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From "Sean Mackrory (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HADOOP-15541) AWS SDK can mistake stream timeouts for EOF and throw SdkClientExceptions
Date Thu, 14 Jun 2018 20:56:00 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-15541?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16512974#comment-16512974

Sean Mackrory commented on HADOOP-15541:

Also filed an issue with the SDK: [https://github.com/aws/aws-sdk-java/issues/1630.] But like
I said, I'm not sure what the point is or if there's anything wrong with just aborting on
SdkClientExceptions since we'll have to fail at some point anyway.

> AWS SDK can mistake stream timeouts for EOF and throw SdkClientExceptions
> -------------------------------------------------------------------------
>                 Key: HADOOP-15541
>                 URL: https://issues.apache.org/jira/browse/HADOOP-15541
>             Project: Hadoop Common
>          Issue Type: Bug
>            Reporter: Sean Mackrory
>            Assignee: Sean Mackrory
>            Priority: Major
> I've gotten a few reports of read timeouts not being handled properly in some Impala
workloads. What happens is the following sequence of events (credit to Sailesh Mukil for figuring
this out):
>  * S3AInputStream.read() gets a SocketTimeoutException when it calls wrappedStream.read()
>  * This is handled by onReadFailure -> reopen -> closeStream. When we try to drain
the stream, SdkFilterInputStream.read() in the AWS SDK fails because of checkLength. The underlying
Apache Commons stream returns -1 in the case of a timeout, and EOF.
>  * The SDK assumes the -1 signifies an EOF, so assumes the bytes read must equal expected
bytes, and because they don't (because it's a timeout and not an EOF) it throws an SdkClientException.
> This is tricky to test for without a ton of mocking of AWS SDK internals, because you
have to get into this conflicting state where the SDK has only read a subset of the expected
bytes and gets a -1.
> closeStream will abort the stream in the event of an IOException when draining. We could
simply also abort in the event of an SdkClientException. I'm testing that this results in
correct functionality in the workloads that seem to hit these timeouts a lot, but all the
s3a tests continue to work with that change. I'm going to open an issue with the AWS SDK Github
as well, but I'm not sure what the ideal outcome would be unless there's a good way to distinguish
between a stream that has timed out and a stream that read all the data without huge rewrites.

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