BELUGA BEHR created HDFS-14292:
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Summary: Introduce Java ExecutorService to DataNode
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
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 that will always maintain a single thread running, always
awaiting a new connection should one arrive. On-demand, it will create up to
{{dfs.datanode.max.transfer.threads}}. A thread that has completed its prior
duties will stay idle for up to 30 seconds, 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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