2, aa + bb, 3, bb, NULL, NULL, NULL + cc, 4, NULL, NULL, NULL, NULL + - id: 19 + # t1------>(t2------->(t3-------t4) + # │ └-(t3.c1)--┘ │ + # │ └--(t4.c1)------┘ + # └-(t2.c1)-┘ + desc: nested last join + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + - name: t4 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["bb",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r, c1rr + from t1 last join ( + select t2.c1, t2.c4 as c4l, t3.c1 as c1r, t3.c2 as c2r, t4.c1 as c1rr + from t2 last join t3 + on t2.c1 = t3.c1 + last join t4 + on t2.c1 = t4.c1 + ) tx + on t1.c1 = tx.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t4.c1 -> c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t4.c1 -> c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, c1rr)) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r, t4.c1 -> c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + - c1rr string + data: | + aa, 2, aa, aa, 2, aa + bb, 3, bb, NULL, NULL, bb + cc, 4, NULL, NULL, NULL, NULL + - id: 20 + # t1------>(t2------->(t3-------t4) + # │ └-(t3.c1)--┘ │ + # └-(t2.c1)----┘ │ + # └-------------------------┘ + desc: nested last join + inputs: + - name: t1 + columns: ["c1 string","c2 int","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,1590738989000] + - ["bb",3,1590738990000] + - ["cc",4,1590738991000] + - name: t2 + columns: ["c1 string","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",1590738989000] + - ["bb",1590738990000] + - ["dd",1590738991000] + - name: t3 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + - name: t4 + columns: ["c1 string","c2 int","c3 bigint","c4 timestamp"] + indexs: ["index1:c1:c4"] + rows: + - ["aa",2,13,1590738989000] + - ["cc",21,131,1590738990000] + - ["dd",41,151,1590738991000] + sql: | + select t1.c1, t1.c2, tx.c1 as c1l, c1r, c2r, t4.c1 as c1rr + from t1 last join ( + select t2.c1, t2.c4 as c4l, t3.c1 as c1r, t3.c2 as c2r + from t2 last join t3 + on t2.c1 = t3.c1 + ) tx + on t1.c1 = tx.c1 + last join t4 + on tx.c1 = t4.c1 + batch_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, t4.c1 -> c1rr)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(tx.c1)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(table=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, t4.c1 -> c1rr)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(tx.c1)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, tx.c1 -> c1l, c1r, c2r, t4.c1 -> c1rr)) + REQUEST_JOIN(type=kJoinTypeConcat) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(#123)) + SIMPLE_PROJECT(sources=(#123 -> tx.c1)) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(#4)) + SIMPLE_PROJECT(sources=(#4 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=tx) + SIMPLE_PROJECT(sources=(t2.c1, t2.c4 -> c4l, t3.c1 -> c1r, t3.c2 -> c2r)) + REQUEST_JOIN(type=LastJoin, condition=, left_keys=(), right_keys=(), index_keys=(t2.c1)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) + DATA_PROVIDER(type=Partition, table=t3, index=index1) + DATA_PROVIDER(type=Partition, table=t4, index=index1) + expect: + order: c1 + columns: + - c1 string + - c2 int + - c1l string + - c1r string + - c2r int + - c1rr string + data: | + aa, 2, aa, aa, 2, aa + bb, 3, bb, NULL, NULL, NULL + cc, 4, NULL, NULL, NULL, NULL diff --git a/cases/query/last_join_where.yaml b/cases/query/last_join_where.yaml index 6a341d001d8..110debcfcdf 100644 --- a/cases/query/last_join_where.yaml +++ b/cases/query/last_join_where.yaml @@ -8,7 +8,6 @@ cases: - id: 0 desc: LASTJOIN(FILTER) deployable: true - mode: batch-request-unsupport sql: | SELECT t1.c1, @@ -38,6 +37,16 @@ cases: RENAME(name=t2) FILTER_BY(condition=, left_keys=(), right_keys=(), index_keys=(aa)) DATA_PROVIDER(type=Partition, table=t2, index=index1) + cluster_request_plan: | + SIMPLE_PROJECT(sources=(t1.c1, t1.c2, t2.c1 -> c21)) + REQUEST_JOIN(type=kJoinTypeConcat) + DATA_PROVIDER(request=t1) + REQUEST_JOIN(OUTPUT_RIGHT_ONLY, type=LastJoin, condition=, left_keys=(#5), right_keys=(#9), index_keys=) + SIMPLE_PROJECT(sources=(#5 -> t1.c1)) + DATA_PROVIDER(request=t1) + RENAME(name=t2) + FILTER_BY(condition=, left_keys=(), right_keys=(), index_keys=(aa)) + DATA_PROVIDER(type=Partition, table=t2, index=index1) expect: columns: - c1 string @@ -51,7 +60,6 @@ cases: - id: 1 desc: LASTJOIN(SimpleOPS(FILTER)) - mode: batch-request-unsupport deployable: true sql: | SELECT @@ -140,7 +148,6 @@ cases: - id: 3 desc: LASTJOIN(FILTER) - mode: batch-request-unsupport deployable: true sql: | SELECT @@ -232,7 +239,6 @@ cases: LASTJOIN(SimpleOps(FILTER)), different index with join, fine to online if there is no order by of last join deployable: true - mode: batch-request-unsupport sql: | SELECT t1.c1, @@ -322,7 +328,6 @@ cases: - id: 7 desc: LASTJOIN(SimpleOps(FILTER)) hit same index with order by - mode: batch-request-unsupport deployable: true sql: | SELECT diff --git a/cases/query/last_join_window_query.yaml b/cases/query/last_join_window_query.yaml index 96467eaf787..a11fce4369f 100644 --- a/cases/query/last_join_window_query.yaml +++ b/cases/query/last_join_window_query.yaml @@ -321,11 +321,11 @@ cases: min(c3r) OVER w1 as sumb, from ( select - {0}.c3 as c3l, - {0}.id as idx, - {1}.c3 as c3r, - {0}.c1 as c1a, - {0}.c7 as c7a + t0.c3 as c3l, + t0.id as idx, + t1.c3 as c3r, + t0.c1 as c1a, + t0.c7 as c7a from t0 last join t1 on t0.c1=t1.c1 ) WINDOW w1 AS ( diff --git a/hybridse/examples/toydb/src/testing/toydb_engine_test.cc b/hybridse/examples/toydb/src/testing/toydb_engine_test.cc index a4cd2b095d8..02438aeebac 100644 --- a/hybridse/examples/toydb/src/testing/toydb_engine_test.cc +++ b/hybridse/examples/toydb/src/testing/toydb_engine_test.cc @@ -91,6 +91,13 @@ TEST_P(EngineTest, TestClusterBatchRequestEngine) { } } +// ====================================================== / +// BatchRequestEngineTest +// test batch request mode only, with yaml: +// - case/function/test_batch_request.yaml +// +// TODO(ace): merge to EngineTest above simply +// ====================================================== / TEST_P(BatchRequestEngineTest, TestBatchRequestEngine) { auto& sql_case = GetParam(); LOG(INFO) << "ID: " << sql_case.id() << ", DESC: " << sql_case.desc(); diff --git a/hybridse/include/node/node_manager.h b/hybridse/include/node/node_manager.h index 2dcd013e36f..ab87e588a53 100644 --- a/hybridse/include/node/node_manager.h +++ b/hybridse/include/node/node_manager.h @@ -151,7 +151,7 @@ class NodeManager { WindowDefNode *MergeWindow(const WindowDefNode *w1, const WindowDefNode *w2); OrderExpression* MakeOrderExpression(const ExprNode* expr, const bool is_asc); - OrderByNode *MakeOrderByNode(const ExprListNode *order_expressions); + OrderByNode *MakeOrderByNode(ExprListNode *order_expressions); FrameExtent *MakeFrameExtent(SqlNode *start, SqlNode *end); SqlNode *MakeFrameBound(BoundType bound_type); SqlNode *MakeFrameBound(BoundType bound_type, ExprNode *offset); diff --git a/hybridse/include/node/sql_node.h b/hybridse/include/node/sql_node.h index 6118c164193..bbdfc83313f 100644 --- a/hybridse/include/node/sql_node.h +++ b/hybridse/include/node/sql_node.h @@ -476,9 +476,10 @@ class ExprNode : public SqlNode { virtual bool IsListReturn(ExprAnalysisContext *ctx) const { return false; } /** - * Default expression node deep copy implementation + * Returns new ExprNode with all of fields copyed, excepting descendants ExprNodes. */ virtual ExprNode *ShadowCopy(NodeManager *) const = 0; + ExprNode *DeepCopy(NodeManager *) const override; // Get the compatible type that lhs and rhs can both casted into @@ -581,8 +582,13 @@ class FnNodeList : public FnNode { }; class OrderExpression : public ExprNode { public: + // expr maybe null OrderExpression(const ExprNode *expr, const bool is_asc) - : ExprNode(kExprOrderExpression), expr_(expr), is_asc_(is_asc) {} + : ExprNode(kExprOrderExpression), expr_(expr), is_asc_(is_asc) { + if (expr != nullptr) { + AddChild(const_cast(expr)); + } + } ~OrderExpression() {} void Print(std::ostream &output, const std::string &org_tab) const; const std::string GetExprString() const; @@ -597,8 +603,10 @@ class OrderExpression : public ExprNode { }; class OrderByNode : public ExprNode { public: - explicit OrderByNode(const ExprListNode *order_expressions) - : ExprNode(kExprOrder), order_expressions_(order_expressions) {} + explicit OrderByNode(ExprListNode *order_expressions) + : ExprNode(kExprOrder), order_expressions_(order_expressions) { + AddChild(order_expressions); + } ~OrderByNode() {} void Print(std::ostream &output, const std::string &org_tab) const; @@ -623,7 +631,7 @@ class OrderByNode : public ExprNode { return order_expression->expr(); } bool is_asc() const { return false; } - const ExprListNode *order_expressions_; + ExprListNode *order_expressions_; }; class TableRefNode : public SqlNode { public: @@ -1648,7 +1656,7 @@ class ColumnRefNode : public ExprNode { static ColumnRefNode *CastFrom(ExprNode *node); void Print(std::ostream &output, const std::string &org_tab) const; - const std::string GetExprString() const; + const std::string GetExprString() const override; const std::string GenerateExpressionName() const; virtual bool Equals(const ExprNode *node) const; ColumnRefNode *ShadowCopy(NodeManager *) const override; diff --git a/hybridse/include/passes/expression/expr_pass.h b/hybridse/include/passes/expression/expr_pass.h index 1c41307c28a..c88b7ee8585 100644 --- a/hybridse/include/passes/expression/expr_pass.h +++ b/hybridse/include/passes/expression/expr_pass.h @@ -65,15 +65,15 @@ class ExprReplacer { void AddReplacement(const node::ExprIdNode* arg, node::ExprNode* repl); void AddReplacement(const node::ExprNode* expr, node::ExprNode* repl); void AddReplacement(size_t column_id, node::ExprNode* repl); - void AddReplacement(const std::string& relation_name, - const std::string& column_name, node::ExprNode* repl); + void AddReplacement(const std::string& relation_name, const std::string& column_name, node::ExprNode* repl); - hybridse::base::Status Replace(node::ExprNode* root, - node::ExprNode** output) const; + // For the given `ExprNode` tree, do the in-place replacements specified by `AddReplacement` calls. + // Returns new ExprNode if `root` is ExprIdNode/ColumnIdNode/ColumnRefNode, `root` with its descendants replaced + // otherwise + hybridse::base::Status Replace(node::ExprNode* root, node::ExprNode** output) const; private: - hybridse::base::Status DoReplace(node::ExprNode* root, - std::unordered_set* visited, + hybridse::base::Status DoReplace(node::ExprNode* root, std::unordered_set* visited, node::ExprNode** output) const; std::unordered_map arg_id_map_; diff --git a/hybridse/include/vm/engine.h b/hybridse/include/vm/engine.h index 3cb7564be98..e552e5889c6 100644 --- a/hybridse/include/vm/engine.h +++ b/hybridse/include/vm/engine.h @@ -420,9 +420,6 @@ class Engine { EngineOptions GetEngineOptions(); private: - // Get all dependent (db, table) info from physical plan - Status GetDependentTables(const PhysicalOpNode*, std::set>*); - std::shared_ptr GetCacheLocked(const std::string& db, const std::string& sql, EngineMode engine_mode); diff --git a/hybridse/include/vm/physical_op.h b/hybridse/include/vm/physical_op.h index c884d0bb7e5..ee3634615c8 100644 --- a/hybridse/include/vm/physical_op.h +++ b/hybridse/include/vm/physical_op.h @@ -155,8 +155,10 @@ class Sort : public FnComponent { public: explicit Sort(const node::OrderByNode *orders) : orders_(orders) {} virtual ~Sort() {} + const node::OrderByNode *orders() const { return orders_; } void set_orders(const node::OrderByNode *orders) { orders_ = orders; } + const bool is_asc() const { const node::OrderExpression *first_order_expression = nullptr == orders_ ? nullptr : orders_->GetOrderExpression(0); @@ -172,18 +174,11 @@ class Sort : public FnComponent { return "sort = " + fn_info_.fn_name(); } - void ResolvedRelatedColumns( - std::vector *columns) const { + void ResolvedRelatedColumns(std::vector *columns) const { if (nullptr == orders_) { return; } - auto expr = orders_->GetOrderExpressionExpr(0); - if (nullptr != expr) { - node::ExprListNode exprs; - exprs.AddChild(const_cast(expr)); - node::ColumnOfExpression(orders_->order_expressions_, columns); - } - return; + node::ColumnOfExpression(orders_->order_expressions_, columns); } base::Status ReplaceExpr(const passes::ExprReplacer &replacer, @@ -286,8 +281,10 @@ class Key : public FnComponent { return oss.str(); } const bool ValidKey() const { return !node::ExprListNullOrEmpty(keys_); } + const node::ExprListNode *keys() const { return keys_; } void set_keys(const node::ExprListNode *keys) { keys_ = keys; } + const node::ExprListNode *PhysicalProjectNode() const { return keys_; } const std::string FnDetail() const { return "keys=" + fn_info_.fn_name(); } @@ -555,8 +552,7 @@ class PhysicalDataProviderNode : public PhysicalOpNode { class PhysicalTableProviderNode : public PhysicalDataProviderNode { public: - explicit PhysicalTableProviderNode( - const std::shared_ptr &table_handler) + explicit PhysicalTableProviderNode(const std::shared_ptr &table_handler) : PhysicalDataProviderNode(table_handler, kProviderTypeTable) {} base::Status WithNewChildren(node::NodeManager *nm, @@ -1287,7 +1283,7 @@ class PhysicalRequestJoinNode : public PhysicalBinaryNode { join_(join_type), joined_schemas_ctx_(this), output_right_only_(false) { - output_type_ = kSchemaTypeRow; + output_type_ = left->GetOutputType(); RegisterFunctionInfo(); } PhysicalRequestJoinNode(PhysicalOpNode *left, PhysicalOpNode *right, @@ -1298,7 +1294,7 @@ class PhysicalRequestJoinNode : public PhysicalBinaryNode { join_(join_type, orders, condition), joined_schemas_ctx_(this), output_right_only_(false) { - output_type_ = kSchemaTypeRow; + output_type_ = left->GetOutputType(); RegisterFunctionInfo(); } PhysicalRequestJoinNode(PhysicalOpNode *left, PhysicalOpNode *right, @@ -1307,7 +1303,7 @@ class PhysicalRequestJoinNode : public PhysicalBinaryNode { join_(join), joined_schemas_ctx_(this), output_right_only_(output_right_only) { - output_type_ = kSchemaTypeRow; + output_type_ = left->GetOutputType(); RegisterFunctionInfo(); } @@ -1321,7 +1317,7 @@ class PhysicalRequestJoinNode : public PhysicalBinaryNode { join_(join_type, condition, left_keys, right_keys), joined_schemas_ctx_(this), output_right_only_(false) { - output_type_ = kSchemaTypeRow; + output_type_ = left->GetOutputType(); RegisterFunctionInfo(); } PhysicalRequestJoinNode(PhysicalOpNode *left, PhysicalOpNode *right, @@ -1334,7 +1330,7 @@ class PhysicalRequestJoinNode : public PhysicalBinaryNode { join_(join_type, orders, condition, left_keys, right_keys), joined_schemas_ctx_(this), output_right_only_(false) { - output_type_ = kSchemaTypeRow; + output_type_ = left->GetOutputType(); RegisterFunctionInfo(); } diff --git a/hybridse/include/vm/schemas_context.h b/hybridse/include/vm/schemas_context.h index 1541c64201d..b2e68d9477a 100644 --- a/hybridse/include/vm/schemas_context.h +++ b/hybridse/include/vm/schemas_context.h @@ -72,7 +72,8 @@ class SchemaSource { // column identifier of each output column std::vector column_ids_; - // trace which child and which column id each column come from + // trace which child and which column id each column comes from, index is measured + // based on the physical node tree, starts from 0. // -1 means the column is created from current node std::vector source_child_idxs_; std::vector source_child_column_ids_; @@ -127,10 +128,6 @@ class SchemasContext { base::Status ResolveColumnRefIndex(const node::ColumnRefNode* column_ref, size_t* schema_idx, size_t* col_idx) const; - /** - * Resolve column id with given column expression [ColumnRefNode, ColumnId] - */ - base::Status ResolveColumnID(const node::ExprNode* column, size_t* column_id) const; /** * Given relation name and column name, return column unique id diff --git a/hybridse/src/node/node_manager.cc b/hybridse/src/node/node_manager.cc index 3c5b8ffd36a..8f6f80d7517 100644 --- a/hybridse/src/node/node_manager.cc +++ b/hybridse/src/node/node_manager.cc @@ -301,7 +301,7 @@ OrderExpression *NodeManager::MakeOrderExpression(const ExprNode *expr, const bo OrderExpression *node_ptr = new OrderExpression(expr, is_asc); return RegisterNode(node_ptr); } -OrderByNode *NodeManager::MakeOrderByNode(const ExprListNode *order_expressions) { +OrderByNode *NodeManager::MakeOrderByNode(ExprListNode *order_expressions) { OrderByNode *node_ptr = new OrderByNode(order_expressions); return RegisterNode(node_ptr); } diff --git a/hybridse/src/passes/physical/cluster_optimized.cc b/hybridse/src/passes/physical/cluster_optimized.cc index d17928742dc..ae53f588930 100644 --- a/hybridse/src/passes/physical/cluster_optimized.cc +++ b/hybridse/src/passes/physical/cluster_optimized.cc @@ -41,7 +41,7 @@ bool ClusterOptimized::SimplifyJoinLeftInput( for (auto column : columns) { oss << node::ExprString(column) << ","; } - LOG(INFO) << "join resolved related columns: \n" << oss.str(); + LOG(INFO) << "join resolved related columns: " << oss.str(); // find columns belong to left side std::vector left_indices; @@ -116,7 +116,7 @@ bool ClusterOptimized::SimplifyJoinLeftInput( << status; return false; } - DLOG(INFO) << "apply root node simplify!"; + DLOG(INFO) << "apply root node simplify: " << root_simplify_project_op->GetTreeString(); *output = root_simplify_project_op; return true; } @@ -134,10 +134,13 @@ bool ClusterOptimized::Transform(PhysicalOpNode* in, PhysicalOpNode** output) { case node::kJoinTypeLast: { auto left = join_op->producers()[0]; auto right = join_op->producers()[1]; - if (vm::PhysicalSchemaType::kSchemaTypeRow == - right->GetOutputType()) { - DLOG(INFO) - << "request join optimized skip: row and row join"; + if (vm::PhysicalSchemaType::kSchemaTypeRow != left->GetOutputType()) { + DLOG(INFO) << "request join optimized skip: left source is not a row"; + return false; + } + + if (vm::PhysicalSchemaType::kSchemaTypeRow == right->GetOutputType()) { + DLOG(INFO) << "request join optimized skip: row and row join"; return false; } auto simplify_left = left; diff --git a/hybridse/src/passes/physical/group_and_sort_optimized.cc b/hybridse/src/passes/physical/group_and_sort_optimized.cc index 287919d9406..ae333b6af47 100644 --- a/hybridse/src/passes/physical/group_and_sort_optimized.cc +++ b/hybridse/src/passes/physical/group_and_sort_optimized.cc @@ -15,15 +15,15 @@ */ #include "passes/physical/group_and_sort_optimized.h" -#include #include #include -#include #include #include #include #include +#include "absl/cleanup/cleanup.h" +#include "absl/status/status.h" #include "absl/strings/string_view.h" #include "vm/physical_op.h" @@ -47,9 +47,47 @@ using hybridse::vm::PhysicalSimpleProjectNode; using hybridse::vm::PhysicalWindowAggrerationNode; using hybridse::vm::ProjectType; -static bool ResolveColumnToSourceColumnName(const node::ColumnRefNode* col, - const SchemasContext* schemas_ctx, - std::string* source_name); +static bool ResolveColumnToSourceColumnName(const node::ColumnRefNode* col, const SchemasContext* schemas_ctx, + std::string* db, std::string* table, std::string* source_col); + +// ExprNode may be resolving under different SchemasContext later (say one of its descendants context), +// with column name etc it may not able to resvole since a column rename may happen in SimpleProject node. +// With the column id hint written to corresponding ColumnRefNode earlier, resolving issue can be mitigated. +absl::Status GroupAndSortOptimized::BuildExprCache(const node::ExprNode* node, const SchemasContext* sc) { + if (node == nullptr) { + return {}; + } + + switch (node->GetExprType()) { + case node::kExprColumnRef: { + auto ref = dynamic_cast(node); + + if (expr_cache_.find(ref) != expr_cache_.end()) { + break; + } + + std::string source_col; + std::string source_db; + std::string source_table; + if (!ResolveColumnToSourceColumnName(ref, sc, &source_db, &source_table, &source_col)) { + return absl::InternalError(absl::StrCat("unable to resolve ", ref->GetExprString())); + } + + expr_cache_.emplace(ref, SrcColInfo{source_col, source_table, source_db}); + break; + } + default: + break; + } + + for (uint32_t i = 0; i < node->GetChildNum(); ++i) { + auto s = BuildExprCache(node->GetChild(i), sc); + if (!s.ok()) { + return s; + } + } + return {}; +} bool GroupAndSortOptimized::Transform(PhysicalOpNode* in, PhysicalOpNode** output) { @@ -239,6 +277,48 @@ bool GroupAndSortOptimized::Transform(PhysicalOpNode* in, return false; } +bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx, + PhysicalOpNode* in, + Key* left_key, + Key* index_key, + Key* right_key, + Sort* sort, + PhysicalOpNode** new_in) { + if (nullptr == left_key || nullptr == index_key || !left_key->ValidKey()) { + return false; + } + + if (right_key != nullptr && !right_key->ValidKey()) { + return false; + } + + absl::Cleanup clean = [&]() { + expr_cache_.clear(); + }; + + auto s = BuildExprCache(left_key->keys(), root_schemas_ctx); + if (!s.ok()) { + return false; + } + s = BuildExprCache(index_key->keys(), root_schemas_ctx); + if (!s.ok()) { + return false; + } + if (right_key != nullptr) { + s = BuildExprCache(right_key->keys(), root_schemas_ctx); + if (!s.ok()) { + return false; + } + } + if (sort != nullptr) { + s = BuildExprCache(sort->orders(), root_schemas_ctx); + if (!s.ok()) { + return false; + } + } + return KeysOptimizedImpl(root_schemas_ctx, in, left_key, index_key, right_key, sort, new_in); +} + /** * optimize keys on condition. Remove keys from upper node if key match indexes * defined in table schema `left_key` & `index_key` is required, `right_key` is @@ -249,7 +329,7 @@ bool GroupAndSortOptimized::Transform(PhysicalOpNode* in, * otherwise: * - `left_key`, `index_key` corresponding to Key group & Key hash */ -bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx, +bool GroupAndSortOptimized::KeysOptimizedImpl(const SchemasContext* root_schemas_ctx, PhysicalOpNode* in, Key* left_key, Key* index_key, @@ -258,15 +338,6 @@ bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx PhysicalOpNode** new_in) { TransformCxtGuard guard(&ctx_, KeysInfo(in->GetOpType(), left_key, right_key, index_key, sort)); - if (nullptr == left_key || nullptr == index_key || !left_key->ValidKey()) { - return false; - } - - if (right_key != nullptr && !right_key->ValidKey()) { - return false; - } - - if (PhysicalOpType::kPhysicalOpDataProvider == in->GetOpType()) { auto scan_op = dynamic_cast(in); // Do not optimize with Request DataProvider (no index has been provided) @@ -386,12 +457,13 @@ bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx return true; } } else if (PhysicalOpType::kPhysicalOpSimpleProject == in->GetOpType()) { - auto simple_project = dynamic_cast(in); PhysicalOpNode* new_depend; - if (!KeysOptimized(root_schemas_ctx, simple_project->producers()[0], - left_key, index_key, right_key, sort, &new_depend)) { + if (!KeysOptimizedImpl(in->GetProducer(0)->schemas_ctx(), in->GetProducer(0), left_key, index_key, right_key, sort, + &new_depend)) { return false; } + + auto simple_project = dynamic_cast(in); PhysicalSimpleProjectNode* new_simple_op = nullptr; Status status = plan_ctx_->CreateOp(&new_simple_op, new_depend, simple_project->project()); @@ -403,7 +475,7 @@ bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx return true; } else if (PhysicalOpType::kPhysicalOpRename == in->GetOpType()) { PhysicalOpNode* new_depend; - if (!KeysOptimized(root_schemas_ctx, in->producers()[0], left_key, + if (!KeysOptimizedImpl(in->GetProducer(0)->schemas_ctx(), in->producers()[0], left_key, index_key, right_key, sort, &new_depend)) { return false; } @@ -421,7 +493,7 @@ bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx PhysicalFilterNode* filter_op = dynamic_cast(in); PhysicalOpNode* new_depend; - if (!KeysOptimized(root_schemas_ctx, in->producers()[0], left_key, index_key, right_key, sort, &new_depend)) { + if (!KeysOptimizedImpl(root_schemas_ctx, in->producers()[0], left_key, index_key, right_key, sort, &new_depend)) { return false; } PhysicalFilterNode* new_filter = nullptr; @@ -438,19 +510,39 @@ bool GroupAndSortOptimized::KeysOptimized(const SchemasContext* root_schemas_ctx // try optimze left source of request join with window definition // window partition by and order by columns must refer to the left most table only PhysicalOpNode* new_depend = nullptr; - if (!KeysOptimized(request_join->GetProducer(0)->schemas_ctx(), request_join->GetProducer(0), left_key, - index_key, right_key, sort, &new_depend)) { + auto* rebase_sc = in->GetProducer(0)->schemas_ctx(); + if (!KeysOptimizedImpl(rebase_sc, in->GetProducer(0), left_key, index_key, right_key, sort, + &new_depend)) { return false; } PhysicalRequestJoinNode* new_join = nullptr; auto s = plan_ctx_->CreateOp(&new_join, new_depend, request_join->GetProducer(1), - request_join->join(), - request_join->output_right_only()); + request_join->join(), request_join->output_right_only()); if (!s.isOK()) { LOG(WARNING) << "Fail to create new request join op: " << s; return false; } + *new_in = new_join; + return true; + } else if (PhysicalOpType::kPhysicalOpJoin == in->GetOpType()) { + auto* join = dynamic_cast(in); + // try optimze left source of request join with window definition + // window partition by and order by columns must refer to the left most table only + PhysicalOpNode* new_depend = nullptr; + auto* rebase_sc = in->GetProducer(0)->schemas_ctx(); + if (!KeysOptimizedImpl(rebase_sc, in->GetProducer(0), left_key, index_key, right_key, sort, + &new_depend)) { + return false; + } + PhysicalJoinNode* new_join = nullptr; + auto s = plan_ctx_->CreateOp(&new_join, new_depend, join->GetProducer(1), + join->join(), join->output_right_only()); + if (!s.isOK()) { + LOG(WARNING) << "Fail to create new join op: " << s; + return false; + } + *new_in = new_join; return true; } @@ -522,39 +614,6 @@ bool GroupAndSortOptimized::KeyAndOrderOptimized( sort, new_in); } -bool GroupAndSortOptimized::SortOptimized( - const SchemasContext* root_schemas_ctx, PhysicalOpNode* in, Sort* sort) { - if (nullptr == sort) { - return false; - } - if (PhysicalOpType::kPhysicalOpDataProvider == in->GetOpType()) { - auto scan_op = dynamic_cast(in); - if (DataProviderType::kProviderTypePartition != - scan_op->provider_type_) { - return false; - } - auto partition_provider = - dynamic_cast(scan_op); - const node::OrderByNode* new_orders = nullptr; - - auto& index_hint = partition_provider->table_handler_->GetIndex(); - std::string index_name = partition_provider->index_name_; - auto index_st = index_hint.at(index_name); - TransformOrderExpr(root_schemas_ctx, sort->orders(), - *(scan_op->table_handler_->GetSchema()), index_st, - &new_orders); - sort->set_orders(new_orders); - return true; - } else if (PhysicalOpType::kPhysicalOpSimpleProject == in->GetOpType()) { - auto simple_project = dynamic_cast(in); - return SortOptimized(root_schemas_ctx, simple_project->producers()[0], - sort); - } else if (PhysicalOpType::kPhysicalOpRename == in->GetOpType()) { - return SortOptimized(root_schemas_ctx, in->producers()[0], sort); - } - return false; -} - bool GroupAndSortOptimized::TransformKeysAndOrderExpr(const SchemasContext* root_schemas_ctx, const node::ExprListNode* groups, const node::OrderByNode* order, @@ -582,13 +641,18 @@ bool GroupAndSortOptimized::TransformKeysAndOrderExpr(const SchemasContext* root switch (group->expr_type_) { case node::kExprColumnRef: { auto column = dynamic_cast(group); - std::string source_column_name; - if (!ResolveColumnToSourceColumnName(column, root_schemas_ctx, &source_column_name)) { + auto op = expr_cache_.find(column); + if (op == expr_cache_.end()) { + return false; + } + + if (table_handler->GetName() != op->second.tb_name || + table_handler->GetDatabase() != op->second.db_name) { return false; } result_bitmap_mapping[columns.size()] = i; - columns.push_back(source_column_name); + columns.emplace_back(op->second.col_name); break; } default: { @@ -602,11 +666,17 @@ bool GroupAndSortOptimized::TransformKeysAndOrderExpr(const SchemasContext* root auto expr = order->GetOrderExpressionExpr(i); if (nullptr != expr && expr->GetExprType() == node::kExprColumnRef) { auto column = dynamic_cast(expr); - std::string source_column_name; - if (!ResolveColumnToSourceColumnName(column, root_schemas_ctx, &source_column_name)) { + auto op = expr_cache_.find(column); + if (op == expr_cache_.end()) { return false; } - order_columns.push_back(source_column_name); + + if (table_handler->GetName() != op->second.tb_name || + table_handler->GetDatabase() != op->second.db_name) { + return false; + } + + order_columns.emplace_back(op->second.col_name); } } } @@ -754,75 +824,21 @@ bool GroupAndSortOptimized::MatchBestIndex(const std::vector& colum return succ; } -bool GroupAndSortOptimized::TransformOrderExpr( - const SchemasContext* schemas_ctx, const node::OrderByNode* order, - const Schema& schema, const IndexSt& index_st, - const node::OrderByNode** output) { - *output = order; - if (nullptr == order || nullptr == output) { - DLOG(WARNING) - << "fail to optimize order expr : order expr or output is null"; - return false; - } - if (index_st.ts_pos == INVALID_POS) { - DLOG(WARNING) << "not set ts col"; - return false; - } - auto& ts_column = schema.Get(index_st.ts_pos); - *output = order; - int succ_match = -1; - for (size_t i = 0; i < order->order_expressions()->GetChildNum(); ++i) { - auto expr = order->GetOrderExpressionExpr(i); - if (nullptr != expr && expr->GetExprType() == node::kExprColumnRef) { - auto column = dynamic_cast(expr); - std::string source_column_name; - if (ResolveColumnToSourceColumnName(column, schemas_ctx, - &source_column_name)) { - if (ts_column.name() == source_column_name) { - succ_match = i; - break; - } - } - } - } - if (succ_match >= 0) { - node::ExprListNode* expr_list = node_manager_->MakeExprList(); - for (size_t i = 0; i < order->order_expressions()->GetChildNum(); ++i) { - if (static_cast(succ_match) != i) { - expr_list->AddChild(order->order_expressions()->GetChild(i)); - } - } - *output = dynamic_cast( - node_manager_->MakeOrderByNode(expr_list)); - return true; - } else { - return false; - } -} - /** * Resolve column reference to possible source table's column name */ -static bool ResolveColumnToSourceColumnName(const node::ColumnRefNode* col, - const SchemasContext* schemas_ctx, - std::string* source_name) { - // use detailed column resolve utility +static bool ResolveColumnToSourceColumnName(const node::ColumnRefNode* col, const SchemasContext* schemas_ctx, + std::string* src_db, std::string* src_table, std::string* src_col) { + auto db = col->GetDBName(); + auto rel = col->GetRelationName(); + auto col_name = col->GetColumnName(); size_t column_id; int path_idx; size_t child_column_id; size_t source_column_id; const PhysicalOpNode* source; - Status status = schemas_ctx->ResolveColumnID(col->GetDBName(), - col->GetRelationName(), col->GetColumnName(), &column_id, &path_idx, - &child_column_id, &source_column_id, &source); - - // try loose the relation - if (!status.isOK() && !col->GetRelationName().empty()) { - status = schemas_ctx->ResolveColumnID( - col->GetDBName(), col->GetRelationName(), col->GetColumnName(), - &column_id, &path_idx, &child_column_id, - &source_column_id, &source); - } + Status status = schemas_ctx->ResolveColumnID(db, rel, col_name, &column_id, &path_idx, &child_column_id, + &source_column_id, &source); if (!status.isOK()) { LOG(WARNING) << "Illegal index column: " << col->GetExprString(); @@ -834,13 +850,17 @@ static bool ResolveColumnToSourceColumnName(const node::ColumnRefNode* col, << col->GetExprString(); return false; } - status = source->schemas_ctx()->ResolveColumnNameByID(source_column_id, - source_name); + + std::string sc_db, sc_table, sc_column; + status = source->schemas_ctx()->ResolveDbTableColumnByID(source_column_id, &sc_db, &sc_table, &sc_column); if (!status.isOK()) { - LOG(WARNING) << "Illegal source column id #" << source_column_id - << " for index column " << col->GetExprString(); + LOG(WARNING) << "Illegal source column id #" << source_column_id << " for index column " + << col->GetExprString(); return false; } + *src_db = sc_db; + *src_table = sc_table; + *src_col = sc_column; return true; } diff --git a/hybridse/src/passes/physical/group_and_sort_optimized.h b/hybridse/src/passes/physical/group_and_sort_optimized.h index 612b9cdaa67..1d410f2b8e8 100644 --- a/hybridse/src/passes/physical/group_and_sort_optimized.h +++ b/hybridse/src/passes/physical/group_and_sort_optimized.h @@ -16,12 +16,13 @@ #ifndef HYBRIDSE_SRC_PASSES_PHYSICAL_GROUP_AND_SORT_OPTIMIZED_H_ #define HYBRIDSE_SRC_PASSES_PHYSICAL_GROUP_AND_SORT_OPTIMIZED_H_ +#include #include #include #include -#include -#include +#include #include +#include #include "passes/physical/transform_up_physical_pass.h" @@ -85,12 +86,22 @@ class GroupAndSortOptimized : public TransformUpPysicalPass { Container* c_; }; + // info to a physical table + struct SrcColInfo { + std::string col_name; + std::string tb_name; + std::string db_name; + }; + private: bool Transform(PhysicalOpNode* in, PhysicalOpNode** output); bool KeysOptimized(const SchemasContext* root_schemas_ctx, PhysicalOpNode* in, Key* left_key, Key* index_key, Key* right_key, Sort* sort, PhysicalOpNode** new_in); + bool KeysOptimizedImpl(const SchemasContext* root_schemas_ctx, PhysicalOpNode* in, Key* left_key, Key* index_key, + Key* right_key, Sort* sort, PhysicalOpNode** new_in); + bool FilterAndOrderOptimized(const SchemasContext* root_schemas_ctx, PhysicalOpNode* in, Filter* filter, Sort* sort, PhysicalOpNode** new_in); @@ -115,12 +126,7 @@ class GroupAndSortOptimized : public TransformUpPysicalPass { bool GroupOptimized(const SchemasContext* root_schemas_ctx, PhysicalOpNode* in, Key* group, PhysicalOpNode** new_in); - bool SortOptimized(const SchemasContext* root_schemas_ctx, - PhysicalOpNode* in, Sort* sort); - bool TransformOrderExpr(const SchemasContext* schemas_ctx, - const node::OrderByNode* order, - const Schema& schema, const IndexSt& index_st, - const node::OrderByNode** output); + bool TransformKeysAndOrderExpr(const SchemasContext* schemas_ctx, const node::ExprListNode* groups, const node::OrderByNode* order, @@ -134,8 +140,15 @@ class GroupAndSortOptimized : public TransformUpPysicalPass { std::string* index_name, IndexBitMap* best_bitmap); + absl::Status BuildExprCache(const node::ExprNode* node, const SchemasContext* sc); + private: std::list ctx_; + + // Map ExprNode to source column name + // A source column name is the column name in string that refers to a physical table, + // only one table got optimized each time + std::unordered_map expr_cache_; }; } // namespace passes } // namespace hybridse diff --git a/hybridse/src/vm/engine.cc b/hybridse/src/vm/engine.cc index 6fd0f14a904..4fdc368887e 100644 --- a/hybridse/src/vm/engine.cc +++ b/hybridse/src/vm/engine.cc @@ -94,27 +94,10 @@ bool Engine::GetDependentTables(const std::string& sql, const std::string& db, return false; } - status = GetDependentTables(physical_plan, db_tables); + status = internal::GetDependentTables(physical_plan, db_tables); return status.isOK(); } -Status Engine::GetDependentTables(const PhysicalOpNode* root, std::set>* db_tbs) { - using OUT = std::set>; - *db_tbs = internal::ReduceNode( - root, OUT{}, - [](OUT init, const PhysicalOpNode* node) { - if (node->GetOpType() == kPhysicalOpDataProvider) { - auto* data_op = dynamic_cast(node); - if (data_op != nullptr) { - init.emplace(data_op->GetDb(), data_op->GetName()); - } - } - return init; - }, - [](const PhysicalOpNode* node) { return node->GetDependents(); }); - return Status::OK(); -} - bool Engine::IsCompatibleCache(RunSession& session, // NOLINT std::shared_ptr info, base::Status& status) { // NOLINT @@ -271,7 +254,7 @@ bool Engine::Explain(const std::string& sql, const std::string& db, EngineMode e explain_output->request_db_name = ctx.request_db_name; explain_output->limit_cnt = ctx.limit_cnt; - auto s = GetDependentTables(ctx.physical_plan, &explain_output->dependent_tables); + auto s = internal::GetDependentTables(ctx.physical_plan, &explain_output->dependent_tables); if (!s.isOK()) { LOG(ERROR) << s; status->code = common::kPhysicalPlanError; diff --git a/hybridse/src/vm/generator.cc b/hybridse/src/vm/generator.cc index 2b437ca2602..28542a7befb 100644 --- a/hybridse/src/vm/generator.cc +++ b/hybridse/src/vm/generator.cc @@ -726,5 +726,9 @@ std::shared_ptr FilterGenerator::Filter(std::shared_ptr(table, limit.value()); } +bool FilterGenerator::ValidIndex() const { + return index_seek_gen_.Valid(); +} + } // namespace vm } // namespace hybridse diff --git a/hybridse/src/vm/generator.h b/hybridse/src/vm/generator.h index 51bc6b1e674..4dded0d6ebf 100644 --- a/hybridse/src/vm/generator.h +++ b/hybridse/src/vm/generator.h @@ -230,6 +230,9 @@ class FilterGenerator : public PredicateFun { const bool Valid() const { return index_seek_gen_.Valid() || condition_gen_.Valid(); } + // return if index seek exists + bool ValidIndex() const; + std::shared_ptr Filter(std::shared_ptr table, const Row& parameter, std::optional limit); diff --git a/hybridse/src/vm/internal/node_helper.cc b/hybridse/src/vm/internal/node_helper.cc new file mode 100644 index 00000000000..9d97c14374a --- /dev/null +++ b/hybridse/src/vm/internal/node_helper.cc @@ -0,0 +1,42 @@ +/** + * Copyright (c) 2023 OpenMLDB authors + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include "vm/internal/node_helper.h" + +namespace hybridse { +namespace vm { +namespace internal { + +Status GetDependentTables(const PhysicalOpNode* root, std::set>* db_tbs) { + using OUT = std::set>; + *db_tbs = internal::ReduceNode( + root, OUT{}, + [](OUT init, const PhysicalOpNode* node) { + if (node->GetOpType() == kPhysicalOpDataProvider) { + auto* data_op = dynamic_cast(node); + if (data_op != nullptr) { + init.emplace(data_op->GetDb(), data_op->GetName()); + } + } + return init; + }, + [](const PhysicalOpNode* node) { return node->GetDependents(); }); + return Status::OK(); +} + +} // namespace internal +} // namespace vm +} // namespace hybridse diff --git a/hybridse/src/vm/internal/node_helper.h b/hybridse/src/vm/internal/node_helper.h index 89b47ea4e0f..7b9d5044748 100644 --- a/hybridse/src/vm/internal/node_helper.h +++ b/hybridse/src/vm/internal/node_helper.h @@ -18,6 +18,8 @@ #ifndef HYBRIDSE_SRC_VM_INTERNAL_NODE_HELPER_H_ #define HYBRIDSE_SRC_VM_INTERNAL_NODE_HELPER_H_ +#include +#include #include #include @@ -63,6 +65,9 @@ State ReduceNode(const PhysicalOpNode* root, State state, BinOp&& op, GetKids&& return state; } +// Get all dependent (db, table) info from physical plan +Status GetDependentTables(const PhysicalOpNode*, std::set>*); + } // namespace internal } // namespace vm } // namespace hybridse diff --git a/hybridse/src/vm/runner.cc b/hybridse/src/vm/runner.cc index 2072715c613..be954653b91 100644 --- a/hybridse/src/vm/runner.cc +++ b/hybridse/src/vm/runner.cc @@ -25,7 +25,6 @@ #include "absl/strings/str_cat.h" #include "absl/strings/substitute.h" #include "base/texttable.h" -#include "udf/udf.h" #include "vm/catalog_wrapper.h" #include "vm/core_api.h" #include "vm/internal/eval.h" @@ -139,10 +138,9 @@ ClusterTask RunnerBuilder::Build(PhysicalOpNode* node, Status& status) { } } case kPhysicalOpSimpleProject: { - auto cluster_task = // NOLINT - Build(node->producers().at(0), status); + auto cluster_task = Build(node->producers().at(0), status); if (!cluster_task.IsValid()) { - status.msg = "fail to build input runner"; + status.msg = "fail to build input runner for simple project:\n" + node->GetTreeString(); status.code = common::kExecutionPlanError; LOG(WARNING) << status; return fail; @@ -338,19 +336,17 @@ ClusterTask RunnerBuilder::Build(PhysicalOpNode* node, Status& status) { return BuildRequestAggUnionTask(node, status); } case kPhysicalOpRequestJoin: { - auto left_task = // NOLINT - Build(node->producers().at(0), status); + auto left_task = Build(node->GetProducer(0), status); if (!left_task.IsValid()) { - status.msg = "fail to build left input runner"; + status.msg = "fail to build left input runner for: " + node->GetProducer(0)->GetTreeString(); status.code = common::kExecutionPlanError; LOG(WARNING) << status; return fail; } auto left = left_task.GetRoot(); - auto right_task = // NOLINT - Build(node->producers().at(1), status); + auto right_task = Build(node->GetProducer(1), status); if (!right_task.IsValid()) { - status.msg = "fail to build right input runner"; + status.msg = "fail to build right input runner for: " + node->GetProducer(1)->GetTreeString(); status.code = common::kExecutionPlanError; LOG(WARNING) << status; return fail; @@ -364,19 +360,38 @@ ClusterTask RunnerBuilder::Build(PhysicalOpNode* node, Status& status) { left->output_schemas()->GetSchemaSourceSize(), right->output_schemas()->GetSchemaSourceSize(), op->output_right_only()); - if (support_cluster_optimized_ && IsPartitionProvider(node->GetProducer(0))) { - // Partion left join partition, route by index of the left source, and it should uncompleted - auto& route_info = left_task.GetRouteInfo(); - runner->AddProducer(left_task.GetRoot()); - runner->AddProducer(right_task.GetRoot()); - return UnCompletedClusterTask(runner, route_info.table_handler_, route_info.index_); - } else { - return RegisterTask( - node, BinaryInherit(left_task, right_task, runner, op->join().index_key(), kLeftBias)); + if (support_cluster_optimized_) { + if (IsPartitionProvider(node->GetProducer(0))) { + // Partion left join partition, route by index of the left source, and it should uncompleted + auto& route_info = left_task.GetRouteInfo(); + runner->AddProducer(left_task.GetRoot()); + runner->AddProducer(right_task.GetRoot()); + return RegisterTask( + node, UnCompletedClusterTask(runner, route_info.table_handler_, route_info.index_)); + } + + if (right_task.IsCompletedClusterTask() && right_task.GetRouteInfo().lazy_route_ && + !op->join_.index_key_.ValidKey()) { + auto& route_info = right_task.GetRouteInfo(); + runner->AddProducer(left_task.GetRoot()); + runner->AddProducer(right_task.GetRoot()); + return RegisterTask(node, ClusterTask(runner, {}, route_info)); + } } + + return RegisterTask( + node, BinaryInherit(left_task, right_task, runner, op->join().index_key(), kLeftBias)); } case node::kJoinTypeConcat: { ConcatRunner* runner = CreateRunner(id_++, node->schemas_ctx(), op->GetLimitCnt()); + if (support_cluster_optimized_) { + if (right_task.IsCompletedClusterTask() && right_task.GetRouteInfo().lazy_route_ && + !op->join_.index_key_.ValidKey()) { + runner->AddProducer(left_task.GetRoot()); + runner->AddProducer(right_task.GetRoot()); + return RegisterTask(node, ClusterTask(runner, {}, RouteInfo{})); + } + } return RegisterTask(node, BinaryInherit(left_task, right_task, runner, Key(), kNoBias)); } default: { @@ -464,9 +479,8 @@ ClusterTask RunnerBuilder::Build(PhysicalOpNode* node, Status& status) { return RegisterTask(node, UnaryInheritTask(cluster_task, runner)); } case kPhysicalOpFilter: { - auto cluster_task = // NOLINT - Build(node->producers().at(0), status); - if (!cluster_task.IsValid()) { + auto producer_task = Build(node->GetProducer(0), status); + if (!producer_task.IsValid()) { status.msg = "fail to build input runner"; status.code = common::kExecutionPlanError; LOG(WARNING) << status; @@ -475,7 +489,27 @@ ClusterTask RunnerBuilder::Build(PhysicalOpNode* node, Status& status) { auto op = dynamic_cast(node); FilterRunner* runner = CreateRunner(id_++, node->schemas_ctx(), op->GetLimitCnt(), op->filter_); - return RegisterTask(node, UnaryInheritTask(cluster_task, runner)); + // under cluster, filter task might be completed or uncompleted + // based on whether filter node has the index_key underlaying DataTask requires + ClusterTask out; + if (support_cluster_optimized_) { + auto& route_info_ref = producer_task.GetRouteInfo(); + if (runner->filter_gen_.ValidIndex()) { + // complete the route info + RouteInfo lazy_route_info(route_info_ref.index_, op->filter().index_key(), + std::make_shared(producer_task), + route_info_ref.table_handler_); + lazy_route_info.lazy_route_ = true; + runner->AddProducer(producer_task.GetRoot()); + out = ClusterTask(runner, {}, lazy_route_info); + } else { + runner->AddProducer(producer_task.GetRoot()); + out = UnCompletedClusterTask(runner, route_info_ref.table_handler_, route_info_ref.index_); + } + } else { + out = UnaryInheritTask(producer_task, runner); + } + return RegisterTask(node, out); } case kPhysicalOpLimit: { auto cluster_task = // NOLINT @@ -709,8 +743,7 @@ ClusterTask RunnerBuilder::BuildClusterTaskForBinaryRunner( new_right.IsCompletedClusterTask()) { // merge left and right task if tasks can be merged if (ClusterTask::TaskCanBeMerge(new_left, new_right)) { - ClusterTask task = - ClusterTask::TaskMerge(runner, new_left, new_right); + ClusterTask task = ClusterTask::TaskMerge(runner, new_left, new_right); runner->AddProducer(new_left.GetRoot()); runner->AddProducer(new_right.GetRoot()); return task; @@ -735,10 +768,12 @@ ClusterTask RunnerBuilder::BuildClusterTaskForBinaryRunner( } } } - if (new_left.IsUnCompletedClusterTask() || - new_right.IsUnCompletedClusterTask()) { - LOG(WARNING) << "Fail to build cluster task, can't handler " - "uncompleted cluster task"; + if (new_left.IsUnCompletedClusterTask()) { + LOG(WARNING) << "can't handler uncompleted cluster task from left:" << new_left; + return ClusterTask(); + } + if (new_right.IsUnCompletedClusterTask()) { + LOG(WARNING) << "can't handler uncompleted cluster task from right:" << new_right; return ClusterTask(); } diff --git a/hybridse/src/vm/runner.h b/hybridse/src/vm/runner.h index 25857dbdd0f..64e712bbde7 100644 --- a/hybridse/src/vm/runner.h +++ b/hybridse/src/vm/runner.h @@ -857,8 +857,7 @@ class ProxyRequestRunner : public Runner { const std::vector>& inputs) override; std::shared_ptr BatchRequestRun( RunnerContext& ctx) override; // NOLINT - virtual void PrintRunnerInfo(std::ostream& output, - const std::string& tab) const { + void PrintRunnerInfo(std::ostream& output, const std::string& tab) const override { output << tab << "[" << id_ << "]" << RunnerTypeName(type_) << "(TASK_ID=" << task_id_ << ")"; if (is_lazy_) { @@ -947,6 +946,9 @@ class RouteInfo { const std::string ToString() const { if (IsCompleted()) { std::ostringstream oss; + if (lazy_route_) { + oss << "[LAZY]"; + } oss << ", routing index = " << table_handler_->GetDatabase() << "." << table_handler_->GetName() << "." << index_ << ", " << index_key_.ToString(); @@ -960,6 +962,9 @@ class RouteInfo { Runner* index_key_input_runner_; std::shared_ptr input_; std::shared_ptr table_handler_; + + // if true: generate the complete ClusterTask only when requires + bool lazy_route_ = false; }; // task info of cluster job @@ -968,9 +973,12 @@ class RouteInfo { // request generator class ClusterTask { public: + // common tasks ClusterTask() : root_(nullptr), input_runners_(), route_info_() {} explicit ClusterTask(Runner* root) : root_(root), input_runners_(), route_info_() {} + + // cluster task with explicit routeinfo ClusterTask(Runner* root, const std::shared_ptr table_handler, std::string index) : root_(root), input_runners_(), route_info_(index, table_handler) {} @@ -978,6 +986,7 @@ class ClusterTask { const RouteInfo& route_info) : root_(root), input_runners_(input_runners), route_info_(route_info) {} ~ClusterTask() {} + void Print(std::ostream& output, const std::string& tab) const { output << route_info_.ToString() << "\n"; if (nullptr == root_) { @@ -988,6 +997,11 @@ class ClusterTask { } } + friend std::ostream& operator<<(std::ostream& os, const ClusterTask& output) { + output.Print(os, ""); + return os; + } + void ResetInputs(std::shared_ptr input) { for (auto input_runner : input_runners_) { input_runner->SetProducer(0, route_info_.input_->GetRoot()); @@ -1180,8 +1194,7 @@ class RunnerBuilder { Status& status) { // NOLINT id_ = 0; cluster_job_.Reset(); - auto task = // NOLINT whitespace/braces - Build(node, status); + auto task = Build(node, status); if (!status.isOK()) { return cluster_job_; } @@ -1215,6 +1228,7 @@ class RunnerBuilder { private: node::NodeManager* nm_; + // only set for request mode bool support_cluster_optimized_; int32_t id_; ClusterJob cluster_job_; diff --git a/hybridse/src/vm/schemas_context.cc b/hybridse/src/vm/schemas_context.cc index 214da20caa5..7d794bc8f92 100644 --- a/hybridse/src/vm/schemas_context.cc +++ b/hybridse/src/vm/schemas_context.cc @@ -382,40 +382,20 @@ Status DoSearchExprDependentColumns(const node::ExprNode* expr, std::vectorpush_back(expr); break; } - case node::kExprBetween: { - std::vector expr_list; - auto between_expr = dynamic_cast(expr); - CHECK_STATUS(DoSearchExprDependentColumns(between_expr->GetLow(), - columns)); - CHECK_STATUS(DoSearchExprDependentColumns(between_expr->GetHigh(), - columns)); - CHECK_STATUS(DoSearchExprDependentColumns(between_expr->GetLhs(), - columns)); - break; - } case node::kExprCall: { auto call_expr = dynamic_cast(expr); if (nullptr != call_expr->GetOver()) { auto orders = call_expr->GetOver()->GetOrders(); if (nullptr != orders) { - CHECK_STATUS( - DoSearchExprDependentColumns(orders, columns)); + CHECK_STATUS(DoSearchExprDependentColumns(orders, columns)); } auto partitions = call_expr->GetOver()->GetPartitions(); if (nullptr != partitions) { - CHECK_STATUS( - DoSearchExprDependentColumns(partitions, columns)); + CHECK_STATUS(DoSearchExprDependentColumns(partitions, columns)); } } break; } - case node::kExprOrderExpression: { - auto refx = dynamic_cast(expr); - CHECK_TRUE(refx != nullptr, common::kTypeError); - CHECK_STATUS(DoSearchExprDependentColumns(refx->expr(), columns)); - - break; - } default: break; } diff --git a/hybridse/src/vm/transform.cc b/hybridse/src/vm/transform.cc index 60549447e42..8020c99741f 100644 --- a/hybridse/src/vm/transform.cc +++ b/hybridse/src/vm/transform.cc @@ -21,6 +21,7 @@ #include #include "absl/cleanup/cleanup.h" +#include "base/fe_status.h" #include "codegen/context.h" #include "codegen/fn_ir_builder.h" #include "codegen/fn_let_ir_builder.h" @@ -38,6 +39,7 @@ #include "passes/physical/transform_up_physical_pass.h" #include "passes/physical/window_column_pruning.h" #include "plan/planner.h" +#include "proto/fe_common.pb.h" #include "vm/physical_op.h" #include "vm/schemas_context.h" #include "vm/internal/node_helper.h" @@ -822,6 +824,7 @@ Status RequestModeTransformer::OptimizeSimpleProjectAsWindowProducer(PhysicalSim return Status::OK(); } +// From window (t1 last join t2 [ last join t3]...) // Optimize // RequestJoin(Request(left_table), DataSource(right_table)) // -> @@ -905,7 +908,8 @@ Status FixupWindowOverSimpleNLastJoin(const node::WindowPlanNode* w_ptr, const S size_t id = 0; CHECK_STATUS(window_depend_sc->ResolveColumnID(ref->GetDBName(), ref->GetRelationName(), - ref->GetColumnName(), &id)); + ref->GetColumnName(), &id), + "fail to resolve ", ref->GetExprString()); std::string name; CHECK_STATUS( left_join_sc->ResolveColumnNameByID(id, &name), @@ -930,7 +934,8 @@ Status FixupWindowOverSimpleNLastJoin(const node::WindowPlanNode* w_ptr, const S size_t id = 0; CHECK_STATUS(window_depend_sc->ResolveColumnID(ref->GetDBName(), ref->GetRelationName(), - ref->GetColumnName(), &id)); + ref->GetColumnName(), &id), + "fail to resolve ", ref->GetExprString()); std::string name; CHECK_STATUS(left_join_sc->ResolveColumnNameByID(id, &name), "Fail to handle window: window order expression should belong to left table of join"); @@ -1603,28 +1608,12 @@ bool BatchModeTransformer::isSourceFromTableOrPartition(PhysicalOpNode* in) { kPhysicalOpFilter == in->GetOpType()) { return isSourceFromTableOrPartition(in->GetProducer(0)); } else if (kPhysicalOpDataProvider == in->GetOpType()) { - return kProviderTypePartition == - dynamic_cast(in) - ->provider_type_ || - kProviderTypeTable == - dynamic_cast(in)->provider_type_; - } - return false; -} -bool BatchModeTransformer::isSourceFromTable(PhysicalOpNode* in) { - if (nullptr == in) { - DLOG(WARNING) << "Invalid physical node: null"; - return false; - } - if (kPhysicalOpSimpleProject == in->GetOpType() || - kPhysicalOpRename == in->GetOpType()) { - return isSourceFromTableOrPartition(in->GetProducer(0)); - } else if (kPhysicalOpDataProvider == in->GetOpType()) { - return kProviderTypeTable == - dynamic_cast(in)->provider_type_; + return kProviderTypePartition == dynamic_cast(in)->provider_type_ || + kProviderTypeTable == dynamic_cast(in)->provider_type_; } return false; } + Status BatchModeTransformer::ValidateTableProvider(PhysicalOpNode* in) { CHECK_TRUE(nullptr != in, kPlanError, "Invalid physical node: null"); CHECK_TRUE(isSourceFromTableOrPartition(in), kPlanError, @@ -1654,11 +1643,9 @@ Status BatchModeTransformer::ValidatePartitionDataProvider(PhysicalOpNode* in) { CHECK_STATUS(ValidatePartitionDataProvider(in->GetProducer(0))); CHECK_STATUS(ValidatePartitionDataProvider(in->GetProducer(1))); } else { - CHECK_TRUE( - kPhysicalOpDataProvider == in->GetOpType() && - kProviderTypePartition == - dynamic_cast(in)->provider_type_, - kPlanError, "Isn't partition provider:", in->GetTreeString()); + CHECK_TRUE(kPhysicalOpDataProvider == in->GetOpType() && + kProviderTypePartition == dynamic_cast(in)->provider_type_, + kPlanError, "Isn't partition provider:", in->GetTreeString()); } return Status::OK(); } @@ -1795,10 +1782,9 @@ Status BatchModeTransformer::ValidatePlanSupported(const PhysicalOpNode* in) { // - ValidateNotAggregationOverTable Status RequestModeTransformer::ValidatePlan(PhysicalOpNode* node) { CHECK_STATUS(BatchModeTransformer::ValidatePlan(node)) - PhysicalOpNode* primary_source = nullptr; // OnlineServing restriction: Expect to infer one and only one request table from given SQL - CHECK_STATUS(ValidateRequestTable(node, &primary_source), "Fail to validate physical plan") + CHECK_STATUS(ValidateRequestTable(node), "Fail to validate physical plan") // For Online serving, SQL queries should be designed extremely performance-sensitive to satisfy the real-time // requirements. Thus, we need to Validate if the SQL has been optimized well enough @@ -2422,18 +2408,32 @@ Status RequestModeTransformer::TransformScanOp(const node::TablePlanNode* node, return BatchModeTransformer::TransformScanOp(node, output); } } -Status RequestModeTransformer::ValidateRequestTable( - PhysicalOpNode* in, PhysicalOpNode** request_table) { - CHECK_TRUE(in != NULL, kPlanError, "NULL Physical Node"); +Status RequestModeTransformer::ValidateRequestTable(PhysicalOpNode* in) { + auto req = ExtractRequestNode(in); + CHECK_TRUE(req.ok(), kPlanError, req.status()); + + std::set> db_tables; + CHECK_STATUS(internal::GetDependentTables(in, &db_tables)); + CHECK_TRUE(req.value() != nullptr || db_tables.empty(), kPlanError, "no request node found"); + + return Status::OK(); +} + +absl::StatusOr RequestModeTransformer::ExtractRequestNode(PhysicalOpNode* in) { + if (in == nullptr) { + return absl::InvalidArgumentError("null input node"); + } switch (in->GetOpType()) { case vm::kPhysicalOpDataProvider: { - CHECK_TRUE(kProviderTypeRequest == dynamic_cast(in)->provider_type_, kPlanError, - "Expect a request table but a ", - vm::DataProviderTypeName(dynamic_cast(in)->provider_type_), " ", - in->GetTreeString()) - *request_table = in; - return Status::OK(); + auto tp = dynamic_cast(in)->provider_type_; + if (tp == kProviderTypeRequest) { + return in; + } + + // else data provider is fine inside node tree, + // generally it is of type Partition, but can be Table as well e.g window (t1 instance_not_in_window) + return nullptr; } case vm::kPhysicalOpJoin: case vm::kPhysicalOpUnion: @@ -2441,45 +2441,46 @@ Status RequestModeTransformer::ValidateRequestTable( case vm::kPhysicalOpRequestUnion: case vm::kPhysicalOpRequestAggUnion: case vm::kPhysicalOpRequestJoin: { - vm::PhysicalOpNode* left_primary_source = nullptr; - CHECK_STATUS(ValidateRequestTable(in->GetProducer(0), &left_primary_source)) - CHECK_TRUE( - nullptr != left_primary_source, kPlanError, - "Fail to infer a request table") - // Case 1: - // binary_node - // + Left - PrimarySource - // + Right - TableProvider - if (isSourceFromTableOrPartition(in->GetProducer(1))) { - *request_table = left_primary_source; - return Status::OK(); + // Binary Node + // - left or right status not ok -> error + // - left and right both has non-null value + // - the two not equals -> error + // - otherwise -> left as request node + auto left = ExtractRequestNode(in->GetProducer(0)); + if (!left.ok()) { + return left; + } + auto right = ExtractRequestNode(in->GetProducer(1)); + if (!right.ok()) { + return right; } - vm::PhysicalOpNode* right_primary_source = nullptr; - CHECK_STATUS(ValidateRequestTable(in->GetProducer(1), &right_primary_source)) - CHECK_TRUE( - nullptr != right_primary_source, kPlanError, - "Fail to infer a request table") - // Case 2: - // binary_node - // + Left <-- SamePrimarySource1 - // + Right <-- SamePrimarySource1 - CHECK_TRUE(left_primary_source->Equals(right_primary_source), kPlanError, - "left path and right path has different request table") - *request_table = left_primary_source; - return Status::OK(); - } - case vm::kPhysicalOpConstProject: { - break; + if (left.value() != nullptr && right.value() != nullptr) { + if (!left.value()->Equals(right.value())) { + return absl::NotFoundError( + absl::StrCat("different request table from left and right path:\n", in->GetTreeString())); + } + } + + return left.value(); } default: { - CHECK_TRUE(in->GetProducerCnt() == 1, kPlanError, - "Non-support Op ", PhysicalOpTypeName(in->GetOpType())) - CHECK_STATUS(ValidateRequestTable(in->GetProducer(0), request_table)); - return Status::OK(); + break; } } - return Status::OK(); + + if (in->GetProducerCnt() == 0) { + // leaf node excepting DataProdiverNode + // consider ok as right source from one of the supported binary op + return nullptr; + } + + if (in->GetProducerCnt() > 1) { + return absl::UnimplementedError( + absl::StrCat("Non-support op with more than one producer:\n", in->GetTreeString())); + } + + return ExtractRequestNode(in->GetProducer(0)); } // transform a single `ProjectListNode` of `ProjectPlanNode` diff --git a/hybridse/src/vm/transform.h b/hybridse/src/vm/transform.h index 22a7b74c5b9..caaf63b655d 100644 --- a/hybridse/src/vm/transform.h +++ b/hybridse/src/vm/transform.h @@ -141,7 +141,6 @@ class BatchModeTransformer { Status GenRange(Range* sort, const SchemasContext* schemas_ctx); static bool isSourceFromTableOrPartition(PhysicalOpNode* in); - bool isSourceFromTable(PhysicalOpNode* in); std::string ExtractSchemaName(PhysicalOpNode* in); static Status ValidateIndexOptimization(PhysicalOpNode* physical_plan); @@ -319,7 +318,17 @@ class RequestModeTransformer : public BatchModeTransformer { absl::StatusOr ResolveCTERef(absl::string_view tb_name) override; - Status ValidateRequestTable(PhysicalOpNode* in, PhysicalOpNode** request_table); + // Valid the final optimized PhysicalOpNode is either: + // - has one and only one request table + // - do not has any physical table refered + Status ValidateRequestTable(PhysicalOpNode* in); + + // Extract request node of the node tree + // returns + // - Request node on success + // - NULL if tree do not has request table but sufficient as as input tree of the big one + // - Error status otherwise + static absl::StatusOr ExtractRequestNode(PhysicalOpNode* in); private: // Optimize simple project node which is the producer of window project From 88e9e79aa133860fe216c6b0f4eaa1570b35668a Mon Sep 17 00:00:00 2001 From: dl239 Date: Tue, 17 Oct 2023 10:32:24 +0800 Subject: [PATCH 17/32] feat: support show create table (#3500) --- cases/plan/cmd.yaml | 17 +++ .../sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md | 28 ++++ docs/en/reference/sql/ddl/index.rst | 1 + .../ddl/SHOW_CREATE_TABLE_STATEMENT.md | 28 ++++ docs/zh/openmldb_sql/ddl/index.rst | 1 + hybridse/include/node/node_enum.h | 1 + hybridse/src/node/sql_node.cc | 1 + hybridse/src/planv2/ast_node_converter.cc | 1 + src/sdk/CMakeLists.txt | 3 + src/sdk/sdk_util.cc | 96 +++++++++++++ src/sdk/sdk_util.h | 35 +++++ src/sdk/sdk_util_test.cc | 127 ++++++++++++++++++ src/sdk/sql_cluster_router.cc | 39 ++++-- src/sdk/sql_cluster_test.cc | 18 +++ third-party/cmake/FetchZetasql.cmake | 8 +- 15 files changed, 392 insertions(+), 12 deletions(-) create mode 100644 docs/en/reference/sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md create mode 100644 docs/zh/openmldb_sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md create mode 100644 src/sdk/sdk_util.cc create mode 100644 src/sdk/sdk_util.h create mode 100644 src/sdk/sdk_util_test.cc diff --git a/cases/plan/cmd.yaml b/cases/plan/cmd.yaml index 3ca7d89ba6f..50b5fa94343 100644 --- a/cases/plan/cmd.yaml +++ b/cases/plan/cmd.yaml @@ -704,3 +704,20 @@ cases: +-actions: +-0: DropPathAction (12) +-1: AddPathAction (13) + + - id: show-create-table + desc: SHOW CREATE TABLE + sql: SHOW CREATE TABLE t1; + expect: + node_tree_str: | + +-node[CMD] + +-cmd_type: show create table + +-args: [t1] + - id: show-create-table-db + desc: SHOW CREATE TABLE + sql: SHOW CREATE TABLE db1.t1; + expect: + node_tree_str: | + +-node[CMD] + +-cmd_type: show create table + +-args: [db1, t1] diff --git a/docs/en/reference/sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md b/docs/en/reference/sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md new file mode 100644 index 00000000000..dd411410e65 --- /dev/null +++ b/docs/en/reference/sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md @@ -0,0 +1,28 @@ +# SHOW CREATE TABLE + +`SHOW CREATE TABLE` shows the `CREATE TABLE` statement that creates the named table + +**Syntax** + +```sql +SHOW CREATE TABLE table_name; +``` + +**Example** + +```sql +show create table t1; + ------- --------------------------------------------------------------- + Table Create Table + ------- --------------------------------------------------------------- + t1 CREATE TABLE `t1` ( + `c1` varchar, + `c2` int, + `c3` bigInt, + `c4` timestamp, + INDEX (KEY=`c1`, TS=`c4`, TTL_TYPE=ABSOLUTE, TTL=0m) + ) OPTIONS (PARTITIONNUM=8, REPLICANUM=2, STORAGE_MODE='HDD'); + ------- --------------------------------------------------------------- + +1 rows in set +``` \ No newline at end of file diff --git a/docs/en/reference/sql/ddl/index.rst b/docs/en/reference/sql/ddl/index.rst index 09199ec27ba..dbc94cc1f3d 100644 --- a/docs/en/reference/sql/ddl/index.rst +++ b/docs/en/reference/sql/ddl/index.rst @@ -23,3 +23,4 @@ Data Definition Statement (DDL) CREATE_FUNCTION SHOW_FUNCTIONS DROP_FUNCTION + SHOW_CREATE_TABLE_STATEMENT diff --git a/docs/zh/openmldb_sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md b/docs/zh/openmldb_sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md new file mode 100644 index 00000000000..e697f687846 --- /dev/null +++ b/docs/zh/openmldb_sql/ddl/SHOW_CREATE_TABLE_STATEMENT.md @@ -0,0 +1,28 @@ +# SHOW CREATE TABLE + +`SHOW CREATE TABLE` 用来显示指定表的建表语句 + +**Syntax** + +```sql +SHOW CREATE TABLE table_name; +``` + +**Example** + +```sql +show create table t1; + ------- --------------------------------------------------------------- + Table Create Table + ------- --------------------------------------------------------------- + t1 CREATE TABLE `t1` ( + `c1` varchar, + `c2` int, + `c3` bigInt, + `c4` timestamp, + INDEX (KEY=`c1`, TS=`c4`, TTL_TYPE=ABSOLUTE, TTL=0m) + ) OPTIONS (PARTITIONNUM=8, REPLICANUM=2, STORAGE_MODE='HDD'); + ------- --------------------------------------------------------------- + +1 rows in set +``` \ No newline at end of file diff --git a/docs/zh/openmldb_sql/ddl/index.rst b/docs/zh/openmldb_sql/ddl/index.rst index 116b9ce29c3..efd36734261 100644 --- a/docs/zh/openmldb_sql/ddl/index.rst +++ b/docs/zh/openmldb_sql/ddl/index.rst @@ -23,3 +23,4 @@ CREATE_FUNCTION SHOW_FUNCTIONS DROP_FUNCTION + SHOW_CREATE_TABLE_STATEMENT diff --git a/hybridse/include/node/node_enum.h b/hybridse/include/node/node_enum.h index 4fc914799d0..16e18291478 100644 --- a/hybridse/include/node/node_enum.h +++ b/hybridse/include/node/node_enum.h @@ -283,6 +283,7 @@ enum CmdType { kCmdShowFunctions, kCmdDropFunction, kCmdShowJobLog, + kCmdShowCreateTable, kCmdFake, // not a real cmd, for testing purpose only kLastCmd = kCmdFake, }; diff --git a/hybridse/src/node/sql_node.cc b/hybridse/src/node/sql_node.cc index bc5aec55cf9..16b88cd51ba 100644 --- a/hybridse/src/node/sql_node.cc +++ b/hybridse/src/node/sql_node.cc @@ -58,6 +58,7 @@ static absl::flat_hash_map CreateCmdTypeNamesMap() { {CmdType::kCmdDropTable, "drop table"}, {CmdType::kCmdShowProcedures, "show procedures"}, {CmdType::kCmdShowCreateSp, "show create procedure"}, + {CmdType::kCmdShowCreateTable, "show create table"}, {CmdType::kCmdDropSp, "drop procedure"}, {CmdType::kCmdDropIndex, "drop index"}, {CmdType::kCmdExit, "exit"}, diff --git a/hybridse/src/planv2/ast_node_converter.cc b/hybridse/src/planv2/ast_node_converter.cc index 19bb0ccfc6c..c0c3864716b 100644 --- a/hybridse/src/planv2/ast_node_converter.cc +++ b/hybridse/src/planv2/ast_node_converter.cc @@ -2172,6 +2172,7 @@ static const absl::flat_hash_map showTargetMap {"SESSION VARIABLES", {node::CmdType::kCmdShowSessionVariables}}, {"GLOBAL VARIABLES", {node::CmdType::kCmdShowGlobalVariables}}, {"CREATE PROCEDURE", {node::CmdType::kCmdShowCreateSp, true}}, + {"CREATE TABLE", {node::CmdType::kCmdShowCreateTable, true}}, {"DEPLOYMENT", {node::CmdType::kCmdShowDeployment, true}}, {"JOB", {node::CmdType::kCmdShowJob, true}}, {"COMPONENTS", {node::CmdType::kCmdShowComponents}}, diff --git a/src/sdk/CMakeLists.txt b/src/sdk/CMakeLists.txt index cc959f6a23b..28c41e09c52 100644 --- a/src/sdk/CMakeLists.txt +++ b/src/sdk/CMakeLists.txt @@ -26,6 +26,9 @@ if(TESTING_ENABLE) add_executable(db_sdk_test db_sdk_test.cc) target_link_libraries(db_sdk_test ${SDK_TEST_DEPS} ${BIN_LIBS} ${THIRD_LIBS}) + add_executable(sdk_util_test sdk_util_test.cc) + target_link_libraries(sdk_util_test ${SDK_TEST_DEPS} ${BIN_LIBS} ${THIRD_LIBS}) + add_executable(result_set_sql_test result_set_sql_test.cc) target_link_libraries(result_set_sql_test ${SDK_TEST_DEPS} ${BIN_LIBS} ${THIRD_LIBS}) diff --git a/src/sdk/sdk_util.cc b/src/sdk/sdk_util.cc new file mode 100644 index 00000000000..f6027f7c08b --- /dev/null +++ b/src/sdk/sdk_util.cc @@ -0,0 +1,96 @@ +/* + * Copyright 2021 4Paradigm + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include "sdk/sdk_util.h" + +#include +#include "codec/schema_codec.h" + +namespace openmldb { +namespace sdk { + +std::string SDKUtil::GenCreateTableSQL(const ::openmldb::nameserver::TableInfo& table_info) { + std::stringstream ss; + ss << "CREATE TABLE `" << table_info.name() << "` (\n"; + for (const auto& column : table_info.column_desc()) { + auto it = openmldb::codec::DATA_TYPE_STR_MAP.find(column.data_type()); + if (it != openmldb::codec::DATA_TYPE_STR_MAP.end()) { + ss << "`" << column.name() << "` " << it->second; + if (column.has_default_value()) { + ss << " DEFAULT '" << column.default_value() << "'"; + } + if (column.not_null()) { + ss << " NOT NULL"; + } + ss << ",\n"; + } + } + int index_cnt = 0; + for (const auto& index : table_info.column_key()) { + if (index.flag() != 0) { + continue; + } + if (index_cnt > 0) { + ss << ",\n"; + } + ss << "INDEX ("; + if (index.col_name_size() == 1) { + ss << "KEY=`" << index.col_name(0) << "`"; + } else { + ss << "KEY=("; + for (int idx = 0; idx < index.col_name_size(); idx++) { + if (idx > 0) { + ss << ","; + } + ss << "`" << index.col_name(idx) << "`"; + } + ss << ")"; + } + if (index.has_ts_name() && !index.ts_name().empty()) { + ss << ", TS=`" << index.ts_name() << "`"; + } + if (index.has_ttl()) { + ss << ", TTL_TYPE="; + if (index.ttl().ttl_type() == openmldb::type::TTLType::kAbsoluteTime) { + ss << "ABSOLUTE, TTL=" << index.ttl().abs_ttl() << "m"; + } else if (index.ttl().ttl_type() == openmldb::type::TTLType::kLatestTime) { + ss << "LATEST, TTL=" << index.ttl().lat_ttl(); + } else if (index.ttl().ttl_type() == openmldb::type::TTLType::kAbsAndLat) { + ss << "ABSANDLAT, TTL=(" << index.ttl().abs_ttl() << "m, " << index.ttl().lat_ttl() << ")"; + } else if (index.ttl().ttl_type() == openmldb::type::TTLType::kAbsOrLat) { + ss << "ABSORLAT, TTL=(" << index.ttl().abs_ttl() << "m, " << index.ttl().lat_ttl() << ")"; + } + } + index_cnt++; + ss << ")"; + } + ss << "\n) "; + ss << "OPTIONS ("; + ss << "PARTITIONNUM=" << table_info.partition_num(); + ss << ", REPLICANUM=" << table_info.replica_num(); + if (table_info.storage_mode() == openmldb::common::StorageMode::kSSD) { + ss << ", STORAGE_MODE='SSD'"; + } else if (table_info.storage_mode() == openmldb::common::StorageMode::kHDD) { + ss << ", STORAGE_MODE='HDD'"; + } else { + ss << ", STORAGE_MODE='Memory'"; + } + ss << ");"; + return ss.str(); +} + +} // namespace sdk +} // namespace openmldb diff --git a/src/sdk/sdk_util.h b/src/sdk/sdk_util.h new file mode 100644 index 00000000000..c3c6df9e407 --- /dev/null +++ b/src/sdk/sdk_util.h @@ -0,0 +1,35 @@ +/* + * Copyright 2021 4Paradigm + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#ifndef SRC_SDK_SDK_UTIL_H_ +#define SRC_SDK_SDK_UTIL_H_ + +#include + +#include "proto/name_server.pb.h" + +namespace openmldb { +namespace sdk { + +class SDKUtil { + public: + static std::string GenCreateTableSQL(const ::openmldb::nameserver::TableInfo& table_info); +}; + +} // namespace sdk +} // namespace openmldb + +#endif // SRC_SDK_SDK_UTIL_H_ diff --git a/src/sdk/sdk_util_test.cc b/src/sdk/sdk_util_test.cc new file mode 100644 index 00000000000..c214f592cba --- /dev/null +++ b/src/sdk/sdk_util_test.cc @@ -0,0 +1,127 @@ +/* + * Copyright 2021 4Paradigm + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include + +#include "absl/strings/str_split.h" +#include "absl/strings/numbers.h" +#include "gtest/gtest.h" +#include "codec/schema_codec.h" +#include "sdk/sdk_util.h" + +namespace openmldb { +namespace sdk { + +class SDKUtilTest : public ::testing::Test { + public: + SDKUtilTest() {} + ~SDKUtilTest() {} +}; + +void SetColumnDesc(const std::vector>& col_vec, + ::openmldb::nameserver::TableInfo* table_info) { + table_info->clear_column_desc(); + for (const auto& col : col_vec) { + auto col_desc = table_info->add_column_desc(); + col_desc->set_name(col[0]); + col_desc->set_data_type(codec::DATA_TYPE_MAP.find(col[1])->second); + if (col.size() > 2 && col[2] == "no") { + col_desc->set_not_null(true); + } + if (col.size() > 3 && !col[3].empty()) { + col_desc->set_default_value(col[3]); + } + } +} + +void SetIndex(const std::vector>& index_vec, + ::openmldb::nameserver::TableInfo* table_info) { + table_info->clear_column_key(); + for (const auto& index_val : index_vec) { + auto index = table_info->add_column_key(); + index->set_index_name(index_val[0]); + std::vector list = absl::StrSplit(index_val[1], ","); + for (const auto& name : list) { + index->add_col_name(name); + } + if (!index_val[2].empty()) { + index->set_ts_name(index_val[2]); + } + auto ttl = index->mutable_ttl(); + int abs_ttl; + int lat_ttl; + ASSERT_TRUE(absl::SimpleAtoi(index_val[4], &abs_ttl)); + ASSERT_TRUE(absl::SimpleAtoi(index_val[5], &lat_ttl)); + if (index_val[3] == "absolute") { + ttl->set_ttl_type(openmldb::type::TTLType::kAbsoluteTime); + ttl->set_abs_ttl(abs_ttl); + } else if (index_val[3] == "latest") { + ttl->set_ttl_type(openmldb::type::TTLType::kLatestTime); + ttl->set_lat_ttl(lat_ttl); + } else if (index_val[3] == "absorlat") { + ttl->set_ttl_type(openmldb::type::TTLType::kAbsAndLat); + ttl->set_abs_ttl(abs_ttl); + ttl->set_lat_ttl(lat_ttl); + } else if (index_val[3] == "absandlat") { + ttl->set_ttl_type(openmldb::type::TTLType::kAbsOrLat); + ttl->set_abs_ttl(abs_ttl); + ttl->set_lat_ttl(lat_ttl); + } + } +} + +TEST_F(SDKUtilTest, GenCreateTableSQL) { + ::openmldb::nameserver::TableInfo table_info; + std::vector> col = { {"col1", "string"}, {"col2", "int"}, {"col3", "bigint", "no"}}; + std::vector> index = { {"index1", "col1", "", "absolute", "100", "0"}}; + SetColumnDesc(col, &table_info); + SetIndex(index, &table_info); + table_info.set_replica_num(1); + table_info.set_partition_num(1); + table_info.set_name("t1"); + std::string exp_ddl = "CREATE TABLE `t1` (\n" + "`col1` string,\n" + "`col2` int,\n" + "`col3` bigInt NOT NULL,\n" + "INDEX (KEY=`col1`, TTL_TYPE=ABSOLUTE, TTL=100m)\n" + ") OPTIONS (PARTITIONNUM=1, REPLICANUM=1, STORAGE_MODE='Memory');"; + ASSERT_EQ(SDKUtil::GenCreateTableSQL(table_info), exp_ddl); + std::vector> col1 = { {"col1", "string", "no", "aa"}, + {"col2", "int"}, {"col3", "timestamp"}}; + std::vector> index1 = { {"index1", "col1", "", "absolute", "100", "0"}, + {"index2", "col1,col2", "col3", "absorlat", "100", "10"}}; + SetColumnDesc(col1, &table_info); + SetIndex(index1, &table_info); + table_info.set_replica_num(3); + table_info.set_partition_num(8); + table_info.set_storage_mode(openmldb::common::StorageMode::kHDD); + exp_ddl = "CREATE TABLE `t1` (\n" + "`col1` string DEFAULT 'aa' NOT NULL,\n" + "`col2` int,\n" + "`col3` timestamp,\n" + "INDEX (KEY=`col1`, TTL_TYPE=ABSOLUTE, TTL=100m),\n" + "INDEX (KEY=(`col1`,`col2`), TS=`col3`, TTL_TYPE=ABSANDLAT, TTL=(100m, 10))\n" + ") OPTIONS (PARTITIONNUM=8, REPLICANUM=3, STORAGE_MODE='HDD');"; + ASSERT_EQ(SDKUtil::GenCreateTableSQL(table_info), exp_ddl); +} + +} // namespace sdk +} // namespace openmldb + +int main(int argc, char** argv) { + ::testing::InitGoogleTest(&argc, argv); + return RUN_ALL_TESTS(); +} diff --git a/src/sdk/sql_cluster_router.cc b/src/sdk/sql_cluster_router.cc index eea62b508ff..90054f277aa 100644 --- a/src/sdk/sql_cluster_router.cc +++ b/src/sdk/sql_cluster_router.cc @@ -55,6 +55,7 @@ #include "sdk/job_table_helper.h" #include "sdk/node_adapter.h" #include "sdk/result_set_sql.h" +#include "sdk/sdk_util.h" #include "sdk/split.h" #include "udf/udf.h" #include "vm/catalog.h" @@ -1625,15 +1626,37 @@ std::shared_ptr SQLClusterRouter::HandleSQLCmd(const h return ResultSetSQL::MakeResultSet({"Tables"}, values, status); } + case hybridse::node::kCmdShowCreateTable: { + auto& args = cmd_node->GetArgs(); + std::string cur_db = db; + std::string table_name; + if (!ParseNamesFromArgs(db, args, &cur_db, &table_name).IsOK()) { + *status = {StatusCode::kCmdError, msg}; + return {}; + } + if (cur_db.empty()) { + *status = {::hybridse::common::StatusCode::kCmdError, "please enter database first"}; + return {}; + } + auto table = cluster_sdk_->GetTableInfo(cur_db, table_name); + if (table == nullptr) { + *status = {StatusCode::kCmdError, "table " + table_name + " does not exist"}; + return {}; + } + std::string sql = SDKUtil::GenCreateTableSQL(*table); + std::vector> values; + std::vector vec = {table_name, sql}; + values.push_back(std::move(vec)); + return ResultSetSQL::MakeResultSet({"Table", "Create Table"}, values, status); + } + case hybridse::node::kCmdDescTable: { std::string cur_db = db; std::string table_name; const auto& args = cmd_node->GetArgs(); - if (args.size() > 1) { - cur_db = args[0]; - table_name = args[1]; - } else { - table_name = args[0]; + if (!ParseNamesFromArgs(db, args, &cur_db, &table_name).IsOK()) { + *status = {StatusCode::kCmdError, msg}; + return {}; } if (cur_db.empty()) { *status = {::hybridse::common::StatusCode::kCmdError, "please enter database first"}; @@ -2990,17 +3013,17 @@ ::hybridse::sdk::Status SQLClusterRouter::SetVariable(hybridse::node::SetPlanNod ::hybridse::sdk::Status SQLClusterRouter::ParseNamesFromArgs(const std::string& db, const std::vector& args, std::string* db_name, - std::string* sp_name) { + std::string* name) { if (args.size() == 1) { // only sp name, no db_name if (db.empty()) { return {StatusCode::kCmdError, "Please enter database first"}; } *db_name = db; - *sp_name = args[0]; + *name = args[0]; } else if (args.size() == 2) { *db_name = args[0]; - *sp_name = args[1]; + *name = args[1]; } else { return {StatusCode::kCmdError, "Invalid args"}; } diff --git a/src/sdk/sql_cluster_test.cc b/src/sdk/sql_cluster_test.cc index 359ac431573..70b6f7a20f2 100644 --- a/src/sdk/sql_cluster_test.cc +++ b/src/sdk/sql_cluster_test.cc @@ -257,6 +257,24 @@ TEST_F(SQLClusterDDLTest, CreateTableWithDatabase) { ASSERT_TRUE(router->DropDB(db2, &status)); } +TEST_F(SQLClusterDDLTest, ShowCreateTable) { + ::hybridse::sdk::Status status; + ASSERT_TRUE(router->ExecuteDDL(db, "drop table if exists t1;", &status)); + std::string ddl = "CREATE TABLE `t1` (\n" + "`col1` varchar,\n" + "`col2` int,\n" + "`col3` bigInt NOT NULL,\n" + "INDEX (KEY=`col1`, TTL_TYPE=ABSOLUTE, TTL=100m)\n" + ") OPTIONS (PARTITIONNUM=1, REPLICANUM=1, STORAGE_MODE='Memory');"; + ASSERT_TRUE(router->ExecuteDDL(db, ddl, &status)) << "ddl: " << ddl; + ASSERT_TRUE(router->RefreshCatalog()); + auto rs = router->ExecuteSQL(db, "show create table t1;", &status); + ASSERT_TRUE(status.IsOK()) << status.msg; + ASSERT_TRUE(rs->Next()); + ASSERT_EQ(ddl, rs->GetStringUnsafe(1)); + ASSERT_TRUE(router->ExecuteDDL(db, "drop table t1;", &status)); +} + TEST_F(SQLClusterDDLTest, CreateTableWithDatabaseWrongDDL) { std::string name = "test" + GenRand(); ::hybridse::sdk::Status status; diff --git a/third-party/cmake/FetchZetasql.cmake b/third-party/cmake/FetchZetasql.cmake index 09d4f3d6761..b2b1d580593 100644 --- a/third-party/cmake/FetchZetasql.cmake +++ b/third-party/cmake/FetchZetasql.cmake @@ -13,10 +13,10 @@ # limitations under the License. set(ZETASQL_HOME https://github.com/4paradigm/zetasql) -set(ZETASQL_VERSION 0.3.0) -set(ZETASQL_HASH_DARWIN 1b7e9c68d7fee29abf734be57934440b6891d4e80e22d8a92832518914373bea) -set(ZETASQL_HASH_LINUX_UBUNTU 0efb4feb822440e91ccd8c04d3a102cac9730745550168266b3544224fc86a63) -set(ZETASQL_HASH_LINUX_CENTOS 098ecb71b8a3dd7d8c6887d3b2b9306f0a130434f135754fd9930ccb11d80fed) +set(ZETASQL_VERSION 0.3.1) +set(ZETASQL_HASH_DARWIN 48bfdfe5fa91d414b0bf8383f116bc2a1f558c12fa286e49ea5ceede366dfbcf) +set(ZETASQL_HASH_LINUX_UBUNTU 3847ed7a60aeda1192adf7d702076d2db2bd49258992e2af67515a57b8f6f6a6) +set(ZETASQL_HASH_LINUX_CENTOS e73e6259ab2df3ae7289a9ae78600b69a8fbb6e4890d07a1031ccb1e37fa4281) set(ZETASQL_TAG v${ZETASQL_VERSION}) function(init_zetasql_urls) From 9077b86de86c8ffb4da874c1b781be3f26275cb0 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 17 Oct 2023 15:40:07 +0800 Subject: [PATCH 18/32] build(deps-dev): bump urllib3 from 1.26.12 to 1.26.17 in /docs (#3538) --- docs/poetry.lock | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/poetry.lock b/docs/poetry.lock index b2e0c52c7c0..fa522bb44da 100644 --- a/docs/poetry.lock +++ b/docs/poetry.lock @@ -670,17 +670,17 @@ test = ["coverage", "pytest", "pytest-cov"] [[package]] name = "urllib3" -version = "1.26.12" +version = "1.26.17" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, <4" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" files = [ - {file = "urllib3-1.26.12-py2.py3-none-any.whl", hash = "sha256:b930dd878d5a8afb066a637fbb35144fe7901e3b209d1cd4f524bd0e9deee997"}, - {file = "urllib3-1.26.12.tar.gz", hash = "sha256:3fa96cf423e6987997fc326ae8df396db2a8b7c667747d47ddd8ecba91f4a74e"}, + {file = "urllib3-1.26.17-py2.py3-none-any.whl", hash = "sha256:94a757d178c9be92ef5539b8840d48dc9cf1b2709c9d6b588232a055c524458b"}, + {file = "urllib3-1.26.17.tar.gz", hash = "sha256:24d6a242c28d29af46c3fae832c36db3bbebcc533dd1bb549172cd739c82df21"}, ] [package.extras] -brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"] +brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"] secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"] socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] From 3bb9df7495b31fff60e14e60ee7a7f93fad3a496 Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Tue, 17 Oct 2023 17:50:28 +0800 Subject: [PATCH 19/32] ci: reduce disk usage for java jobs (#3556) * build(java): dont pack resouces for source-jars Github runner has the limitation of disk usage of 14G, this should help reduce the disk usage on CI. * ci(sdk): reduce cache size for maven 1. don't include local installed openmldb jars, they are not dependency 2. don't fallback cache if key miss-match * fix: rm if dir not exists --- .github/workflows/sdk.yml | 9 +++++---- java/pom.xml | 5 ++++- 2 files changed, 9 insertions(+), 5 deletions(-) diff --git a/.github/workflows/sdk.yml b/.github/workflows/sdk.yml index ed78524a9f6..8f4dc6bd628 100644 --- a/.github/workflows/sdk.yml +++ b/.github/workflows/sdk.yml @@ -68,8 +68,6 @@ jobs: with: path: ~/.m2/repository key: ${{ runner.os }}-maven-${{ hashFiles('java/**/pom.xml') }} - restore-keys: | - ${{ runner.os }}-maven- - name: prepare release if: github.event_name == 'push' @@ -124,6 +122,7 @@ jobs: - name: maven coverage working-directory: java run: | + rm -rfv ~/.m2/repository/com/4paradigm/ ./mvnw --batch-mode prepare-package ./mvnw --batch-mode scoverage:report @@ -160,8 +159,6 @@ jobs: with: path: ~/.m2/repository key: ${{ runner.os }}-maven-${{ hashFiles('java/**/pom.xml') }} - restore-keys: | - ${{ runner.os }}-maven- - name: Cache thirdparty uses: actions/cache@v3 @@ -236,6 +233,10 @@ jobs: MAVEN_USERNAME: ${{ secrets.OSSRH_USERNAME }} MAVEN_TOKEN: ${{ secrets.OSSRH_TOKEN }} GPG_PASSPHRASE: ${{ secrets.GPG_PASSPHRASE }} + - name: cleanup + run: | + rm -rfv ~/.m2/repository/com/4paradigm/ + python-sdk: runs-on: ubuntu-latest diff --git a/java/pom.xml b/java/pom.xml index 00c893a4201..42ba84c34b8 100644 --- a/java/pom.xml +++ b/java/pom.xml @@ -355,7 +355,7 @@ org.apache.maven.plugins maven-source-plugin - 2.2.1 + 3.3.0 attach-sources @@ -364,6 +364,9 @@ + + true + org.apache.maven.plugins From 190992d3ce02067baab962c5c5bdd0d673503581 Mon Sep 17 00:00:00 2001 From: dl239 Date: Fri, 20 Oct 2023 14:57:55 +0800 Subject: [PATCH 20/32] fix: python mac sdk run failed (#3518) * fix: python mac * fix: fix comment --- onebox/stop_all.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/onebox/stop_all.sh b/onebox/stop_all.sh index 747adcdf929..7ba340228f3 100755 --- a/onebox/stop_all.sh +++ b/onebox/stop_all.sh @@ -17,7 +17,7 @@ set -x -e if [[ "$OSTYPE" = "darwin"* ]]; then - pkill -9 -x -l openmldb + pkill -9 -x -l openmldb || exit 0 else pgrep -a -f "openmldb.*onebox.*" | awk '{print $1}' | xargs -I {} kill -9 {} fi From 6fe2a30e5679e55e8ac6480a3df5c981e01ee8ca Mon Sep 17 00:00:00 2001 From: aceforeverd Date: Mon, 23 Oct 2023 21:43:22 +0800 Subject: [PATCH 21/32] fix(codegen): handle nullable for date type (#3543) * fix(codegen): handle nullable for date type Also fix include headers * fix(codegen): handle nulls for date and timestamp always returns allocated structure even it is null, for the cases: 1. construct timestamp from number, even number is < 0 2. construct date from timestamp, even timestamp is null --- cases/query/const_query.yaml | 12 +++++++++ hybridse/src/codegen/array_ir_builder.cc | 1 + hybridse/src/codegen/cast_expr_ir_builder.cc | 5 ++++ hybridse/src/codegen/date_ir_builder.cc | 19 ++++++++++---- hybridse/src/codegen/date_ir_builder.h | 22 +++++++--------- hybridse/src/codegen/ir_base_builder.h | 1 - hybridse/src/codegen/native_value.cc | 1 - .../src/codegen/predicate_expr_ir_builder.cc | 1 + hybridse/src/codegen/struct_ir_builder.h | 6 ++--- hybridse/src/codegen/timestamp_ir_builder.cc | 26 ++++++++++--------- hybridse/src/codegen/timestamp_ir_builder.h | 9 +++---- hybridse/src/codegen/type_ir_builder.cc | 1 + hybridse/src/codegen/type_ir_builder.h | 7 +++-- hybridse/src/codegen/udf_ir_builder.cc | 12 ++++----- hybridse/src/codegen/udf_ir_builder.h | 4 --- hybridse/src/udf/default_udf_library.cc | 13 ++-------- hybridse/src/udf/udf.cc | 15 +++-------- hybridse/src/udf/udf.h | 4 --- 18 files changed, 76 insertions(+), 83 deletions(-) diff --git a/cases/query/const_query.yaml b/cases/query/const_query.yaml index 38bbbeb5e47..5efe6fa3c29 100644 --- a/cases/query/const_query.yaml +++ b/cases/query/const_query.yaml @@ -126,3 +126,15 @@ cases: columns: ['c1 bool', 'c2 int16', 'c3 int', 'c4 double', 'c5 string', 'c6 date', 'c7 timestamp' ] rows: - [ true, 3, 13, 10.0, 'a string', '2020-05-22', 1590115420000 ] + - id: 10 + mode: procedure-unsupport + sql: | + select + datediff(Date(timestamp(-1)), Date("2021-05-01")) as out1, + datediff(Date(timestamp(-2177481600)), Date("2021-05-01")) as out2, + datediff(cast(NULL as date), Date("2021-05-01")) as out3 + ; + expect: + columns: ["out1 int", "out2 int", "out3 int"] + data: | + NULL, NULL, NULL diff --git a/hybridse/src/codegen/array_ir_builder.cc b/hybridse/src/codegen/array_ir_builder.cc index f07f551caf1..0788c1ba8aa 100644 --- a/hybridse/src/codegen/array_ir_builder.cc +++ b/hybridse/src/codegen/array_ir_builder.cc @@ -17,6 +17,7 @@ #include "codegen/array_ir_builder.h" #include +#include "codegen/ir_base_builder.h" namespace hybridse { namespace codegen { diff --git a/hybridse/src/codegen/cast_expr_ir_builder.cc b/hybridse/src/codegen/cast_expr_ir_builder.cc index 526a686ae66..bdb6329c6c8 100644 --- a/hybridse/src/codegen/cast_expr_ir_builder.cc +++ b/hybridse/src/codegen/cast_expr_ir_builder.cc @@ -126,6 +126,11 @@ Status CastExprIRBuilder::UnSafeCast(const NativeValue& value, StringIRBuilder string_ir_builder(block_->getModule()); CHECK_STATUS(string_ir_builder.CreateNull(block_, output)); return base::Status::OK(); + + } else if (TypeIRBuilder::IsDatePtr(type)) { + DateIRBuilder date_ir(block_->getModule()); + CHECK_STATUS(date_ir.CreateNull(block_, output)); + return base::Status::OK(); } else { *output = NativeValue::CreateNull(type); } diff --git a/hybridse/src/codegen/date_ir_builder.cc b/hybridse/src/codegen/date_ir_builder.cc index 65c439fd143..3a60147bd9a 100644 --- a/hybridse/src/codegen/date_ir_builder.cc +++ b/hybridse/src/codegen/date_ir_builder.cc @@ -19,6 +19,7 @@ #include #include "codegen/arithmetic_expr_ir_builder.h" #include "codegen/ir_base_builder.h" +#include "codegen/null_ir_builder.h" namespace hybridse { namespace codegen { @@ -43,6 +44,15 @@ void DateIRBuilder::InitStructType() { struct_type_ = stype; return; } + +base::Status DateIRBuilder::CreateNull(::llvm::BasicBlock* block, NativeValue* output) { + ::llvm::Value* value = nullptr; + CHECK_TRUE(CreateDefault(block, &value), common::kCodegenError, "Fail to construct string") + ::llvm::IRBuilder<> builder(block); + *output = NativeValue::CreateWithFlag(value, builder.getInt1(true)); + return base::Status::OK(); +} + bool DateIRBuilder::CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) { return NewDate(block, output); @@ -123,11 +133,10 @@ base::Status DateIRBuilder::CastFrom(::llvm::BasicBlock* block, auto cast_func = m_->getOrInsertFunction( fn_name, ::llvm::FunctionType::get(builder.getVoidTy(), - {src.GetType(), dist->getType(), - builder.getInt1Ty()->getPointerTo()}, - false)); - builder.CreateCall(cast_func, - {src.GetValue(&builder), dist, is_null_ptr}); + {src.GetType(), dist->getType(), builder.getInt1Ty()->getPointerTo()}, false)); + + builder.CreateCall(cast_func, {src.GetValue(&builder), dist, is_null_ptr}); + ::llvm::Value* should_return_null = builder.CreateLoad(is_null_ptr); null_ir_builder.CheckAnyNull(block, src, &should_return_null); *output = NativeValue::CreateWithFlag(dist, should_return_null); diff --git a/hybridse/src/codegen/date_ir_builder.h b/hybridse/src/codegen/date_ir_builder.h index cb41dc5f263..b44b039d57d 100644 --- a/hybridse/src/codegen/date_ir_builder.h +++ b/hybridse/src/codegen/date_ir_builder.h @@ -16,13 +16,9 @@ #ifndef HYBRIDSE_SRC_CODEGEN_DATE_IR_BUILDER_H_ #define HYBRIDSE_SRC_CODEGEN_DATE_IR_BUILDER_H_ + #include "base/fe_status.h" -#include "codegen/cast_expr_ir_builder.h" -#include "codegen/null_ir_builder.h" -#include "codegen/scope_var.h" #include "codegen/struct_ir_builder.h" -#include "llvm/IR/IRBuilder.h" -#include "proto/fe_type.pb.h" namespace hybridse { namespace codegen { @@ -31,17 +27,17 @@ class DateIRBuilder : public StructTypeIRBuilder { public: explicit DateIRBuilder(::llvm::Module* m); ~DateIRBuilder(); - void InitStructType(); - bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output); + void InitStructType() override; + + base::Status CreateNull(::llvm::BasicBlock* block, NativeValue* output); + bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output) override; + bool NewDate(::llvm::BasicBlock* block, ::llvm::Value** output); bool NewDate(::llvm::BasicBlock* block, ::llvm::Value* date, ::llvm::Value** output); - bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, - ::llvm::Value* dist); - base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, - NativeValue* output); - base::Status CastFrom(::llvm::BasicBlock* block, ::llvm::Value* src, - ::llvm::Value** output); + bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist); + base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, NativeValue* output); + bool GetDate(::llvm::BasicBlock* block, ::llvm::Value* date, ::llvm::Value** output); bool SetDate(::llvm::BasicBlock* block, ::llvm::Value* date, diff --git a/hybridse/src/codegen/ir_base_builder.h b/hybridse/src/codegen/ir_base_builder.h index c52bba23431..db2075289cf 100644 --- a/hybridse/src/codegen/ir_base_builder.h +++ b/hybridse/src/codegen/ir_base_builder.h @@ -19,7 +19,6 @@ #include #include -#include "glog/logging.h" #include "llvm/IR/IRBuilder.h" #include "node/sql_node.h" #include "node/type_node.h" diff --git a/hybridse/src/codegen/native_value.cc b/hybridse/src/codegen/native_value.cc index c4c6e2e562a..fce4f0bb5bb 100644 --- a/hybridse/src/codegen/native_value.cc +++ b/hybridse/src/codegen/native_value.cc @@ -17,7 +17,6 @@ #include "codegen/native_value.h" #include #include -#include #include "codegen/context.h" #include "codegen/ir_base_builder.h" diff --git a/hybridse/src/codegen/predicate_expr_ir_builder.cc b/hybridse/src/codegen/predicate_expr_ir_builder.cc index aaf0fb0753c..45ed8f7ec21 100644 --- a/hybridse/src/codegen/predicate_expr_ir_builder.cc +++ b/hybridse/src/codegen/predicate_expr_ir_builder.cc @@ -17,6 +17,7 @@ #include "codegen/predicate_expr_ir_builder.h" #include "codegen/date_ir_builder.h" #include "codegen/ir_base_builder.h" +#include "codegen/null_ir_builder.h" #include "codegen/string_ir_builder.h" #include "codegen/timestamp_ir_builder.h" #include "codegen/type_ir_builder.h" diff --git a/hybridse/src/codegen/struct_ir_builder.h b/hybridse/src/codegen/struct_ir_builder.h index 2f1f94d036c..e306dfe869e 100644 --- a/hybridse/src/codegen/struct_ir_builder.h +++ b/hybridse/src/codegen/struct_ir_builder.h @@ -16,12 +16,10 @@ #ifndef HYBRIDSE_SRC_CODEGEN_STRUCT_IR_BUILDER_H_ #define HYBRIDSE_SRC_CODEGEN_STRUCT_IR_BUILDER_H_ + #include "base/fe_status.h" -#include "codegen/cast_expr_ir_builder.h" -#include "codegen/scope_var.h" +#include "codegen/native_value.h" #include "codegen/type_ir_builder.h" -#include "llvm/IR/IRBuilder.h" -#include "proto/fe_type.pb.h" namespace hybridse { namespace codegen { diff --git a/hybridse/src/codegen/timestamp_ir_builder.cc b/hybridse/src/codegen/timestamp_ir_builder.cc index 13d6e065f39..f14952f455c 100644 --- a/hybridse/src/codegen/timestamp_ir_builder.cc +++ b/hybridse/src/codegen/timestamp_ir_builder.cc @@ -15,14 +15,15 @@ */ #include "codegen/timestamp_ir_builder.h" + #include #include + #include "codegen/arithmetic_expr_ir_builder.h" #include "codegen/ir_base_builder.h" #include "codegen/null_ir_builder.h" #include "codegen/predicate_expr_ir_builder.h" #include "glog/logging.h" -#include "node/sql_node.h" using hybridse::common::kCodegenError; @@ -70,29 +71,30 @@ base::Status TimestampIRBuilder::CastFrom(::llvm::BasicBlock* block, CondSelectIRBuilder cond_ir_builder; PredicateIRBuilder predicate_ir_builder(block); NullIRBuilder null_ir_builder; + + // always allocate for returned timestmap even it is null + ::llvm::Value* dist = nullptr; + if (!CreateDefault(block, &dist)) { + status.code = common::kCodegenError; + status.msg = "Fail to cast date: create default date fail"; + return status; + } + if (IsNumber(src.GetType())) { CHECK_STATUS(cast_builder.Cast(src, builder.getInt64Ty(), &ts)); NativeValue cond; CHECK_STATUS(predicate_ir_builder.BuildGeExpr( ts, NativeValue::Create(builder.getInt64(0)), &cond)); - ::llvm::Value* timestamp; - CHECK_TRUE(NewTimestamp(block, ts.GetValue(&builder), ×tamp), + CHECK_TRUE(SetTs(block, dist, ts.GetValue(&builder)), kCodegenError, "Fail to cast timestamp: new timestamp(ts) fail"); - CHECK_STATUS( - cond_ir_builder.Select(block, cond, NativeValue::Create(timestamp), - NativeValue::CreateNull(GetType()), output)); + CHECK_STATUS(cond_ir_builder.Select(block, cond, NativeValue::Create(dist), + NativeValue::CreateWithFlag(dist, builder.getInt1(true)), output)); } else if (IsStringPtr(src.GetType()) || IsDatePtr(src.GetType())) { ::llvm::IRBuilder<> builder(block); - ::llvm::Value* dist = nullptr; ::llvm::Value* is_null_ptr = CreateAllocaAtHead( &builder, builder.getInt1Ty(), "timestamp_is_null_alloca"); - if (!CreateDefault(block, &dist)) { - status.code = common::kCodegenError; - status.msg = "Fail to cast date: create default date fail"; - return status; - } ::std::string fn_name = "timestamp." + TypeName(src.GetType()); auto cast_func = m_->getOrInsertFunction( diff --git a/hybridse/src/codegen/timestamp_ir_builder.h b/hybridse/src/codegen/timestamp_ir_builder.h index 33de3cce2e5..84051979597 100644 --- a/hybridse/src/codegen/timestamp_ir_builder.h +++ b/hybridse/src/codegen/timestamp_ir_builder.h @@ -16,12 +16,9 @@ #ifndef HYBRIDSE_SRC_CODEGEN_TIMESTAMP_IR_BUILDER_H_ #define HYBRIDSE_SRC_CODEGEN_TIMESTAMP_IR_BUILDER_H_ + #include "base/fe_status.h" -#include "codegen/cast_expr_ir_builder.h" -#include "codegen/scope_var.h" #include "codegen/struct_ir_builder.h" -#include "llvm/IR/IRBuilder.h" -#include "proto/fe_type.pb.h" namespace hybridse { namespace codegen { @@ -33,8 +30,8 @@ class TimestampIRBuilder : public StructTypeIRBuilder { void InitStructType(); bool CreateDefault(::llvm::BasicBlock* block, ::llvm::Value** output); bool NewTimestamp(::llvm::BasicBlock* block, ::llvm::Value** output); - bool NewTimestamp(::llvm::BasicBlock* block, ::llvm::Value* ts, - ::llvm::Value** output); + bool NewTimestamp(::llvm::BasicBlock* block, ::llvm::Value* ts, ::llvm::Value** output); + bool CopyFrom(::llvm::BasicBlock* block, ::llvm::Value* src, ::llvm::Value* dist); base::Status CastFrom(::llvm::BasicBlock* block, const NativeValue& src, diff --git a/hybridse/src/codegen/type_ir_builder.cc b/hybridse/src/codegen/type_ir_builder.cc index 3fcd5891c4c..bbdf1346995 100644 --- a/hybridse/src/codegen/type_ir_builder.cc +++ b/hybridse/src/codegen/type_ir_builder.cc @@ -15,6 +15,7 @@ */ #include "codegen/type_ir_builder.h" + #include "codegen/ir_base_builder.h" #include "glog/logging.h" #include "node/node_manager.h" diff --git a/hybridse/src/codegen/type_ir_builder.h b/hybridse/src/codegen/type_ir_builder.h index e06e77244e6..ad7d5f225b9 100644 --- a/hybridse/src/codegen/type_ir_builder.h +++ b/hybridse/src/codegen/type_ir_builder.h @@ -18,11 +18,10 @@ #define HYBRIDSE_SRC_CODEGEN_TYPE_IR_BUILDER_H_ #include -#include + #include "base/fe_status.h" -#include "codec/fe_row_codec.h" -#include "codegen/ir_base_builder.h" -#include "node/node_enum.h" +#include "llvm/IR/Module.h" +#include "llvm/IR/Type.h" #include "node/sql_node.h" #include "node/type_node.h" diff --git a/hybridse/src/codegen/udf_ir_builder.cc b/hybridse/src/codegen/udf_ir_builder.cc index 6d6f967a83e..5030f3cd8ae 100644 --- a/hybridse/src/codegen/udf_ir_builder.cc +++ b/hybridse/src/codegen/udf_ir_builder.cc @@ -15,19 +15,17 @@ */ #include "codegen/udf_ir_builder.h" -#include -#include + #include + #include "codegen/context.h" -#include "codegen/date_ir_builder.h" #include "codegen/fn_ir_builder.h" +#include "codegen/ir_base_builder.h" #include "codegen/list_ir_builder.h" #include "codegen/null_ir_builder.h" -#include "codegen/timestamp_ir_builder.h" +#include "codegen/type_ir_builder.h" #include "llvm/IR/Attributes.h" -#include "node/node_manager.h" #include "node/sql_node.h" -#include "udf/udf.h" #include "udf/udf_registry.h" using ::hybridse::common::kCodegenError; @@ -162,7 +160,7 @@ Status UdfIRBuilder::BuildLambdaCall( Status UdfIRBuilder::BuildCodeGenUdfCall( const node::UdfByCodeGenDefNode* fn, const std::vector& args, NativeValue* output) { - auto gen_impl = fn->GetGenImpl(); + std::shared_ptr gen_impl = fn->GetGenImpl(); ::llvm::Value* ret_null = nullptr; for (size_t i = 0; i < fn->GetArgSize(); ++i) { diff --git a/hybridse/src/codegen/udf_ir_builder.h b/hybridse/src/codegen/udf_ir_builder.h index ed15b6432c7..9e33837bf96 100644 --- a/hybridse/src/codegen/udf_ir_builder.h +++ b/hybridse/src/codegen/udf_ir_builder.h @@ -17,13 +17,9 @@ #ifndef HYBRIDSE_SRC_CODEGEN_UDF_IR_BUILDER_H_ #define HYBRIDSE_SRC_CODEGEN_UDF_IR_BUILDER_H_ -#include -#include #include #include "base/fe_status.h" #include "codegen/expr_ir_builder.h" -#include "codegen/scope_var.h" -#include "llvm/IR/Module.h" #include "node/sql_node.h" namespace hybridse { diff --git a/hybridse/src/udf/default_udf_library.cc b/hybridse/src/udf/default_udf_library.cc index 8b98212fffb..fef776d3ffd 100644 --- a/hybridse/src/udf/default_udf_library.cc +++ b/hybridse/src/udf/default_udf_library.cc @@ -26,7 +26,6 @@ #include #include -#include "absl/strings/str_cat.h" #include "codegen/date_ir_builder.h" #include "codegen/string_ir_builder.h" #include "codegen/timestamp_ir_builder.h" @@ -2169,11 +2168,7 @@ void DefaultUdfLibrary::InitTypeUdf() { )"); RegisterExternal("date") - .args(reinterpret_cast( - static_cast( - v1::timestamp_to_date))) - .return_by_arg(true) - .returns>() + .args(v1::timestamp_to_date) .doc(R"( @brief Cast timestamp or string expression to date (date >= 1900-01-01) @@ -2192,11 +2187,7 @@ void DefaultUdfLibrary::InitTypeUdf() { @endcode @since 0.1.0)"); RegisterExternal("date") - .args(reinterpret_cast( - static_cast( - v1::string_to_date))) - .return_by_arg(true) - .returns>(); + .args(v1::string_to_date); RegisterExternal("timestamp") .args(reinterpret_cast( diff --git a/hybridse/src/udf/udf.cc b/hybridse/src/udf/udf.cc index 2ec7033472f..9326d576685 100644 --- a/hybridse/src/udf/udf.cc +++ b/hybridse/src/udf/udf.cc @@ -20,8 +20,6 @@ #include #include -#include -#include #include #include "absl/strings/ascii.h" @@ -29,20 +27,17 @@ #include "absl/time/civil_time.h" #include "absl/time/time.h" #include "base/iterator.h" -#include "boost/date_time.hpp" +#include "boost/date_time/gregorian/conversion.hpp" #include "boost/date_time/gregorian/parsers.hpp" -#include "boost/date_time/posix_time/posix_time.hpp" #include "bthread/types.h" -#include "codec/list_iterator_codec.h" #include "codec/row.h" #include "codec/type_codec.h" -#include "codegen/fn_ir_builder.h" #include "farmhash.h" #include "node/node_manager.h" #include "node/sql_node.h" #include "re2/re2.h" -#include "udf/default_udf_library.h" #include "udf/literal_traits.h" +#include "udf/udf_library.h" #include "vm/jit_runtime.h" namespace hybridse { @@ -394,8 +389,7 @@ void bool_to_string(bool v, StringRef *output) { } } -void timestamp_to_date(Timestamp *timestamp, - Date *output, bool *is_null) { +void timestamp_to_date(Timestamp *timestamp, Date *output, bool *is_null) { time_t time = (timestamp->ts_ + TZ_OFFSET) / 1000; struct tm t; memset(&t, 0, sizeof(struct tm)); @@ -771,8 +765,7 @@ void string_to_double(StringRef *str, double *out, bool *is_null_ptr) { } return; } -void string_to_date(StringRef *str, Date *output, - bool *is_null) { +void string_to_date(StringRef *str, Date *output, bool *is_null) { if (19 == str->size_) { struct tm timeinfo; memset(&timeinfo, 0, sizeof(struct tm)); diff --git a/hybridse/src/udf/udf.h b/hybridse/src/udf/udf.h index a761e99f88b..c91b78d1c90 100644 --- a/hybridse/src/udf/udf.h +++ b/hybridse/src/udf/udf.h @@ -26,10 +26,6 @@ #include "absl/strings/ascii.h" #include "base/string_ref.h" #include "base/type.h" -#include "codec/list_iterator_codec.h" -#include "codec/type_codec.h" -#include "node/node_manager.h" -#include "proto/fe_type.pb.h" #include "udf/literal_traits.h" #include "udf/openmldb_udf.h" From d2467ea45abcffa109745e7a704143dc838764fd Mon Sep 17 00:00:00 2001 From: TanZiYen <104113819+TanZiYen@users.noreply.github.com> Date: Thu, 26 Oct 2023 14:27:31 +0800 Subject: [PATCH 22/32] docs: remove the export tool doc from the maintain folder (en) --- docs/en/maintain/data_export.md | 58 --------------------------------- 1 file changed, 58 deletions(-) delete mode 100644 docs/en/maintain/data_export.md diff --git a/docs/en/maintain/data_export.md b/docs/en/maintain/data_export.md deleted file mode 100644 index 0916a8bc553..00000000000 --- a/docs/en/maintain/data_export.md +++ /dev/null @@ -1,58 +0,0 @@ -# Data Export Tool - -Data Export Tool locates in [src/tools](https://github.com/4paradigm/OpenMLDB/tree/main/src/tools)。It supports exporting data from remote machines in standalone mode or cluster mode. - -## 1. Build - -Generate the Unix Executable file：`make` under src folder. - -## 2. Data Export Usage - -### 2.1 Command Line Arguments - -All configurations are showed as follows, * indicates required configurations. - -``` -Usage: ./data_exporter [--delimiter=] --db_name= - [--user_name=] --table_name= - --config_path= - -* --db_name= openmldb database name -* --table_name= openmldb table name of the selected database -* --config_path= absolute or relative path of the config file - --delimiter= delimiter for the output csv, default is ',' - --user_name= user name of the remote machine -``` - -### 2.2 Important Configurations Instructions - -Descriptions of the important configurations: - -- `--db_name=`: OpenMLDB database name. The database must exist, otherwise would return an error message: database not found. -- `--table_name=`: table name. 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