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From "Tsz Wo (Nicholas), SZE (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HDFS-1606) Provide a stronger data guarantee in the write pipeline
Date Tue, 08 Feb 2011 08:51:57 GMT

    [ https://issues.apache.org/jira/browse/HDFS-1606?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12991839#comment-12991839

Tsz Wo (Nicholas), SZE commented on HDFS-1606:

A straightforward approach is to
\(i) start \(\*) right after #1 and stall #2 until \(*) is done. 

If we feel comfortable, we may
(ii) start \(*) right after #1 in a separated thread and start #2 concurrently.  Once #3 is
done, join the thread and then combine the old data with the new data before #4.

Depending on the block size, a partial block may have several hundreds megabytes.  So \(*)
is an expensive operation which may potentially take a long time (in the order of seconds).
 (ii) has a lower latency but \(i) is a simpler solution.  How about we have \(i) in the first
implementation and have (ii) as a future improvement?

> Provide a stronger data guarantee in the write pipeline
> -------------------------------------------------------
>                 Key: HDFS-1606
>                 URL: https://issues.apache.org/jira/browse/HDFS-1606
>             Project: Hadoop HDFS
>          Issue Type: New Feature
>          Components: data-node, hdfs client
>            Reporter: Tsz Wo (Nicholas), SZE
>            Assignee: Tsz Wo (Nicholas), SZE
> In the current design, if there is a datanode/network failure in the write pipeline,
DFSClient will try to remove the failed datanode from the pipeline and then continue writing
with the remaining datanodes.  As a result, the number of datanodes in the pipeline is decreased.
 Unfortunately, it is possible that DFSClient may incorrectly remove a healthy datanode but
leave the failed datanode in the pipeline because failure detection may be inaccurate under
erroneous conditions.
> We propose to have a new mechanism for adding new datanodes to the pipeline in order
to provide a stronger data guarantee.

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