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https://issues.apache.org/jira/browse/SPARK-23308?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16354784#comment-16354784
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Steve Loughran commented on SPARK-23308:
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bq. I have not heard this come up before as an issue in another implementation.

S3A's input stream handles an IOE other than EOF with a: increment metrics, 
close the stream, retry once; generally that causes the error to be recovered 
from. If not, you are into the unrecoverable-network-problems kind of problem, 
except for the special case of "you are recycling the pool of HTTP connections 
and should abort that TCP connection before trying anything else". I think 
there are opportunities to improve S3A there by aborting the connection before 
retrying.

I don't think Spark is in the position to  be clever about retries, as its too 
low-level as to what is retryable vs not; it would need a policy for all 
possible exceptions from all known FS clients and split them into "we can 
recover" from "no, fail fast"

Trying to come up with a good policy is (a) something the FS clients should be 
doing and (b) really hard to get right in the absence of frequent failures; its 
usually evolution based on bug reports. For example 
[S3ARetryPolicy|https://github.com/apache/hadoop/blob/trunk/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/S3ARetryPolicy.java#L87]
 is very much a WiP (HADOOP-14531).

Marcio: surprised you are getting so many socket timeouts. If this is happening 
in EC2 it's *potentially* throttling related; overloaded connection pools raise 
ConnectionPoolTimeoutException, apparently.

> 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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