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From "Ming Ma (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HDFS-7128) Decommission slows way down when it gets towards the end
Date Mon, 22 Sep 2014 22:22:35 GMT
Ming Ma created HDFS-7128:
-----------------------------

             Summary: Decommission slows way down when it gets towards the end
                 Key: HDFS-7128
                 URL: https://issues.apache.org/jira/browse/HDFS-7128
             Project: Hadoop HDFS
          Issue Type: Improvement
            Reporter: Ming Ma


When we decommission nodes across different racks, the decommission process becomes really
slow at the end, hardly making any progress. The problem is some blocks are on 3 decomm-in-progress
DNs and the way how replications are scheduled caused unnecessary delay. Here is the analysis.

When BlockManager schedules the replication work from neededReplication, it first needs to
pick the source node for replication via chooseSourceDatanode. The core policies to pick the
source node are:

1. Prefer decomm-in-progress node.

2. Only pick the nodes whose outstanding replication counts are below thresholds dfs.namenode.replication.max-streams
or dfs.namenode.replication.max-streams-hard-limit, based on the replication priority.


When we decommission nodes,

1. All the decommission nodes' blocks will be added to neededReplication.

2. BM will pick X number of blocks from neededReplication in each iteration. X is based on
cluster size and some configurable multiplier. So if the cluster has 2000 nodes, X will be
around 4000.

3. Given these 4000 nodes are on the same decomm-in-progress node A, A end up being chosen
as the source node of all these 4000 nodes. The reason the outstanding replication thresholds
don't kick is due to the implementation of BlockManager.computeReplicationWorkForBlocks; node.getNumberOfBlocksToBeReplicated()
remains zero given node.addBlockToBeReplicated is called after source node iteration.

{noformat}
...
      synchronized (neededReplications) {
        for (int priority = 0; priority < blocksToReplicate.size(); priority++) {
...
chooseSourceDatanode
...
        }


      for(ReplicationWork rw : work){
...
          rw.srcNode.addBlockToBeReplicated(block, targets);
...
      }
{noformat}
 
4. So several decomm-in-progress nodes A, B, C end up with 4000 node.getNumberOfBlocksToBeReplicated().

5. If we assume each node can replicate 5 blocks per minutes, it is going to take 800 minutes
to finish replication of these blocks.

6. Pending replication timeout kick in after 5 minutes. The items will be removed from the
pending replication queue and added back to neededReplication. The replications will then
be handled by other source nodes of these blocks. But the blocks still remain in nodes A,
B, C's pending replication queue, DatanodeDescriptor.replicateBlocks, so A, B, C continue
the replications of these blocks, although these blocks might have been replicated by other
DNs after replication timeout.

7. Some block' replicas exist on A, B, C and it is at the end of A's pending replication queue.
Even though the block's replication timeout, no source node can be chosen given A, B, C all
have high pending replication count. So we have to wait until A drains its pending replication
queue. Meanwhile, the items in A's pending replication queue have been taken care of by other
nodes and no longer under replicated.



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