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https://issues.apache.org/jira/browse/SPARK-21938?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16156455#comment-16156455
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Hyukjin Kwon commented on SPARK-21938:
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Without reproducible steps or narrowing it down, it sounds almost impossible to
reproduce and verify this issue and, even we'd be almost unable to make sure
even if this was an actual issue or is already fixed. I think we'd better start
this on the mailing list and and narrow down and investigate it more before
posting this as an issue.
> Spark partial CSV write fails silently
> --------------------------------------
>
> Key: SPARK-21938
> URL: https://issues.apache.org/jira/browse/SPARK-21938
> Project: Spark
> Issue Type: Bug
> Components: Java API, Spark Core
> Affects Versions: 2.2.0
> Environment: Amazon EMR 5.8, varying instance types
> Reporter: Abbi McClintic
>
> Hello,
> My team has been experiencing a recurring unpredictable bug where only a
> partial write to CSV in S3 on one partition of our Dataset is performed. For
> example, in a Dataset of 10 partitions written to CSV in S3, we might see 9
> of the partitions as 2.8 GB in size, but one of them as 1.6 GB. However, the
> job does not exit with an error code.
> This becomes problematic in the following ways:
> 1. When we copy the data to Redshift, we get a bad decrypt error on the
> partial file, suggesting that the failure occurred at a weird byte in the
> file.
> 2. We lose data - sometimes as much as 10%.
> We don't see this problem with parquet, which we also use, but moving all of
> our data to parquet is not currently feasible. We're using the Java API.
> Any help on resolving this would be much appreciated.
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