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https://issues.apache.org/jira/browse/SPARK-23308?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16357266#comment-16357266
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Steve Loughran commented on SPARK-23308:
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bq. Other option would be creating a special exception
(CorruptedFileException?) that could be thrown by FS implementations and let
them decide what is a corrupted file or just a transient error.
Its pretty hard to get consistent semantics on "working" FS behaviour, let
alone failure modes; it's why the Hadoop FS specs and compliance tests have the
notion of strict failure "does what HDFS does" and "lax", "raises an IOE".
AFAIK HDFS raises {{ChecksumException}} on checksum errors, I don't know what
it does on. say. decryption failure or erasure coding problems. and don't
really want to look. You could try to add a parent class here, "Unrecoverable
IOE" & see about getting it in to everything over time.
Common prefixes and the classic year=2018/month=12 partitioning is pretty
pathological for S3. But like you say, 503 is the standard response, though it
may be caught in the AWS SDK. Talk to the AWS people
> 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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