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Posted to common-dev@hadoop.apache.org by "dhruba borthakur (JIRA)" <ji...@apache.org> on 2009/05/03 02:55:30 UTC

[jira] Issue Comment Edited: (HADOOP-3799) Design a pluggable interface to place replicas of blocks in HDFS

    [ https://issues.apache.org/jira/browse/HADOOP-3799?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12705361#action_12705361 ] 

dhruba borthakur edited comment on HADOOP-3799 at 5/2/09 5:55 PM:
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@Stefan: I completely agree with you. This patch should enable researchers to experiment with various modes of HDFS block placement without changing code-hdfs code. I plan on using this to co-locate blocks from hdfs datasets that are frequently scanner together in a small number of datanodes so that such a "join" operation gets better node/rack locality.

      was (Author: dhruba):
    @Stefan: I complete agree with you. This patch should enable researchers to experiment with various modes of HDFS block placement without changing code-hdfs code. I plan on using this to co-locate blocks from hdfs datasets that are frequently scanner together in a small number of datanodes so that such a "join" operation gets better node/rack locality.
  
> Design a pluggable interface to place replicas of blocks in HDFS
> ----------------------------------------------------------------
>
>                 Key: HADOOP-3799
>                 URL: https://issues.apache.org/jira/browse/HADOOP-3799
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: dfs
>            Reporter: dhruba borthakur
>            Assignee: dhruba borthakur
>         Attachments: BlockPlacementPluggable.txt
>
>
> The current HDFS code typically places one replica on local rack, the second replica on remote random rack and the third replica on a random node of that remote rack. This algorithm is baked in the NameNode's code. It would be nice to make the block placement algorithm a pluggable interface. This will allow experimentation of different placement algorithms based on workloads, availability guarantees and failure models.

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