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Posted to reviews@spark.apache.org by "xinrong-meng (via GitHub)" <gi...@apache.org> on 2024/02/07 21:58:44 UTC
Re: [PR] [SPARK-46689][SPARK-46690][PYTHON][CONNECT] Support v2 profiling in group/cogroup applyInPandas/applyInArrow [spark]
xinrong-meng commented on code in PR #45050:
URL: https://github.com/apache/spark/pull/45050#discussion_r1482146994
##########
python/pyspark/sql/tests/test_udf_profiler.py:
##########
@@ -333,6 +333,69 @@ def filter_func(iterator):
self.assertEqual(0, len(self.profile_results), str(self.profile_results.keys()))
+ @unittest.skipIf(
+ not have_pandas or not have_pyarrow,
+ cast(str, pandas_requirement_message or pyarrow_requirement_message),
+ )
+ def test_perf_profiler_group_apply_in_pandas(self):
Review Comment:
Good catch!
##########
python/pyspark/sql/tests/test_udf_profiler.py:
##########
@@ -333,6 +333,69 @@ def filter_func(iterator):
self.assertEqual(0, len(self.profile_results), str(self.profile_results.keys()))
+ @unittest.skipIf(
+ not have_pandas or not have_pyarrow,
+ cast(str, pandas_requirement_message or pyarrow_requirement_message),
+ )
+ def test_perf_profiler_group_apply_in_pandas(self):
+ # FlatMapGroupsInBatchExec
+ df = self.spark.createDataFrame(
+ [(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2, 10.0)], ("id", "v")
+ )
+
+ def normalize(pdf):
+ v = pdf.v
+ return pdf.assign(v=(v - v.mean()) / v.std())
+
+ with self.sql_conf({"spark.sql.pyspark.udf.profiler": "perf"}):
+ df.groupby("id").applyInPandas(normalize, schema="id long, v double").show()
+
+ self.assertEqual(1, len(self.profile_results), str(self.profile_results.keys()))
+
+ for id in self.profile_results:
+ with self.trap_stdout() as io:
+ self.spark.showPerfProfiles(id)
+
+ self.assertIn(f"Profile of UDF<id={id}>", io.getvalue())
+ self.assertRegex(
+ io.getvalue(), f"2.*{os.path.basename(inspect.getfile(_do_computation))}"
+ )
+
+ @unittest.skipIf(
+ not have_pandas or not have_pyarrow,
+ cast(str, pandas_requirement_message or pyarrow_requirement_message),
+ )
+ def test_perf_profiler_cogroup_apply_in_pandas(self):
Review Comment:
Sounds good.
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