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https://issues.apache.org/jira/browse/HADOOP-1652?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12515859
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Stu Hood commented on HADOOP-1652:
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{quote}
...among which we should favor data nodes that are on the same rack as the
target data node.
{quote}
This is a tradeoff though... one of the reasons for recording what racks blocks
are on is to prevent putting "all of your eggs in one basket" so to speak (See
the middle paragraph of
http://lucene.apache.org/hadoop/hdfs_design.html#Data+Replication ).
> Rebalance data blocks when new data nodes added or data nodes become full
> -------------------------------------------------------------------------
>
> Key: HADOOP-1652
> URL: https://issues.apache.org/jira/browse/HADOOP-1652
> Project: Hadoop
> Issue Type: New Feature
> Components: dfs
> Affects Versions: 0.13.0
> Reporter: Hairong Kuang
> Assignee: Hairong Kuang
> Fix For: 0.15.0
>
>
> When a new data node joins hdfs cluster, it does not hold much data. So any
> map task assigned to the machine most likely does not read local data, thus
> increasing the use of network bandwidth. On the other hand, when some data
> nodes become full, new data blocks are placed on only non-full data nodes,
> thus reducing their read parallelism.
> This jira aims to find an approach to redistribute data blocks when imbalance
> occurs in the cluster. An solution should meet the following requirements:
> 1. It maintains data availablility guranteens in the sense that rebalancing
> does not reduce the number of replicas that a block has or the number of
> racks that the block resides.
> 2. An adminstrator should be able to invoke and interrupt rebalancing from a
> command line.
> 3. Rebalancing should be throttled so that rebalancing does not cause a
> namenode to be too busy to serve any incoming request or saturate the network.
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