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• • Re: [PR] ci: add breaking change detector [datafusion] via GitHub
• Re: [PR] perf: Optimize `substr_index` to use bulk-NULL string builder [datafusion] via GitHub
  • Re: [PR] perf: Optimize `substr_index` to use bulk-NULL string builder [datafusion] via GitHub
• Re: [I] Refactor Spark 4.0 and 4.1 shims [datafusion-comet] via GitHub
• Re: [PR] refactor: consolidate identical spark-4.0 and spark-4.1 shims into spark-4.x [datafusion-comet] via GitHub
• Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
  • Re: [PR] fix(proto): correctly serialize FilterExec empty projection [datafusion] via GitHub
• Re: [PR] chore: update python deps to ballista and datafusion 52 [datafusion-ballista] via GitHub
  • Re: [PR] chore: update python deps to ballista and datafusion 52 [datafusion-ballista] via GitHub
  • Re: [PR] chore: update python deps to ballista and datafusion 52 [datafusion-ballista] via GitHub
  • Re: [PR] chore: update python deps to ballista and datafusion 52 [datafusion-ballista] via GitHub
  • Re: [PR] chore: update python deps to ballista and datafusion 52 [datafusion-ballista] via GitHub
  • Re: [PR] chore: update python deps to ballista and datafusion 52 [datafusion-ballista] via GitHub
• Re: [PR] feat: defer sort-shuffle materialization with interleave_record_batch [datafusion-ballista] via GitHub
• Re: [I] Use interleave_record_batch to avoid tiny batches in sort-based shuffle [datafusion-ballista] via GitHub
• Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
  • Re: [PR] feat: support binary arguments for StringConcat operator [datafusion] via GitHub
• [PR] ci: drop Intel macOS Python wheel build [datafusion-ballista] via GitHub
  • Re: [PR] ci: drop Intel macOS Python wheel build [datafusion-ballista] via GitHub
  • Re: [PR] ci: drop Intel macOS Python wheel build [datafusion-ballista] via GitHub
  • Re: [PR] ci: drop Intel macOS Python wheel build [datafusion-ballista] via GitHub
  • Re: [PR] ci: drop Intel macOS Python wheel build [datafusion-ballista] via GitHub
• [I] Adaptive query planner does not support sort-based shuffle [datafusion-ballista] via GitHub
  • Re: [I] Adaptive query planner does not support sort-based shuffle [datafusion-ballista] via GitHub
  • Re: [I] Adaptive query planner does not support sort-based shuffle [datafusion-ballista] via GitHub
  • Re: [I] Adaptive query planner does not support sort-based shuffle [datafusion-ballista] via GitHub
• [I] Iceberg reflection failure [datafusion-comet] via GitHub
  • Re: [I] Iceberg reflection failure [datafusion-comet] via GitHub
• Re: [PR] refactor `array_remove` benchmarks & add nested benches [datafusion] via GitHub
  • Re: [PR] refactor `array_remove` benchmarks & add nested benches [datafusion] via GitHub
  • Re: [PR] refactor `array_remove` benchmarks & add nested benches [datafusion] via GitHub
• [PR] docs(release): document PyPI publish process for python client [datafusion-ballista] via GitHub
  • Re: [PR] docs(release): document PyPI publish process for python client [datafusion-ballista] via GitHub
  • Re: [PR] docs(release): document PyPI publish process for python client [datafusion-ballista] via GitHub
  • Re: [PR] docs(release): document PyPI publish process for python client [datafusion-ballista] via GitHub
  • Re: [PR] docs(release): document PyPI publish process for python client [datafusion-ballista] via GitHub
  • Re: [PR] docs(release): document PyPI publish process for python client [datafusion-ballista] via GitHub
• Re: [PR] feat: Add standalone shuffle writer benchmark that shuffles real Parquet input [datafusion-ballista] via GitHub
  • Re: [PR] feat: Add standalone shuffle writer benchmark that shuffles real Parquet input [datafusion-ballista] via GitHub
• [I] Add installation instructions to Python user guide [datafusion-ballista] via GitHub
• Re: [I] Create PyPi Release Process [datafusion-ballista] via GitHub
• [I] Python release wheels: macOS x86_64 wheel is missing and arm64 wheel is built twice [datafusion-ballista] via GitHub
  • Re: [I] Python release wheels: macOS x86_64 wheel is missing and arm64 wheel is built twice [datafusion-ballista] via GitHub
• Re: [PR] docs: improve Python documentation structure [datafusion-ballista] via GitHub
  • Re: [PR] docs: improve Python documentation structure [datafusion-ballista] via GitHub
  • Re: [PR] docs: improve Python documentation structure [datafusion-ballista] via GitHub
  • Re: [PR] docs: improve Python documentation structure [datafusion-ballista] via GitHub
• [I] Ballista configs cannot be set in Python client [datafusion-ballista] via GitHub
  • Re: [I] Ballista configs cannot be set in Python client [datafusion-ballista] via GitHub
  • Re: [I] Ballista configs cannot be set in Python client [datafusion-ballista] via GitHub
• [I] Add IO_BLOCK_TRANSPORT support for sort-based shuffle [datafusion-ballista] via GitHub
• Re: [PR] ci: enable Spark 4.1 PR test matrix [datafusion-comet] via GitHub
  • Re: [PR] ci: enable Spark 4.1 PR test matrix [datafusion-comet] via GitHub
  • Re: [PR] ci: enable Spark 4.1 PR test matrix [datafusion-comet] via GitHub
• [I] SPARK-53968 SQLViewSuite: decimal arithmetic returns ~10x smaller values through view CTE on Spark 4.1.1 [datafusion-comet] via GitHub
  • Re: [I] SPARK-53968 SQLViewSuite: decimal arithmetic returns ~10x smaller values through view CTE on Spark 4.1.1 [datafusion-comet] via GitHub
• [I] Comet native sort lacks row-format support for Struct(Map(...)) sort keys [datafusion-comet] via GitHub
  • Re: [I] Comet native sort lacks row-format support for Struct(Map(...)) sort keys [datafusion-comet] via GitHub
  • Re: [I] Comet native sort lacks row-format support for Struct(Map(...)) sort keys [datafusion-comet] via GitHub
• [I] EXCEPT ALL / INTERSECT ALL with GROUP BY return incorrect results on Spark 4.1.1 [datafusion-comet] via GitHub
  • Re: [I] EXCEPT ALL / INTERSECT ALL with GROUP BY return incorrect results on Spark 4.1.1 [datafusion-comet] via GitHub
• [I] Comet native scan rejects invalid UTF-8 byte sequences in STRING column (hll.sql on Spark 4.1) [datafusion-comet] via GitHub
  • Re: [I] Comet native scan rejects invalid UTF-8 byte sequences in STRING column (hll.sql on Spark 4.1) [datafusion-comet] via GitHub
• [I] Type annotation requires UDFs to return a type instead of an array [datafusion-python] via GitHub
• Re: [PR] fix: grouping separator for float and decimal [datafusion] via GitHub
  • Re: [PR] fix: grouping separator for float and decimal [datafusion] via GitHub
  • Re: [PR] fix: grouping separator for float and decimal [datafusion] via GitHub
  • Re: [PR] fix: grouping separator for float and decimal [datafusion] via GitHub
  • Re: [PR] fix: grouping separator for float and decimal [datafusion] via GitHub
• Re: [PR] Add support for nested types to nullif. [datafusion] via GitHub
• Re: [I] Add support for nested types to `nullif`. [datafusion] via GitHub
• Re: [I] Support `EXPLAIN ANALYZE` in Ballista [datafusion-ballista] via GitHub
• Re: [PR] feat: Support `EXPLAIN ANALYZE` in Ballista [datafusion-ballista] via GitHub
• Re: [PR] feat(unparser): Keep inner join `Filter → TableScan` predicates to `WHERE` instead of moving to `JOIN ON` [datafusion] via GitHub
• Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
  • Re: [PR] Add StatisticsContext parameter to partition_statistics [datafusion] via GitHub
• Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
  • Re: [PR] Intermediate result blocked approach to aggregation memory management [datafusion] via GitHub
• Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
  • Re: [PR] feat: Support Spark levenshtein expression in native execution [datafusion-comet] via GitHub
• Re: [PR] fix: fix elapsed_compute metric in ParquetSink to report encoding time only [datafusion] via GitHub
  • Re: [PR] fix: fix elapsed_compute metric in ParquetSink to report encoding time only [datafusion] via GitHub
  • Re: [PR] fix: fix elapsed_compute metric in ParquetSink to report encoding time only [datafusion] via GitHub
  • Re: [PR] fix: fix elapsed_compute metric in ParquetSink to report encoding time only [datafusion] via GitHub
  • Re: [PR] fix: fix elapsed_compute metric in ParquetSink to report encoding time only [datafusion] via GitHub
• Re: [I] Potential Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [I] Potential Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [I] Potential Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [I] Potential Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
• Re: [PR] feat: Scheduler config update [datafusion-ballista] via GitHub
  • Re: [PR] feat: Scheduler config update [datafusion-ballista] via GitHub
• [PR] chore(deps): bump libloading from 0.8.9 to 0.9.0 [datafusion] via GitHub
  • Re: [PR] chore(deps): bump libloading from 0.8.9 to 0.9.0 [datafusion] via GitHub
  • Re: [PR] chore(deps): bump libloading from 0.8.9 to 0.9.0 [datafusion] via GitHub
  • Re: [PR] chore(deps): bump libloading from 0.8.9 to 0.9.0 [datafusion] via GitHub
• Re: [PR] ci: pin JDK per Spark version in Iceberg workflow matrix [datafusion-comet] via GitHub
  • Re: [PR] ci: pin JDK per Spark version in Iceberg workflow matrix [datafusion-comet] via GitHub
  • Re: [PR] ci: pin JDK per Spark version in Iceberg workflow matrix [datafusion-comet] via GitHub
• Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
  • Re: [PR] Add lambda support and array_transform udf [datafusion] via GitHub
• [PR] chore(deps): update pydata-sphinx-theme requirement from <1,>=0.17.0 to >=0.17.1,<1 in /docs [datafusion] via GitHub
  • Re: [PR] chore(deps): update pydata-sphinx-theme requirement from <1,>=0.17.0 to >=0.17.1,<1 in /docs [datafusion] via GitHub
• [PR] chore(deps): bump pbjson-types from 0.8.0 to 0.9.0 in the proto group [datafusion] via GitHub
  • Re: [PR] chore(deps): bump pbjson-types from 0.8.0 to 0.9.0 in the proto group [datafusion] via GitHub
  • Re: [PR] chore(deps): bump pbjson-types from 0.8.0 to 0.9.0 in the proto group [datafusion] via GitHub
  • [PR] chore(deps): bump pbjson-types from 0.8.0 to 0.9.0 in the proto group [datafusion] via GitHub
  • Re: [PR] chore(deps): bump pbjson-types from 0.8.0 to 0.9.0 in the proto group [datafusion] via GitHub
  • Re: [PR] chore(deps): bump pbjson-types from 0.8.0 to 0.9.0 in the proto group [datafusion] via GitHub
• [PR] chore(deps): bump taiki-e/install-action from 2.75.18 to 2.75.23 [datafusion] via GitHub
  • Re: [PR] chore(deps): bump taiki-e/install-action from 2.75.18 to 2.75.23 [datafusion] via GitHub
• Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
  • Re: [PR] feat: Improved multiple column aggregation performance by using bitmasks rather than `Vec<bool>` [datafusion] via GitHub
• Re: [I] Blog post about 1000 distinct committers / history of the project [datafusion] via GitHub

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