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From "dhruba borthakur (JIRA)" <j...@apache.org>
Subject [jira] Created: (HADOOP-1079) DFS Scalability: optimize processing time of block reports
Date Wed, 07 Mar 2007 17:59:24 GMT
DFS Scalability: optimize processing time of block reports
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                 Key: HADOOP-1079
                 URL: https://issues.apache.org/jira/browse/HADOOP-1079
             Project: Hadoop
          Issue Type: Bug
          Components: dfs
            Reporter: dhruba borthakur


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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