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https://issues.apache.org/jira/browse/SPARK-33000?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17215469#comment-17215469
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Nicholas Chammas commented on SPARK-33000:
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I've tested this out a bit more, and I think the original issue I reported is
valid. Either that, or I'm still missing something.
I built Spark at the latest commit from {{master}}:
{code:java}
commit 3ae1520185e2d96d1bdbd08c989f0d48ad3ba578 (HEAD -> master, origin/master,
origin/HEAD, apache/master)
Author: ulysses <youxi...@weidian.com>
Date: Fri Oct 16 11:26:27 2020 +0000 {code}
One thing that has changed is that Spark now prevents you from setting
{{cleanCheckpoints}} after startup:
{code:java}
>>> spark.conf.set('spark.cleaner.referenceTracking.cleanCheckpoints', 'true')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File ".../spark/python/pyspark/sql/conf.py", line 36, in set
self._jconf.set(key, value)
File ".../spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
1304, in __call__
File ".../spark/python/pyspark/sql/utils.py", line 117, in deco
raise converted from None
pyspark.sql.utils.AnalysisException: Cannot modify the value of a Spark config:
spark.cleaner.referenceTracking.cleanCheckpoints; {code}
So that's good! This makes it clear to the user that this setting cannot be set
at this time (though it could be made more helpful it explained why).
However, if I try to set the config as part of invoking PySpark, I still don't
see any checkpointed data get cleaned up on shutdown:
{code:java}
$ rm -rf /tmp/spark/checkpoint/
$ ./bin/pyspark --conf spark.cleaner.referenceTracking.cleanCheckpoints=true
<snipped>
>>> spark.conf.get('spark.cleaner.referenceTracking.cleanCheckpoints')
'true'
>>> spark.sparkContext.setCheckpointDir('/tmp/spark/checkpoint/')
>>> a = spark.range(10)
>>> a.checkpoint()
DataFrame[id: bigint]
>>> <Ctrl-D>
$ du -sh /tmp/spark/checkpoint/*
32K /tmp/spark/checkpoint/57b0a413-9d47-4bcd-99ef-265e9f5c0f3b{code}
> cleanCheckpoints config does not clean all checkpointed RDDs on shutdown
> ------------------------------------------------------------------------
>
> Key: SPARK-33000
> URL: https://issues.apache.org/jira/browse/SPARK-33000
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.4.6
> Reporter: Nicholas Chammas
> Priority: Minor
>
> Maybe it's just that the documentation needs to be updated, but I found this
> surprising:
> {code:python}
> $ pyspark
> ...
> >>> spark.conf.set('spark.cleaner.referenceTracking.cleanCheckpoints', 'true')
> >>> spark.sparkContext.setCheckpointDir('/tmp/spark/checkpoint/')
> >>> a = spark.range(10)
> >>> a.checkpoint()
> DataFrame[id: bigint]
>
> >>> exit(){code}
> The checkpoint data is left behind in {{/tmp/spark/checkpoint/}}. I expected
> Spark to clean it up on shutdown.
> The documentation for {{spark.cleaner.referenceTracking.cleanCheckpoints}}
> says:
> {quote}Controls whether to clean checkpoint files if the reference is out of
> scope.
> {quote}
> When Spark shuts down, everything goes out of scope, so I'd expect all
> checkpointed RDDs to be cleaned up.
> For the record, I see the same behavior in both the Scala and Python REPLs.
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