spark-instrumented-optimizer/sql/core
Yingyi Bu 3f6322f9aa [SPARK-35077][SQL] Migrate to transformWithPruning for leftover optimizer rules
### What changes were proposed in this pull request?

Migrate to transformWithPruning for the following queries:
- SimplifyExtractValueOps
- NormalizeFloatingNumbers
- PushProjectionThroughUnion
- PushDownPredicates
- ExtractPythonUDFFromAggregate
- ExtractPythonUDFFromJoinCondition
- ExtractGroupingPythonUDFFromAggregate
- ExtractPythonUDFs
- CleanupDynamicPruningFilters

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### Why are the changes needed?

Reduce the number of tree traversals and hence improve the query compilation latency.

### How was this patch tested?

Existing tests.
Performance diff:
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&nbsp; | Baseline | Experiment | Experiment/Baseline
-- | -- | -- | --
SimplifyExtractValueOps | 99367049 | 3679579 | 0.04
NormalizeFloatingNumbers | 24717928 | 20451094 | 0.83
PushProjectionThroughUnion | 14130245 | 7913551 | 0.56
PushDownPredicates | 276333542 | 261246842 | 0.95
ExtractPythonUDFFromAggregate | 6459451 | 2683556 | 0.42
ExtractPythonUDFFromJoinCondition | 5695404 | 2504573 | 0.44
ExtractGroupingPythonUDFFromAggregate | 5546701 | 1858755 | 0.34
ExtractPythonUDFs | 58726458 | 1598518 | 0.03
CleanupDynamicPruningFilters | 26606652 | 15417936 | 0.58
OptimizeSubqueries | 3072287940 | 2876462708 | 0.94

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Closes #32721 from sigmod/pushdown.

Authored-by: Yingyi Bu <yingyi.bu@databricks.com>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
2021-06-02 11:46:33 +08:00
..
benchmarks [SPARK-34981][SQL][FOLLOWUP] Use SpecificInternalRow in ApplyFunctionExpression 2021-05-24 17:25:24 +09:00
src [SPARK-35077][SQL] Migrate to transformWithPruning for leftover optimizer rules 2021-06-02 11:46:33 +08:00
pom.xml [SPARK-33662][BUILD] Setting version to 3.2.0-SNAPSHOT 2020-12-04 14:10:42 -08:00