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From "dhruba borthakur (JIRA)" <j...@apache.org>
Subject [jira] Updated: (HADOOP-1079) DFS Scalability: optimize processing time of block reports
Date Wed, 16 May 2007 23:04:16 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-1079?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

dhruba borthakur updated HADOOP-1079:
-------------------------------------

    Attachment: blockReportPeriod.patch

Here is a sample patch that increases the blockReport periodicity from 1 hour to 1 day. It
also causes a blockReport to be sent after a failed heartbeat.

I would like some comments/feedback on this approach.

> DFS Scalability: optimize processing time of block reports
> ----------------------------------------------------------
>
>                 Key: HADOOP-1079
>                 URL: https://issues.apache.org/jira/browse/HADOOP-1079
>             Project: Hadoop
>          Issue Type: Bug
>          Components: dfs
>            Reporter: dhruba borthakur
>         Attachments: blockReportPeriod.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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