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https://issues.apache.org/jira/browse/HDFS-1094?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12856097#action_12856097
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Karthik Ranganathan commented on HDFS-1094:
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The issue I see with 1 (which may not be a big deal) is that if more racks are
added, then the placement policy cannot utilize the new, emptier machines more
efficiently without re-balancing data. Would a hybrid help? Replica 1 is chosen
at random from (r-1) and the next replica using scheme 2 (excluding the node on
rack r-1).
@Brian:
I think this change protects against node failures more than rack failures.
Lets say the replication factor is three. If you calculate the probability of
data loss if *any* 3 machines fail in the cluster at the same time, then the
placement matters:
1) If the blocks are scattered across all the machines, then any 3 machines
failing will contribute towards data loss.
2) If a given block (by virtue of the new replication scheme) is placed only on
a subset of machines, then the probability of data loss is reduced from any 3
machines failing to 3 machines in that subset failing. Failures of machines in
the distinct subsets don't contribute to data loss.
> Intelligent block placement policy to decrease probability of block loss
> ------------------------------------------------------------------------
>
> Key: HDFS-1094
> URL: https://issues.apache.org/jira/browse/HDFS-1094
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: name-node
> Reporter: dhruba borthakur
> Assignee: dhruba borthakur
>
> The current HDFS implementation specifies that the first replica is local and
> the other two replicas are on any two random nodes on a random remote rack.
> This means that if any three datanodes die together, then there is a
> non-trivial probability of losing at least one block in the cluster. This
> JIRA is to discuss if there is a better algorithm that can lower probability
> of losing a block.
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