[
https://issues.apache.org/jira/browse/BEAM-7750?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Strokach updated BEAM-7750:
----------------------------------
Description:
It seems that Apache Beam's Pipeline instances are not garbage collected, even
if the pipelines are finished or cancelled and there are no references to those
pipelines in the Python interpreter.
For pipelines executed in a script, this is not a problem. However, for
interactive pipelines executed inside a Jupyter notebook, this limits how well
we can track and remove the dependencies of those pipelines. For example, if a
pipeline reads from some cache, it would be nice to be able to delete that
cache once there are no references to it from pipelines or the global namespace.
The issue can be reproduced using the following script:
[https://gist.github.com/ostrokach/a16556dc77c96b87fe23c2fbd8fb6346].
-----
On further examination, turns out that this is due to
{{_PubSubReadEvaluator._subscription_cache}} class attribute keeping references
to all {{ReadFromPubSub}} transforms.
was:
It seems that Apache Beam's Pipeline instances are not garbage collected, even
if the pipelines are finished or cancelled and there are no references to those
pipelines in the Python interpreter.
For pipelines executed in a script, this is not a problem. However, for
interactive pipelines executed inside a Jupyter notebook, this limits how well
we can track and remove the dependencies of those pipelines. For example, if a
pipeline reads from some cache, it would be nice to be able to delete that
cache once there are no references to it from pipelines or the global namespace.
The issue can be reproduced using the following script:
[https://gist.github.com/ostrokach/a16556dc77c96b87fe23c2fbd8fb6346].
-----
On further examination, turns out that this is due to
`_PubSubReadEvaluator._subscription_cache` class attribute keeping references
to all `ReadFromPubSub` transforms.
> Pipeline instances are not garbage collected
> --------------------------------------------
>
> Key: BEAM-7750
> URL: https://issues.apache.org/jira/browse/BEAM-7750
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Affects Versions: 2.14.0
> Environment: OS: Debian rodete.
> Tested using:
> Beam versions: 2.13.0, 2.15.0.dev
> Python versions: Python 2.7, Python 3.7.
> Runners: DirectRunner, DataflowRunner.
> Reporter: Alexey Strokach
> Priority: Minor
>
> It seems that Apache Beam's Pipeline instances are not garbage collected,
> even if the pipelines are finished or cancelled and there are no references
> to those pipelines in the Python interpreter.
> For pipelines executed in a script, this is not a problem. However, for
> interactive pipelines executed inside a Jupyter notebook, this limits how
> well we can track and remove the dependencies of those pipelines. For
> example, if a pipeline reads from some cache, it would be nice to be able to
> delete that cache once there are no references to it from pipelines or the
> global namespace.
> The issue can be reproduced using the following script:
> [https://gist.github.com/ostrokach/a16556dc77c96b87fe23c2fbd8fb6346].
> -----
> On further examination, turns out that this is due to
> {{_PubSubReadEvaluator._subscription_cache}} class attribute keeping
> references to all {{ReadFromPubSub}} transforms.
--
This message was sent by Atlassian JIRA
(v7.6.14#76016)
