gaogaotiantian commented on code in PR #59845:
URL: https://github.com/apache/spark/pull/59845#discussion_r4474673339
##########
python/pyspark/eval_handlers/tests/test_arrow_eval_type_handlers.py:
##########
@@ -367,6 +367,19 @@ def test_concurrency_level(self):
out = list(handler.run(0, iter([self._batch(a=list(range(10)), b=[0] *
10)])))
self.assertEqual(out[0].column(0).to_pylist(), [v * 2 for v in
range(10)])
+ def test_concurrency_level_multi_and_zero_arg(self):
Review Comment:
Added a keyword-argument UDF to `test_concurrency_level_multi_and_zero_arg`.
##########
python/benchmarks/bench_eval_type.py:
##########
@@ -540,6 +540,7 @@ def _build_scenario(cls, name):
"identity_udf": (lambda x: x, None, [0]),
"stringify_udf": (lambda x: str(x), StringType(), [0]),
"nullcheck_udf": (lambda x: x is not None, BooleanType(), [0]),
+ "concat3_udf": (lambda a, b, c: f"{a}{b}{c}", StringType(), [0, 1, 2]),
Review Comment:
I fixed the `arg_offsets` comment. I'd prefer to keep `concat3_udf` shared
between the Time and Peakmem benchmarks, so every UDF for this eval type is
defined in one place and both benchmarks cover the same matrix.
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