Utkarsh Agarwal created SPARK-44705:
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Summary: Make PythonRunner single-threaded
Key: SPARK-44705
URL: https://issues.apache.org/jira/browse/SPARK-44705
Project: Spark
Issue Type: Improvement
Components: PySpark
Affects Versions: 3.5.0
Reporter: Utkarsh Agarwal
PythonRunner, a utility that executes Python UDFs in Spark, uses two threads in
a producer-consumer model today. This multi-threading model is problematic and
confusing as Spark's execution model within a task is commonly understood to be
single-threaded.
More importantly, this departure of a double-threaded execution resulted in a
series of customer issues involving [race
conditions|https://issues.apache.org/jira/browse/SPARK-33277] and
[deadlocks|https://issues.apache.org/jira/browse/SPARK-38677] between threads
as the code was hard to reason about. There have been multiple attempts to
reign in these issues, viz., [fix
1|https://issues.apache.org/jira/browse/SPARK-22535], [fix
2|https://github.com/apache/spark/pull/30177], [fix
3|https://github.com/apache/spark/commit/243c321db2f02f6b4d926114bd37a6e74c2be185].
Moreover, the fixes have made the code base somewhat abstruse by introducing
multiple daemon [monitor
threads|https://github.com/apache/spark/blob/a3a32912be04d3760cb34eb4b79d6d481bbec502/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala#L579]
to detect deadlocks.
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