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https://issues.apache.org/jira/browse/HDFS-14292?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16772457#comment-16772457
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Erik Krogen commented on HDFS-14292:
------------------------------------

Hi [~belugabehr], the reasoning makes sense to me but I'm curious if there is 
any context that we are missing about why a new thread is used each time 
previously, since a thread pool seems fairly obvious. Have you done any digging 
in the history to see if anything is obvious?

Do you have any benchmarks to show that this strategy is better in any way?

> Introduce Java ExecutorService to DataXceiverServer
> ---------------------------------------------------
>
>                 Key: HDFS-14292
>                 URL: https://issues.apache.org/jira/browse/HDFS-14292
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: datanode
>    Affects Versions: 3.2.0
>            Reporter: BELUGA BEHR
>            Assignee: BELUGA BEHR
>            Priority: Major
>         Attachments: HDFS-14292.1.patch, HDFS-14292.2.patch, 
> HDFS-14292.3.patch
>
>
> I wanted to investigate {{dfs.datanode.max.transfer.threads}} from 
> {{hdfs-site.xml}}.  It is described as "Specifies the maximum number of 
> threads to use for transferring data in and out of the DN."   The default 
> value is 4096.  I found it interesting because 4096 threads sounds like a lot 
> to me.  I'm not sure how a system with 8-16 cores would react to this large a 
> thread count.  Intuitively, I would say that the overhead of context 
> switching would be immense.
> During mt investigation, I discovered the 
> [following|https://github.com/apache/hadoop/blob/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/DataXceiverServer.java#L203-L216]
>  setup in the {{DataXceiverServer}} class:
> # A peer connects to a DataNode
> # A new thread is spun up to service this connection
> # The thread runs to completion
> # The tread dies
> It would perhaps be better if we used a thread pool to better manage the 
> lifecycle of the service threads and to allow the DataNode to re-use existing 
> threads, saving on the need to create and spin-up threads on demand.
> In this JIRA, I have added a couple of things:
> # Added a thread pool to {{DataXceiverServer}} class that, on demand, will 
> create up to {{dfs.datanode.max.transfer.threads}}.  A thread that has 
> completed its prior duties will stay idle for up to 60 seconds 
> (configurable), it will be retired if no new work has arrived.
> # Added new methods to the {{Peer}} Interface to allow for better logging and 
> less code within each Thread ({{DataXceiver}}).
> # Updated the Thread code ({{DataXceiver}}) regarding its interactions with 
> {{blockReceiver}} instance variable



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