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Date: Fri, 26 Aug 2011 04:17:29 +0000 (UTC)
From: "Hairong Kuang (JIRA)" <jira@apache.org>
To: hdfs-issues@hadoop.apache.org
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Subject: [jira] [Updated] (HDFS-395) DFS Scalability: Incremental block
 reports
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     [ https://issues.apache.org/jira/browse/HDFS-395?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hairong Kuang updated HDFS-395:
-------------------------------

    Fix Version/s:     (was: 0.23.0)
                   0.24.0

> 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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