[SPARK-57020][PYTHON][TESTS] Add ASV microbenchmark for SQL_TRANSFORM_WITH_STATE_PANDAS_UDF#56192
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[SPARK-57020][PYTHON][TESTS] Add ASV microbenchmark for SQL_TRANSFORM_WITH_STATE_PANDAS_UDF#56192Yicong-Huang wants to merge 1 commit into
Yicong-Huang wants to merge 1 commit into
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funrollloops
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funrollloops
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I'm kind of confused about what this actually benchmarks. We seem to manipulate the data directly in the UDF functions here, so the logic to invoke the transform with state user function is never executed.
Are the code paths you are benchmarking different between the different UDF types?
| np.repeat(np.arange(num_groups, dtype=np.int32), rows_per_group), | ||
| type=pa.int32(), | ||
| ) | ||
| value_pool = MockDataFactory.NUMERIC_TYPES |
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Sure you don't want to add non-numeric types? Maybe some cases with nested types (arrays, structs, etc)?
| batches, schema = self._build_scenario(scenario) | ||
| udf_func, ret_type = self._udfs[udf_name] | ||
| if ret_type is None: | ||
| ret_type = StructType(schema.fields[self._NUM_KEY_COLS :]) |
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nit: we typically see the keys included in the output schema for transform with state.
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What changes were proposed in this pull request?
Add an ASV micro-benchmark for
SQL_TRANSFORM_WITH_STATE_PANDAS_UDFtobench_eval_type.py.A stub TCP listener (
_StubStateServer) satisfiesStatefulProcessorApiClient's socket connect; the benchmark UDFs never call any state API so no protocol exchange beyond connect is needed.Scenarios cover few/many groups, small/large group sizes, and wide columns. UDFs:
identity_udf,sort_udf,count_udf.Why are the changes needed?
Part of SPARK-55724. Establishes a performance baseline before refactoring
SQL_TRANSFORM_WITH_STATE_PANDAS_UDF.Does this PR introduce any user-facing change?
No
How was this patch tested?
COLUMNS=120 ./python/asv run --python=same --bench "TransformWithStatePandas" -a "repeat=(3,5,5.0)"(one of two stable runs):TransformWithStatePandasUDFTimeBench:TransformWithStatePandasUDFPeakmemBench:Was this patch authored or co-authored using generative AI tooling?
No