zhengruifeng commented on code in PR #49000:
URL: https://github.com/apache/spark/pull/49000#discussion_r1861713749
##########
python/pyspark/worker.py:
##########
@@ -171,9 +171,21 @@ def wrap_arrow_batch_udf(f, args_offsets, kwargs_offsets,
return_type):
elif type(return_type) == BinaryType:
result_func = lambda r: bytes(r) if r is not None else r # noqa: E731
- @fail_on_stopiteration
- def evaluate(*args: pd.Series) -> pd.Series:
- return pd.Series([result_func(func(*row)) for row in zip(*args)])
+ if "spark.sql.execution.pythonUDF.arrow.concurrency.level" in runner_conf:
+ from concurrent.futures import ThreadPoolExecutor
+
+ c =
int(runner_conf["spark.sql.execution.pythonUDF.arrow.concurrency.level"])
Review Comment:
when `c == 1`, I guess we might fallback to the old path?
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