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Posted to commits@beam.apache.org by "Kenneth Knowles (JIRA)" <ji...@apache.org> on 2018/01/19 23:25:00 UTC
[jira] [Assigned] (BEAM-3484) HadoopInputFormatIO reads big
datasets invalid
[ https://issues.apache.org/jira/browse/BEAM-3484?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Kenneth Knowles reassigned BEAM-3484:
-------------------------------------
Assignee: Chamikara Jayalath (was: Kenneth Knowles)
> HadoopInputFormatIO reads big datasets invalid
> ----------------------------------------------
>
> Key: BEAM-3484
> URL: https://issues.apache.org/jira/browse/BEAM-3484
> Project: Beam
> Issue Type: Bug
> Components: sdk-java-extensions
> Reporter: Łukasz Gajowy
> Assignee: Chamikara Jayalath
> Priority: Major
> Attachments: result_sorted1000000, result_sorted600000
>
>
> For big datasets HadoopInputFormat sometimes skips/duplicates elements from database in resulting PCollection. This gives incorrect read result.
> Occurred to me while developing HadoopInputFormatIOIT and running it on dataflow. For datasets smaller or equal to 600 000 database rows I wasn't able to reproduce the issue. Bug appeared only for bigger sets, eg. 700 000, 1 000 000.
> Attachments:
> - text file with sorted HadoopInputFormat.read() result saved using TextIO.write().to().withoutSharding(). If you look carefully you'll notice duplicates or missing values that should not happen
> - same text file for 600 000 records not having any duplicates and missing elements
> - link to a PR with HadoopInputFormatIO integration test that allows to reproduce this issue. At the moment of writing, this code is not merged yet.
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