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https://issues.apache.org/jira/browse/HDFS-395?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13082565#comment-13082565
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Hadoop QA commented on HDFS-395:
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-1 overall. Here are the results of testing the latest attachment
http://issues.apache.org/jira/secure/attachment/12488048/explicitAcks.patch-3
against trunk revision 1155998.
+1 @author. The patch does not contain any @author tags.
+1 tests included. The patch appears to include 6 new or modified tests.
-1 patch. The patch command could not apply the patch.
Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/1061//console
This message is automatically generated.
> DFS Scalability: Incremental block reports
> ------------------------------------------
>
> Key: HDFS-395
> URL: https://issues.apache.org/jira/browse/HDFS-395
> Project: Hadoop HDFS
> Issue Type: Sub-task
> 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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