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https://issues.apache.org/jira/browse/SPARK-22959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-22959:
---------------------------------
Description:
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.
was:
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.
> 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
>
> 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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