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From "Hairong Kuang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-395) DFS Scalability: Incremental block reports
Date Fri, 26 Aug 2011 04:21:29 GMT

    [ https://issues.apache.org/jira/browse/HDFS-395?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13091564#comment-13091564
] 

Hairong Kuang commented on HDFS-395:
------------------------------------

My bad. I did not notice that 0.23 is branched. Updated the fix version to be 0.24 and updated
the change log of the jira to be in the trunk section. Unless anybody else really need it,
I do not plan to backport it to 0.23. 

> DFS Scalability: Incremental block reports
> ------------------------------------------
>
>                 Key: HDFS-395
>                 URL: https://issues.apache.org/jira/browse/HDFS-395
>             Project: Hadoop HDFS
>          Issue Type: Sub-task
>          Components: data-node, name-node
>            Reporter: dhruba borthakur
>            Assignee: Tomasz Nykiel
>             Fix For: 0.24.0
>
>         Attachments: blockReportPeriod.patch, explicitAcks.patch-3, explicitAcks.patch-4,
explicitAcks.patch-5, explicitAcks.patch-6, explicitDeleteAcks.patch
>
>
> I have a cluster that has 1800 datanodes. Each datanode has around 50000 blocks and sends
a block report to the namenode once every hour. This means that the namenode processes a block
report once every 2 seconds. Each block report contains all blocks that the datanode currently
hosts. This makes the namenode compare a huge number of blocks that practically remains the
same between two consecutive reports. This wastes CPU on the namenode.
> The problem becomes worse when the number of datanodes increases.
> One proposal is to make succeeding block reports (after a successful send of a full block
report) be incremental. This will make the namenode process only those blocks that were added/deleted
in the last period.

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