Support SHOW ALL VERBOSE to show settings description (#7735)

* Expand SHOW ALL stmt to show settings description

* cli tests

* comments

datafusion-cli/tests/cli_integration.rs

@@ -43,7 +43,7 @@ fn init() {
 )]
 #[case::set_batch_size(
     ["--command", "show datafusion.execution.batch_size", "--format", "json", "-q", "-b", "1"],
-    "[{\"name\":\"datafusion.execution.batch_size\",\"setting\":\"1\"}]\n"
+    "[{\"name\":\"datafusion.execution.batch_size\",\"value\":\"1\"}]\n"
 )]
 #[test]
 fn cli_quick_test<'a>(

datafusion/core/src/catalog/information_schema.rs

@@ -626,7 +626,8 @@ impl InformationSchemaDfSettings {
     fn new(config: InformationSchemaConfig) -> Self {
         let schema = Arc::new(Schema::new(vec![
             Field::new("name", DataType::Utf8, false),
-            Field::new("setting", DataType::Utf8, true),
+            Field::new("value", DataType::Utf8, true),
+            Field::new("description", DataType::Utf8, true),
         ]));
 
         Self { schema, config }
@@ -635,7 +636,8 @@ impl InformationSchemaDfSettings {
     fn builder(&self) -> InformationSchemaDfSettingsBuilder {
         InformationSchemaDfSettingsBuilder {
             names: StringBuilder::new(),
-            settings: StringBuilder::new(),
+            values: StringBuilder::new(),
+            descriptions: StringBuilder::new(),
             schema: self.schema.clone(),
         }
     }
@@ -664,21 +666,24 @@ impl PartitionStream for InformationSchemaDfSettings {
 struct InformationSchemaDfSettingsBuilder {
     schema: SchemaRef,
     names: StringBuilder,
-    settings: StringBuilder,
+    values: StringBuilder,
+    descriptions: StringBuilder,
 }
 
 impl InformationSchemaDfSettingsBuilder {
     fn add_setting(&mut self, entry: ConfigEntry) {
         self.names.append_value(entry.key);
-        self.settings.append_option(entry.value);
+        self.values.append_option(entry.value);
+        self.descriptions.append_value(entry.description);
     }
 
     fn finish(&mut self) -> RecordBatch {
         RecordBatch::try_new(
             self.schema.clone(),
             vec![
                 Arc::new(self.names.finish()),
-                Arc::new(self.settings.finish()),
+                Arc::new(self.values.finish()),
+                Arc::new(self.descriptions.finish()),
             ],
         )
         .unwrap()

datafusion/sql/src/statement.rs

@@ -757,28 +757,34 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
     }
 
     fn show_variable_to_plan(&self, variable: &[Ident]) -> Result<LogicalPlan> {
-        let variable = object_name_to_string(&ObjectName(variable.to_vec()));
-
         if !self.has_table("information_schema", "df_settings") {
             return plan_err!(
                 "SHOW [VARIABLE] is not supported unless information_schema is enabled"
             );
         }
 
-        let variable_lower = variable.to_lowercase();
+        let verbose = variable
+            .last()
+            .map(|s| ident_to_string(s) == "verbose")
+            .unwrap_or(false);
+        let mut variable_vec = variable.to_vec();
+        let mut columns: String = "name, value".to_owned();
+
+        if verbose {
+            columns = format!("{columns}, description");
+            variable_vec = variable_vec.split_at(variable_vec.len() - 1).0.to_vec();
+        }
 
-        let query = if variable_lower == "all" {
+        let variable = object_name_to_string(&ObjectName(variable_vec));
+        let base_query = format!("SELECT {columns} FROM information_schema.df_settings");
+        let query = if variable == "all" {
             // Add an ORDER BY so the output comes out in a consistent order
-            String::from(
-                "SELECT name, setting FROM information_schema.df_settings ORDER BY name",
-            )
-        } else if variable_lower == "timezone" || variable_lower == "time.zone" {
+            format!("{base_query} ORDER BY name")
+        } else if variable == "timezone" || variable == "time.zone" {
             // we could introduce alias in OptionDefinition if this string matching thing grows
-            String::from("SELECT name, setting FROM information_schema.df_settings WHERE name = 'datafusion.execution.time_zone'")
+            format!("{base_query} WHERE name = 'datafusion.execution.time_zone'")
         } else {
-            format!(
-                "SELECT name, setting FROM information_schema.df_settings WHERE name = '{variable}'"
-            )
+            format!("{base_query} WHERE name = '{variable}'")
         };
 
         let mut rewrite = DFParser::parse_sql(&query)?;

datafusion/sqllogictest/test_files/information_schema.slt

@@ -202,12 +202,85 @@ datafusion.sql_parser.dialect generic
 datafusion.sql_parser.enable_ident_normalization true
 datafusion.sql_parser.parse_float_as_decimal false
 
+# show all variables with verbose
+query TTT rowsort
+SHOW ALL VERBOSE
+----
+datafusion.catalog.create_default_catalog_and_schema true Whether the default catalog and schema should be created automatically.
+datafusion.catalog.default_catalog datafusion The default catalog name - this impacts what SQL queries use if not specified
+datafusion.catalog.default_schema public The default schema name - this impacts what SQL queries use if not specified
+datafusion.catalog.format NULL Type of `TableProvider` to use when loading `default` schema
+datafusion.catalog.has_header false If the file has a header
+datafusion.catalog.information_schema true Should DataFusion provide access to `information_schema` virtual tables for displaying schema information
+datafusion.catalog.location NULL Location scanned to load tables for `default` schema
+datafusion.execution.aggregate.scalar_update_factor 10 Specifies the threshold for using `ScalarValue`s to update accumulators during high-cardinality aggregations for each input batch. The aggregation is considered high-cardinality if the number of affected groups is greater than or equal to `batch_size / scalar_update_factor`. In such cases, `ScalarValue`s are utilized for updating accumulators, rather than the default batch-slice approach. This can lead to performance improvements. By adjusting the `scalar_update_factor`, you can balance the trade-off between more efficient accumulator updates and the number of groups affected.
+datafusion.execution.batch_size 8192 Default batch size while creating new batches, it's especially useful for buffer-in-memory batches since creating tiny batches would result in too much metadata memory consumption
+datafusion.execution.coalesce_batches true When set to true, record batches will be examined between each operator and small batches will be coalesced into larger batches. This is helpful when there are highly selective filters or joins that could produce tiny output batches. The target batch size is determined by the configuration setting
+datafusion.execution.collect_statistics false Should DataFusion collect statistics after listing files
+datafusion.execution.meta_fetch_concurrency 32 Number of files to read in parallel when inferring schema and statistics
+datafusion.execution.parquet.allow_single_file_parallelism false Controls whether DataFusion will attempt to speed up writing large parquet files by first writing multiple smaller files and then stitching them together into a single large file. This will result in faster write speeds, but higher memory usage. Also currently unsupported are bloom filters and column indexes when single_file_parallelism is enabled.
+datafusion.execution.parquet.bloom_filter_enabled false Sets if bloom filter is enabled for any column
+datafusion.execution.parquet.bloom_filter_fpp NULL Sets bloom filter false positive probability. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.bloom_filter_ndv NULL Sets bloom filter number of distinct values. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.column_index_truncate_length NULL Sets column index trucate length
+datafusion.execution.parquet.compression zstd(3) Sets default parquet compression codec Valid values are: uncompressed, snappy, gzip(level), lzo, brotli(level), lz4, zstd(level), and lz4_raw. These values are not case sensitive. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.created_by datafusion Sets "created by" property
+datafusion.execution.parquet.data_page_row_count_limit 18446744073709551615 Sets best effort maximum number of rows in data page
+datafusion.execution.parquet.data_pagesize_limit 1048576 Sets best effort maximum size of data page in bytes
+datafusion.execution.parquet.dictionary_enabled NULL Sets if dictionary encoding is enabled. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.dictionary_page_size_limit 1048576 Sets best effort maximum dictionary page size, in bytes
+datafusion.execution.parquet.enable_page_index true If true, reads the Parquet data page level metadata (the Page Index), if present, to reduce the I/O and number of rows decoded.
+datafusion.execution.parquet.encoding NULL Sets default encoding for any column Valid values are: plain, plain_dictionary, rle, bit_packed, delta_binary_packed, delta_length_byte_array, delta_byte_array, rle_dictionary, and byte_stream_split. These values are not case sensitive. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.max_row_group_size 1048576 Sets maximum number of rows in a row group
+datafusion.execution.parquet.max_statistics_size NULL Sets max statistics size for any column. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.metadata_size_hint NULL If specified, the parquet reader will try and fetch the last `size_hint` bytes of the parquet file optimistically. If not specified, two reads are required: One read to fetch the 8-byte parquet footer and another to fetch the metadata length encoded in the footer
+datafusion.execution.parquet.pruning true If true, the parquet reader attempts to skip entire row groups based on the predicate in the query and the metadata (min/max values) stored in the parquet file
+datafusion.execution.parquet.pushdown_filters false If true, filter expressions are be applied during the parquet decoding operation to reduce the number of rows decoded
+datafusion.execution.parquet.reorder_filters false If true, filter expressions evaluated during the parquet decoding operation will be reordered heuristically to minimize the cost of evaluation. If false, the filters are applied in the same order as written in the query
+datafusion.execution.parquet.skip_metadata true If true, the parquet reader skip the optional embedded metadata that may be in the file Schema. This setting can help avoid schema conflicts when querying multiple parquet files with schemas containing compatible types but different metadata
+datafusion.execution.parquet.statistics_enabled NULL Sets if statistics are enabled for any column Valid values are: "none", "chunk", and "page" These values are not case sensitive. If NULL, uses default parquet writer setting
+datafusion.execution.parquet.write_batch_size 1024 Sets write_batch_size in bytes
+datafusion.execution.parquet.writer_version 1.0 Sets parquet writer version valid values are "1.0" and "2.0"
+datafusion.execution.planning_concurrency 13 Fan-out during initial physical planning. This is mostly use to plan `UNION` children in parallel. Defaults to the number of CPU cores on the system
+datafusion.execution.sort_in_place_threshold_bytes 1048576 When sorting, below what size should data be concatenated and sorted in a single RecordBatch rather than sorted in batches and merged.
+datafusion.execution.sort_spill_reservation_bytes 10485760 Specifies the reserved memory for each spillable sort operation to facilitate an in-memory merge. When a sort operation spills to disk, the in-memory data must be sorted and merged before being written to a file. This setting reserves a specific amount of memory for that in-memory sort/merge process. Note: This setting is irrelevant if the sort operation cannot spill (i.e., if there's no `DiskManager` configured).
+datafusion.execution.target_partitions 7 Number of partitions for query execution. Increasing partitions can increase concurrency. Defaults to the number of CPU cores on the system
+datafusion.execution.time_zone +00:00 The default time zone Some functions, e.g. `EXTRACT(HOUR from SOME_TIME)`, shift the underlying datetime according to this time zone, and then extract the hour
+datafusion.explain.logical_plan_only false When set to true, the explain statement will only print logical plans
+datafusion.explain.physical_plan_only false When set to true, the explain statement will only print physical plans
+datafusion.explain.show_statistics false When set to true, the explain statement will print operator statistics for physical plans
+datafusion.optimizer.allow_symmetric_joins_without_pruning true Should DataFusion allow symmetric hash joins for unbounded data sources even when its inputs do not have any ordering or filtering If the flag is not enabled, the SymmetricHashJoin operator will be unable to prune its internal buffers, resulting in certain join types - such as Full, Left, LeftAnti, LeftSemi, Right, RightAnti, and RightSemi - being produced only at the end of the execution. This is not typical in stream processing. Additionally, without proper design for long runner execution, all types of joins may encounter out-of-memory errors.
+datafusion.optimizer.enable_round_robin_repartition true When set to true, the physical plan optimizer will try to add round robin repartitioning to increase parallelism to leverage more CPU cores
+datafusion.optimizer.enable_topk_aggregation true When set to true, the optimizer will attempt to perform limit operations during aggregations, if possible
+datafusion.optimizer.filter_null_join_keys false When set to true, the optimizer will insert filters before a join between a nullable and non-nullable column to filter out nulls on the nullable side. This filter can add additional overhead when the file format does not fully support predicate push down.
+datafusion.optimizer.hash_join_single_partition_threshold 1048576 The maximum estimated size in bytes for one input side of a HashJoin will be collected into a single partition
+datafusion.optimizer.max_passes 3 Number of times that the optimizer will attempt to optimize the plan
+datafusion.optimizer.prefer_existing_sort false When true, DataFusion will opportunistically remove sorts when the data is already sorted, (i.e. setting `preserve_order` to true on `RepartitionExec`  and using `SortPreservingMergeExec`) When false, DataFusion will maximize plan parallelism using `RepartitionExec` even if this requires subsequently resorting data using a `SortExec`.
+datafusion.optimizer.prefer_hash_join true When set to true, the physical plan optimizer will prefer HashJoin over SortMergeJoin. HashJoin can work more efficiently than SortMergeJoin but consumes more memory
+datafusion.optimizer.repartition_aggregations true Should DataFusion repartition data using the aggregate keys to execute aggregates in parallel using the provided `target_partitions` level
+datafusion.optimizer.repartition_file_min_size 10485760 Minimum total files size in bytes to perform file scan repartitioning.
+datafusion.optimizer.repartition_file_scans true When set to `true`, file groups will be repartitioned to achieve maximum parallelism. Currently Parquet and CSV formats are supported. If set to `true`, all files will be repartitioned evenly (i.e., a single large file might be partitioned into smaller chunks) for parallel scanning. If set to `false`, different files will be read in parallel, but repartitioning won't happen within a single file.
+datafusion.optimizer.repartition_joins true Should DataFusion repartition data using the join keys to execute joins in parallel using the provided `target_partitions` level
+datafusion.optimizer.repartition_sorts true Should DataFusion execute sorts in a per-partition fashion and merge afterwards instead of coalescing first and sorting globally. With this flag is enabled, plans in the form below ```text      "SortExec: [a@0 ASC]",      "  CoalescePartitionsExec",      "    RepartitionExec: partitioning=RoundRobinBatch(8), input_partitions=1", ``` would turn into the plan below which performs better in multithreaded environments ```text      "SortPreservingMergeExec: [a@0 ASC]",      "  SortExec: [a@0 ASC]",      "    RepartitionExec: partitioning=RoundRobinBatch(8), input_partitions=1", ```
+datafusion.optimizer.repartition_windows true Should DataFusion repartition data using the partitions keys to execute window functions in parallel using the provided `target_partitions` level
+datafusion.optimizer.skip_failed_rules false When set to true, the logical plan optimizer will produce warning messages if any optimization rules produce errors and then proceed to the next rule. When set to false, any rules that produce errors will cause the query to fail
+datafusion.optimizer.top_down_join_key_reordering true When set to true, the physical plan optimizer will run a top down process to reorder the join keys
+datafusion.sql_parser.dialect generic Configure the SQL dialect used by DataFusion's parser; supported values include: Generic, MySQL, PostgreSQL, Hive, SQLite, Snowflake, Redshift, MsSQL, ClickHouse, BigQuery, and Ansi.
+datafusion.sql_parser.enable_ident_normalization true When set to true, SQL parser will normalize ident (convert ident to lowercase when not quoted)
+datafusion.sql_parser.parse_float_as_decimal false When set to true, SQL parser will parse float as decimal type
+
 # show_variable_in_config_options
 query TT
 SHOW datafusion.execution.batch_size
 ----
 datafusion.execution.batch_size 8192
 
+# show_variable_in_config_options_verbose
+query TTT
+SHOW datafusion.execution.batch_size VERBOSE
+----
+datafusion.execution.batch_size 8192 Default batch size while creating new batches, it's especially useful for buffer-in-memory batches since creating tiny batches would result in too much metadata memory consumption
+
 # show_time_zone_default_utc
 # https://github.com/apache/arrow-datafusion/issues/3255
 query TT
@@ -223,6 +296,26 @@ SHOW TIMEZONE
 datafusion.execution.time_zone +00:00
 
 
+# show_time_zone_default_utc_verbose
+# https://github.com/apache/arrow-datafusion/issues/3255
+query TTT
+SHOW TIME ZONE VERBOSE
+----
+datafusion.execution.time_zone +00:00 The default time zone Some functions, e.g. `EXTRACT(HOUR from SOME_TIME)`, shift the underlying datetime according to this time zone, and then extract the hour
+
+# show_timezone_default_utc
+# https://github.com/apache/arrow-datafusion/issues/3255
+query TTT
+SHOW TIMEZONE VERBOSE
+----
+datafusion.execution.time_zone +00:00 The default time zone Some functions, e.g. `EXTRACT(HOUR from SOME_TIME)`, shift the underlying datetime according to this time zone, and then extract the hour
+
+
+# show empty verbose
+query TTT
+SHOW VERBOSE
+----
+
 # information_schema_describe_table
 
 ## some_table
@@ -372,6 +465,9 @@ set datafusion.catalog.information_schema = false;
 statement error Error during planning: SHOW \[VARIABLE\] is not supported unless information_schema is enabled
 SHOW SOMETHING
 
+statement error Error during planning: SHOW \[VARIABLE\] is not supported unless information_schema is enabled
+SHOW SOMETHING VERBOSE
+
 statement ok
 set datafusion.catalog.information_schema = true;
 

datafusion/sqllogictest/test_files/set_variable.slt

@@ -243,4 +243,4 @@ statement ok
 SET TIME ZONE = 'Asia/Taipei2'
 
 statement error Arrow error: Parser error: Invalid timezone "Asia/Taipei2": 'Asia/Taipei2' is not a valid timezone
-SELECT '2000-01-01T00:00:00'::TIMESTAMP::TIMESTAMPTZ
+SELECT '2000-01-01T00:00:00'::TIMESTAMP::TIMESTAMPTZ