Arseniy Tashoyan created SPARK-22471:
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Summary: SQLListener consumes much memory causing OutOfMemoryError
Key: SPARK-22471
URL: https://issues.apache.org/jira/browse/SPARK-22471
Project: Spark
Issue Type: Bug
Components: SQL, Web UI
Affects Versions: 2.2.0
Environment: Spark 2.2.0, Linux
Reporter: Arseniy Tashoyan
_SQLListener_ may grow very large when Spark runs complex multi-stage requests.
The listener tracks metrics for all stages in __stageIdToStageMetrics_ hash
map. _SQLListener_ has some means to cleanup this hash map regularly, but this
is not enough. Precisely, the method _trimExecutionsIfNecessary_ ensures that
__stageIdToStageMetrics_ does not have metrics for very old data; this method
runs on each execution completion.
However, if an execution has many stages, _SQLListener_ keeps adding new
entries to __stageIdToStageMetrics_ without calling
_trimExecutionsIfNecessary_. The hash map may grow to enormous size.
Strictly speaking, it is not a memory leak, because finally
_trimExecutionsIfNecessary_ cleans the hash map. However, the driver program
has high odds to crash with OutOfMemoryError (and it does).
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