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Posted to commits@beam.apache.org by "Ahmet Altay (JIRA)" <ji...@apache.org> on 2017/07/25 17:39:00 UTC
[jira] [Comment Edited] (BEAM-2490) ReadFromText function is not
taking all data with glob operator (*)
[ https://issues.apache.org/jira/browse/BEAM-2490?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16062089#comment-16062089 ]
Ahmet Altay edited comment on BEAM-2490 at 7/25/17 5:38 PM:
------------------------------------------------------------
gzip issue could be related to https://issues.apache.org/jira/browse/BEAM-2497 [~wileeam], are you running against head with the fix (https://github.com/apache/beam/pull/3428) ?
was (Author: altay):
gzip issue could be related to https://issues.apache.org/jira/browse/BEAM-2490 [~wileeam], are you running against head with the fix (https://github.com/apache/beam/pull/3428) ?
> ReadFromText function is not taking all data with glob operator (*)
> --------------------------------------------------------------------
>
> Key: BEAM-2490
> URL: https://issues.apache.org/jira/browse/BEAM-2490
> Project: Beam
> Issue Type: Bug
> Components: sdk-py
> Affects Versions: 2.0.0
> Environment: Usage with Google Cloud Platform: Dataflow runner
> Reporter: Olivier NGUYEN QUOC
> Assignee: Chamikara Jayalath
> Fix For: Not applicable
>
>
> I run a very simple pipeline:
> * Read my files from Google Cloud Storage
> * Split with '\n' char
> * Write in on a Google Cloud Storage
> I have 8 files that match with the pattern:
> * my_files_2016090116_20160902_060051_xxxxxxxxxx.csv.gz (229.25 MB)
> * my_files_2016090117_20160902_060051_xxxxxxxxxx.csv.gz (184.1 MB)
> * my_files_2016090118_20160902_060051_xxxxxxxxxx.csv.gz (171.73 MB)
> * my_files_2016090119_20160902_060051_xxxxxxxxxx.csv.gz (151.34 MB)
> * my_files_2016090120_20160902_060051_xxxxxxxxxx.csv.gz (129.69 MB)
> * my_files_2016090121_20160902_060051_xxxxxxxxxx.csv.gz (151.7 MB)
> * my_files_2016090122_20160902_060051_xxxxxxxxxx.csv.gz (346.46 MB)
> * my_files_2016090122_20160902_060051_xxxxxxxxxx.csv.gz (222.57 MB)
> This code should take them all:
> {code:python}
> beam.io.ReadFromText(
> "gs://XXXX_folder1/my_files_20160901*.csv.gz",
> skip_header_lines=1,
> compression_type=beam.io.filesystem.CompressionTypes.GZIP
> )
> {code}
> It runs well but there is only a 288.62 MB file in output of this pipeline (instead of a 1.5 GB file).
> The whole pipeline code:
> {code:python}
> data = (p | 'ReadMyFiles' >> beam.io.ReadFromText(
> "gs://XXXX_folder1/my_files_20160901*.csv.gz",
> skip_header_lines=1,
> compression_type=beam.io.filesystem.CompressionTypes.GZIP
> )
> | 'SplitLines' >> beam.FlatMap(lambda x: x.split('\n'))
> )
> output = (
> data| "Write" >> beam.io.WriteToText('gs://XXX_folder2/test.csv', num_shards=1)
> )
> {code}
> Dataflow indicates me that the estimated size of the output after the ReadFromText step is 602.29 MB only, which not correspond to any unique input file size nor the overall file size matching with the pattern.
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