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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2018/01/14 02:28:03 UTC
[jira] [Resolved] (SPARK-22959) Configuration to select the modules
for daemon and worker in PySpark
[ https://issues.apache.org/jira/browse/SPARK-22959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-22959.
----------------------------------
Resolution: Fixed
Fix Version/s: 2.4.0
Issue resolved by pull request 20151
[https://github.com/apache/spark/pull/20151]
> Configuration to select the modules for daemon and worker in PySpark
> --------------------------------------------------------------------
>
> Key: SPARK-22959
> URL: https://issues.apache.org/jira/browse/SPARK-22959
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Fix For: 2.4.0
>
>
> We are now forced to use {{pyspark/daemon.py}} and {{pyspark/worker.py}} in PySpark tests.
> This doesn't allow a custom modification for it and it's sometimes hard to debug what happens in Python worker processes.
> This is actually related with SPARK-7721 too as somehow Coverage is unable to detect the coverage from {{os.fork}}. If we have some custom fixes to force the coverage, it works fine.
> This is also related with SPARK-20368. This JIRA describes Sentry supports which (roughly) needs some changes within worker side. With this simple workaround, advanced users will be able to do a lot of pluggable workarounds.
> As an example, let's say if I configure the module {{coverage_daemon}} and had {{coverage_daemon.py}} in the python path:
> {code}
> import os
> from pyspark import daemon
> if "COVERAGE_PROCESS_START" in os.environ:
> from pyspark.worker import main
> def _cov_wrapped(*args, **kwargs):
> import coverage
> cov = coverage.coverage(
> config_file=os.environ["COVERAGE_PROCESS_START"])
> cov.start()
> try:
> main(*args, **kwargs)
> finally:
> cov.stop()
> cov.save()
> daemon.worker_main = _cov_wrapped
> if __name__ == '__main__':
> daemon.manager()
> {code}
> I can leave the main code intact but do some workarounds.
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