ueshin opened a new pull request #30177:
URL: https://github.com/apache/spark/pull/30177
### 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.
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