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https://issues.apache.org/jira/browse/HDFS-13279?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16427895#comment-16427895
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Tao Jie commented on HDFS-13279:
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[~ajayydv] Thank you for your comments.
{quote}
Don't remove the default impl entry from core-default.xml.
Similarly we can do this with almost no change in Network Topology,
DFSNetworkTopology and TestBalancerWithNodeGroup. We can update
DatanodeManager#init to instantiate according to value of "net.topology.impl".
{quote}
Actually in original patch based on 2.8.2, we don't need to modify
core-default.xml, Network Topology, TestBalancerWithNodeGroup. It is a little
tricky in HDFS-11998 which set DFSNetworkTopology as default topology
implementation even though {{net.topology.impl}} is set to NetworkTopology. In
HDFS-11530, once {{dfs.use.dfs.network.topology}} is true, the implementation
is hard code to {{DFSNetworkTopology}} no matter what {{net.topology.impl}} is.
So we have to modify the behavior if we need to add a new topology
implementation and let it work. Maybe we could fix it in another Jira?
{quote}
L43, chooseDataNode: Instead of choosing datanode twice we can just call
super.chooseRandom if we overide chooseRandom in
NetworkTopologyWithWeightedRack. This way we can avoid calling chooseRandom
twice.
{quote}
It is OK if we use {{first choose a rack then choose a node}} logic in
{{chooseRandom}}. The purpose of a twice choosing is to mostly reuse the
current choosing logic, which make the code more easier:)
> Datanodes usage is imbalanced if number of nodes per rack is not equal
> ----------------------------------------------------------------------
>
> Key: HDFS-13279
> URL: https://issues.apache.org/jira/browse/HDFS-13279
> Project: Hadoop HDFS
> Issue Type: Bug
> Affects Versions: 2.8.3, 3.0.0
> Reporter: Tao Jie
> Assignee: Tao Jie
> Priority: Major
> Attachments: HDFS-13279.001.patch, HDFS-13279.002.patch,
> HDFS-13279.003.patch, HDFS-13279.004.patch, HDFS-13279.005.patch
>
>
> In a Hadoop cluster, number of nodes on a rack could be different. For
> example, we have 50 Datanodes in all and 15 datanodes per rack, it would
> remain 5 nodes on the last rack. In this situation, we find that storage
> usage on the last 5 nodes would be much higher than other nodes.
> With the default blockplacement policy, for each block, the first
> replication has the same probability to write to each datanode, but the
> probability for the 2nd/3rd replication to write to the last 5 nodes would
> much higher than to other nodes.
> Consider we write 50 blocks to such 50 datanodes. The first rep of 100 block
> would distirbuted to 50 node equally. The 2rd rep of blocks which the 1st rep
> is on rack1(15 reps) would send equally to other 35 nodes and each nodes
> receive 0.428 rep. So does blocks on rack2 and rack3. As a result, node on
> rack4(5 nodes) would receive 1.29 replications in all, while other node would
> receive 0.97 reps.
> ||-||Rack1(15 nodes)||Rack2(15 nodes)||Rack3(15 nodes)||Rack4(5 nodes)||
> |From rack1|-|15/35=0.43|0.43|0.43|
> |From rack2|0.43|-|0.43|0.43|
> |From rack3|0.43|0.43|-|0.43|
> |From rack4|5/45=0.11|0.11|0.11|-|
> |Total|0.97|0.97|0.97|1.29|
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