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https://issues.apache.org/jira/browse/BEAM-3484?focusedWorklogId=92146&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-92146
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ASF GitHub Bot logged work on BEAM-3484:
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Author: ASF GitHub Bot
Created on: 18/Apr/18 15:45
Start Date: 18/Apr/18 15:45
Worklog Time Spent: 10m
Work Description: iemejia commented on issue #5166: [BEAM-3484] Fix split
issue in HadoopInputFormatIOIT
URL: https://github.com/apache/beam/pull/5166#issuecomment-382433558
@lgajowy can you please help us validate if the proposed fix by
@aromanenko-dev fix the issue. In our local tests it does but better to double
check with you since you reported it.
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Issue Time Tracking
-------------------
Worklog Id: (was: 92146)
Time Spent: 0.5h (was: 20m)
> HadoopInputFormatIO reads big datasets invalid
> ----------------------------------------------
>
> Key: BEAM-3484
> URL: https://issues.apache.org/jira/browse/BEAM-3484
> Project: Beam
> Issue Type: Bug
> Components: io-java-hadoop
> Affects Versions: 2.3.0, 2.4.0
> Reporter: Łukasz Gajowy
> Assignee: Alexey Romanenko
> Priority: Minor
> Fix For: 2.5.0
>
> Attachments: result_sorted1000000, result_sorted600000
>
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> 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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