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From "Tomasz Nykiel (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-395) DFS Scalability: Incremental block reports
Date Fri, 12 Aug 2011 04:32:27 GMT

    [ https://issues.apache.org/jira/browse/HDFS-395?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13083916#comment-13083916
] 

Tomasz Nykiel commented on HDFS-395:
------------------------------------

@Nicholas

I will follow up after Aug 16th. I am away in Asia now, and I don't have access to any dev
environment. Thanks.

> 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
>         Attachments: blockReportPeriod.patch, explicitAcks.patch-3, 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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