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https://issues.apache.org/jira/browse/SPARK-23308?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16354250#comment-16354250
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Márcio Furlani Carmona commented on SPARK-23308:
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Yeah, I set it back to `ignoreCorruptFiles=false` to prevent this. But then if
there's indeed a corrupt file, our job will never succeed until we fix that.
The biggest problem for me was that silent failure you mentioned. I just found
out there was something wrong after running a job for the same input multiple
times and noticing some missing data, then I started investigating the reason
why and figured out it was due to this flag and the SocketTimeoutException I
mentioned.
I agree the documentation should at least mention the risks of setting this
flags and for which exceptions it considers the data as corrupt. Right now I
believe this flag is not even documented officially, is it?
https://spark.apache.org/docs/latest/configuration.html
> ignoreCorruptFiles should not ignore retryable IOException
> ----------------------------------------------------------
>
> Key: SPARK-23308
> URL: https://issues.apache.org/jira/browse/SPARK-23308
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.1
> Reporter: Márcio Furlani Carmona
> Priority: Minor
>
> When `spark.sql.files.ignoreCorruptFiles` is set it totally ignores any kind
> of RuntimeException or IOException, but some possible IOExceptions may happen
> even if the file is not corrupted.
> One example is the SocketTimeoutException which can be retried to possibly
> fetch the data without meaning the data is corrupted.
>
> See:
> https://github.com/apache/spark/blob/e30e2698a2193f0bbdcd4edb884710819ab6397c/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala#L163
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