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Posted to commits@beam.apache.org by "Chamikara Jayalath (JIRA)" <ji...@apache.org> on 2017/07/27 18:22:00 UTC
[jira] [Resolved] (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:all-tabpanel ]
Chamikara Jayalath resolved BEAM-2490.
--------------------------------------
Resolution: Fixed
Fix Version/s: (was: Not applicable)
2.2.0
> 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: 2.2.0
>
>
> 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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