[jira] [Updated] (BEAM-9029) Two bugs in Python SDK S3 filesystem support

["Beam JIRA Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-9029?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Beam JIRA Bot updated BEAM-9029:
--------------------------------
    Labels: pull-request-available stale-P2  (was: pull-request-available)

> 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
>            Priority: P2
>              Labels: pull-request-available, stale-P2
>   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)