Merge branch 'branch-24.10' into json-tree-refactor

rapidsai · Sep 24, 2024 · 278f391 · 278f391
2 parents 2c37e42 + 8b12cf4
commit 278f391
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Showing 11 changed files with 30 additions and 37 deletions.
diff --git a/.github/workflows/build.yaml b/.github/workflows/build.yaml
@@ -62,7 +62,7 @@ jobs:
       arch: "amd64"
       branch: ${{ inputs.branch }}
       build_type: ${{ inputs.build_type || 'branch' }}
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       date: ${{ inputs.date }}
       node_type: "gpu-v100-latest-1"
       run_script: "ci/build_docs.sh"

diff --git a/.github/workflows/pr.yaml b/.github/workflows/pr.yaml
@@ -160,7 +160,7 @@ jobs:
       build_type: pull-request
       node_type: "gpu-v100-latest-1"
       arch: "amd64"
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       run_script: "ci/test_java.sh"
   static-configure:
     needs: checks
@@ -181,7 +181,7 @@ jobs:
       build_type: pull-request
       node_type: "gpu-v100-latest-1"
       arch: "amd64"
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       run_script: "ci/test_notebooks.sh"
   docs-build:
     needs: conda-python-build
@@ -191,7 +191,7 @@ jobs:
       build_type: pull-request
       node_type: "gpu-v100-latest-1"
       arch: "amd64"
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       run_script: "ci/build_docs.sh"
   wheel-build-libcudf:
     needs: checks

diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml
@@ -41,7 +41,7 @@ jobs:
       sha: ${{ inputs.sha }}
       node_type: "gpu-v100-latest-1"
       arch: "amd64"
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       run_script: "ci/test_cpp_memcheck.sh"
   static-configure:
     secrets: inherit
@@ -81,7 +81,7 @@ jobs:
       sha: ${{ inputs.sha }}
       node_type: "gpu-v100-latest-1"
       arch: "amd64"
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       run_script: "ci/test_java.sh"
   conda-notebook-tests:
     secrets: inherit
@@ -93,7 +93,7 @@ jobs:
       sha: ${{ inputs.sha }}
       node_type: "gpu-v100-latest-1"
       arch: "amd64"
-      container_image: "rapidsai/ci-conda:latest"
+      container_image: "rapidsai/ci-conda:cuda12.5.1-ubuntu22.04-py3.11"
       run_script: "ci/test_notebooks.sh"
   wheel-tests-cudf:
     secrets: inherit

diff --git a/conda/environments/all_cuda-118_arch-x86_64.yaml b/conda/environments/all_cuda-118_arch-x86_64.yaml
@@ -31,7 +31,7 @@ dependencies:
 - doxygen=1.9.1
 - fastavro>=0.22.9
 - flatbuffers==24.3.25
-- fmt>=10.1.1,<11
+- fmt>=11.0.2,<12
 - fsspec>=0.6.0
 - gcc_linux-64=11.*
 - hypothesis
@@ -84,7 +84,7 @@ dependencies:
 - s3fs>=2022.3.0
 - scikit-build-core>=0.10.0
 - scipy
-- spdlog>=1.12.0,<1.13
+- spdlog>=1.14.1,<1.15
 - sphinx
 - sphinx-autobuild
 - sphinx-copybutton

diff --git a/conda/environments/all_cuda-125_arch-x86_64.yaml b/conda/environments/all_cuda-125_arch-x86_64.yaml
@@ -32,7 +32,7 @@ dependencies:
 - doxygen=1.9.1
 - fastavro>=0.22.9
 - flatbuffers==24.3.25
-- fmt>=10.1.1,<11
+- fmt>=11.0.2,<12
 - fsspec>=0.6.0
 - gcc_linux-64=11.*
 - hypothesis
@@ -82,7 +82,7 @@ dependencies:
 - s3fs>=2022.3.0
 - scikit-build-core>=0.10.0
 - scipy
-- spdlog>=1.12.0,<1.13
+- spdlog>=1.14.1,<1.15
 - sphinx
 - sphinx-autobuild
 - sphinx-copybutton

diff --git a/conda/recipes/libcudf/conda_build_config.yaml b/conda/recipes/libcudf/conda_build_config.yaml
@@ -26,13 +26,13 @@ librdkafka_version:
   - ">=2.5.0,<2.6.0a0"
 
 fmt_version:
-  - ">=10.1.1,<11"
+  - ">=11.0.2,<12"
 
 flatbuffers_version:
   - "=24.3.25"
 
 spdlog_version:
-  - ">=1.12.0,<1.13"
+  - ">=1.14.1,<1.15"
 
 nvcomp_version:
   - "=4.0.1"

diff --git a/cpp/CMakeLists.txt b/cpp/CMakeLists.txt
@@ -799,7 +799,7 @@ add_dependencies(cudf jitify_preprocess_run)
 # Specify the target module library dependencies
 target_link_libraries(
   cudf
-  PUBLIC CCCL::CCCL rmm::rmm $<BUILD_LOCAL_INTERFACE:BS::thread_pool>
+  PUBLIC CCCL::CCCL rmm::rmm $<BUILD_LOCAL_INTERFACE:BS::thread_pool> spdlog::spdlog_header_only
   PRIVATE $<BUILD_LOCAL_INTERFACE:nvtx3::nvtx3-cpp> cuco::cuco ZLIB::ZLIB nvcomp::nvcomp
           kvikio::kvikio $<TARGET_NAME_IF_EXISTS:cuFile_interface> nanoarrow
 )

diff --git a/cpp/cmake/thirdparty/get_spdlog.cmake b/cpp/cmake/thirdparty/get_spdlog.cmake
@@ -1,5 +1,5 @@
 # =============================================================================
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 #
 # 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
@@ -16,21 +16,12 @@
 function(find_and_configure_spdlog)
 
   include(${rapids-cmake-dir}/cpm/spdlog.cmake)
-  rapids_cpm_spdlog(FMT_OPTION "EXTERNAL_FMT_HO" INSTALL_EXPORT_SET cudf-exports)
-  rapids_export_package(BUILD spdlog cudf-exports)
+  rapids_cpm_spdlog(
+    FMT_OPTION "EXTERNAL_FMT_HO"
+    INSTALL_EXPORT_SET cudf-exports
+    BUILD_EXPORT_SET cudf-exports
+  )
 
-  if(spdlog_ADDED)
-    rapids_export(
-      BUILD spdlog
-      EXPORT_SET spdlog
-      GLOBAL_TARGETS spdlog spdlog_header_only
-      NAMESPACE spdlog::
-    )
-    include("${rapids-cmake-dir}/export/find_package_root.cmake")
-    rapids_export_find_package_root(
-      BUILD spdlog [=[${CMAKE_CURRENT_LIST_DIR}]=] EXPORT_SET cudf-exports
-    )
-  endif()
 endfunction()
 
 find_and_configure_spdlog()
diff --git a/dependencies.yaml b/dependencies.yaml
@@ -350,12 +350,12 @@ dependencies:
     common:
       - output_types: conda
         packages:
-          - fmt>=10.1.1,<11
+          - fmt>=11.0.2,<12
           - flatbuffers==24.3.25
           - librdkafka>=2.5.0,<2.6.0a0
           # Align nvcomp version with rapids-cmake
           - nvcomp==4.0.1
-          - spdlog>=1.12.0,<1.13
+          - spdlog>=1.14.1,<1.15
   rapids_build_skbuild:
     common:
       - output_types: [conda, requirements, pyproject]

diff --git a/docs/cudf/source/cudf_polars/index.rst b/docs/cudf/source/cudf_polars/index.rst
@@ -1,7 +1,7 @@
-cuDF-based GPU backend for Polars [Open Beta]
-=============================================
+Polars GPU engine
+=================
 
-cuDF supports an in-memory, GPU-accelerated execution engine for Python users of the Polars Lazy API.
+cuDF provides an in-memory, GPU-accelerated execution engine for Python users of the Polars Lazy API.
 The engine supports most of the core expressions and data types as well as a growing set of more advanced dataframe manipulations
 and data file formats. When using the GPU engine, Polars will convert expressions into an optimized query plan and determine
 whether the plan is supported on the GPU. If it is not, the execution will transparently fall back to the standard Polars engine
@@ -16,7 +16,7 @@ We reproduced the `Polars Decision Support (PDS) <https://github.com/pola-rs/pol
 
 
 
-You can see up to 13x speedup using the GPU backend on the compute-heavy PDS queries involving complex aggregation and join operations. Below are the speedups for the top performing queries:
+You can see up to 13x speedup using the GPU engine on the compute-heavy PDS queries involving complex aggregation and join operations. Below are the speedups for the top performing queries:
 
 
 .. figure:: ../_static/compute_heavy_queries_polars.png
@@ -29,7 +29,7 @@ You can reproduce the results by visiting the `Polars Decision Support (PDS) Git
 Learn More
 ----------
 
-The GPU backend for Polars is now available in Open Beta and the engine is undergoing rapid development. To learn more, visit the `GPU Support page <https://docs.pola.rs/user-guide/gpu-support/>`__ on the Polars website.
+The GPU engine for Polars is now available in Open Beta and the engine is undergoing rapid development. To learn more, visit the `GPU Support page <https://docs.pola.rs/user-guide/gpu-support/>`__ on the Polars website.
 
 Launch on Google Colab
 ----------------------
@@ -38,4 +38,4 @@ Launch on Google Colab
    :width: 200px
    :target: https://colab.research.google.com/github/rapidsai-community/showcase/blob/main/accelerated_data_processing_examples/polars_gpu_engine_demo.ipynb
 
-   Take the cuDF backend for Polars for a test-drive in a free GPU-enabled notebook environment using your Google account by `launching on Colab <https://colab.research.google.com/github/rapidsai-community/showcase/blob/main/accelerated_data_processing_examples/polars_gpu_engine_demo.ipynb>`__.
+   Try out the GPU engine for Polars in a free GPU notebook environment. Sign in with your Google account and `launch the demo on Colab <https://colab.research.google.com/github/rapidsai-community/showcase/blob/main/accelerated_data_processing_examples/polars_gpu_engine_demo.ipynb>`__.
diff --git a/python/cudf/cudf/tests/pytest.ini b/python/cudf/cudf/tests/pytest.ini
@@ -14,4 +14,6 @@ filterwarnings =
     ignore:Passing a BlockManager to DataFrame is deprecated:DeprecationWarning
     # PerformanceWarning from cupy warming up the JIT cache
     ignore:Jitify is performing a one-time only warm-up to populate the persistent cache:cupy._util.PerformanceWarning
+    # Ignore numba PEP 456 warning specific to arm machines
+    ignore:FNV hashing is not implemented in Numba.*:UserWarning
 addopts = --tb=native