[
https://issues.apache.org/jira/browse/BEAM-9029?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17121747#comment-17121747
]
Kenneth Knowles commented on BEAM-9029:
---------------------------------------
This issue is assigned but has not received an update in 30 days so it has been
labeled "stale-assigned". If you are still working on the issue, please give an
update and remove the label. If you are no longer working on the issue, please
unassign so someone else may work on it. In 7 days the issue will be
automatically unassigned.
> Two bugs in Python SDK S3 filesystem support
> --------------------------------------------
>
> Key: BEAM-9029
> URL: https://issues.apache.org/jira/browse/BEAM-9029
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Wenhai Pan
> Assignee: Wenhai Pan
> Priority: P2
> Labels: pull-request-available, stale-assigned
> Original Estimate: 24h
> Time Spent: 3h
> Remaining Estimate: 21h
>
> Hi :)
> There seem to be 2 bugs in the S3 filesystem support.
> I tried to use S3 storage for a simple wordcount demo with DirectRunner.
> The demo script:
> {code:java}
> def main():
> options = PipelineOptions().view_as(StandardOptions)
> options.runner = 'DirectRunner'
> pipeline = beam.Pipeline(options = options)
> (
> pipeline
> | ReadFromText("s3://mx-machine-learning/panwenhai/beam_test/test_data")
> | "extract_words" >> beam.FlatMap(lambda x: re.findall(r" [A-Za-z\']+", x))
> | beam.combiners.Count.PerElement()
> | beam.MapTuple(lambda word, count: "%s: %s" % (word, count))
> | WriteToText("s3://mx-machine-learning/panwenhai/beam_test/output")
> )
> result = pipeline.run()
> result.wait_until_finish()
> return
> {code}
>
> Error message 1:
> {noformat}
> apache_beam.io.filesystem.BeamIOError: Match operation failed with exceptions
> {'s3://mx-machine-learning/panwenhai/beam_test/output-*-of-00001':
> BeamIOError("List operation failed with exceptions
> {'s3://mx-machine-learning/panwenhai/beam_test/output-': S3ClientError('Tried
> to list nonexistent S3 path:
> s3://mx-machine-learning/panwenhai/beam_test/output-', 404)}")} [while
> running 'WriteToText/Write/WriteImpl/PreFinalize'] with exceptions
> None{noformat}
>
> After digging into the code, it seems the Boto3 client's list function will
> raise an exception when trying to list a nonexistent S3 path
> (beam/sdks/pythonapache_beam/io/aws/clients/s3/boto3_client.py line 111). And
> the S3IO class does not handle this exception in list_prefix function
> (beam/sdks/python/apache_beam/io/aws/s3io.py line 121).
> When the runner tries to list and delete the existing output file, if there
> is no existing output file, it will try to list a nonexistent S3 path and
> will trigger the exception.
> This should not be an issue here. I think we can ignore this exception safely
> in the S3IO list_prefix function.
> Error Message 2:
> {noformat}
> File
> "/Users/wenhai.pan/venvs/tfx/lib/python3.7/site-packages/apache_beam-2.19.0.dev0-py3.7.egg/apache_beam/io/aws/s3filesystem.py",
> line 272, in delete
> exceptions = {path: error for (path, error) in results
> File
> "/Users/wenhai.pan/venvs/tfx/lib/python3.7/site-packages/apache_beam-2.19.0.dev0-py3.7.egg/apache_beam/io/aws/s3filesystem.py",
> line 272, in <dictcomp>
> exceptions = {path: error for (path, error) in results
> ValueError: too many values to unpack (expected 2) [while running
> 'WriteToText/Write/WriteImpl/FinalizeWrite']{noformat}
>
> When the runner tries to delete the temporary output directory, it will
> trigger this exception. This exception is caused by parsing (path, error)
> directly from the "results" which is a dict
> (beam/sdks/python/apache_beam/io/aws/s3filesystem.py line 272). I think we
> should use results.items() here.
> I have submitted a patch for these 2 bugs:
> https://github.com/apache/beam/pull/10459
>
> Thank you.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
