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https://issues.apache.org/jira/browse/HDFS-1595?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12986589#action_12986589
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Tsz Wo (Nicholas), SZE commented on HDFS-1595:
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> I'll be honest: I don't know the new Append code in trunk very well. I
> thought the client called nn.updatePipeline() whenever a node was removed
> from the pipeline. That's not the case?
You are actually right about the new append codes. I am sorry that I was
mostly looking at the 0.20 codes. It will work for 0.22 but we need to change
protocol for 0.20. Nice.
> DFSClient may incorrectly detect datanode failure
> -------------------------------------------------
>
> Key: HDFS-1595
> URL: https://issues.apache.org/jira/browse/HDFS-1595
> Project: Hadoop HDFS
> Issue Type: Bug
> Components: data-node, hdfs client
> Affects Versions: 0.20.4
> Reporter: Tsz Wo (Nicholas), SZE
> Priority: Critical
> Attachments: hdfs-1595-idea.txt
>
>
> Suppose a source datanode S is writing to a destination datanode D in a write
> pipeline. We have an implicit assumption that _if S catches an exception
> when it is writing to D, then D is faulty and S is fine._ As a result,
> DFSClient will take out D from the pipeline, reconstruct the write pipeline
> with the remaining datanodes and then continue writing .
> However, we find a case that the faulty machine F is indeed S but not D. In
> the case we found, F has a faulty network interface (or a faulty switch port)
> in such a way that the faulty network interface works fine when sending out a
> small amount of data, say 1MB, but it fails when sending out a large amount
> of data, say 100MB.
> It is even worst if F is the first datanode in the pipeline. Consider the
> following:
> # DFSClient creates a pipeline with three datanodes. The first datanode is F.
> # F catches an IOException when writing to the second datanode. Then, F
> reports the second datanode has error.
> # DFSClient removes the second datanode from the pipeline and continue
> writing with the remaining datanode(s).
> # The pipeline now has two datanodes but (2) and (3) repeat.
> # Now, only F remains in the pipeline. DFSClient continues writing with one
> replica in F.
> # The write succeeds and DFSClient is able to *close the file successfully*.
> # The block is under replicated. The NameNode schedules replication from F
> to some other datanode D.
> # The replication fails from the same reason. D reports to the NameNode that
> the replica in F is corrupted.
> # The NameNode marks the replica in F is corrupted.
> # The block is corrupted since no replica is available.
> This is a *data loss* scenario.
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