b8a440f098
### What changes were proposed in this pull request? As the Python evaluation consumes the parent iterator in a separate thread, it could consume more data from the parent even after the task ends and the parent is closed. Thus, we should use `ContextAwareIterator` to stop consuming after the task ends. ### Why are the changes needed? Python/Pandas UDF right after off-heap vectorized reader could cause executor crash. E.g.,: ```py spark.range(0, 100000, 1, 1).write.parquet(path) spark.conf.set("spark.sql.columnVector.offheap.enabled", True) def f(x): return 0 fUdf = udf(f, LongType()) spark.read.parquet(path).select(fUdf('id')).head() ``` This is because, the Python evaluation consumes the parent iterator in a separate thread and it consumes more data from the parent even after the task ends and the parent is closed. If an off-heap column vector exists in the parent iterator, it could cause segmentation fault which crashes the executor. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Added tests, and manually. Closes #30177 from ueshin/issues/SPARK-33277/python_pandas_udf. Authored-by: Takuya UESHIN <ueshin@databricks.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> |
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.. | ||
__init__.py | ||
test_arrow.py | ||
test_catalog.py | ||
test_column.py | ||
test_conf.py | ||
test_context.py | ||
test_dataframe.py | ||
test_datasources.py | ||
test_functions.py | ||
test_group.py | ||
test_pandas_cogrouped_map.py | ||
test_pandas_grouped_map.py | ||
test_pandas_map.py | ||
test_pandas_udf.py | ||
test_pandas_udf_grouped_agg.py | ||
test_pandas_udf_scalar.py | ||
test_pandas_udf_typehints.py | ||
test_pandas_udf_window.py | ||
test_readwriter.py | ||
test_serde.py | ||
test_session.py | ||
test_streaming.py | ||
test_types.py | ||
test_udf.py | ||
test_utils.py |