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From "Jiandan Yang (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HDFS-12200) Optimize CachedDNSToSwitchMapping to avoid cpu utilization is too high
Date Wed, 26 Jul 2017 08:36:00 GMT
Jiandan Yang  created HDFS-12200:
------------------------------------

             Summary: Optimize CachedDNSToSwitchMapping to avoid cpu utilization is too high
                 Key: HDFS-12200
                 URL: https://issues.apache.org/jira/browse/HDFS-12200
             Project: Hadoop HDFS
          Issue Type: Improvement
          Components: namenode
            Reporter: Jiandan Yang 


1. Background :
Our hadoop cluster is disaggregated storage and compute, HDFS is deployed to 600+ machines,
YARN is deployed to another machine pool where off-line job and online service are run, Yarn's
offline job will visit HDFS, but points The machines used for offline jobs are dynamically
changing because the online service has a higher priority, and when the online service is
idle, the machine will be assigned to offline tasks, and when the online service is busy,
it will seize the resources of the offline job.
We found that sometimes NameNode cpu utilization rate of 90% or even 100%. The most serious
is cpu utilization rate of 100% for a long time result in writing journalNode timeout, eventually
leading to NameNode hang up. The reason is  offline tasks running in a few hundred servers
access HDFS at the same time, NameNode resolve rack of client machine, started several hundred
sub-process. 

{code:java}
"process reaper"#10864 daemon prio=10 os_prio=0 tid=0x00007fe270a31800 nid=0x38d93 runnable
[0x00007fcdc36fc000]
   java.lang.Thread.State: RUNNABLE
        at java.lang.UNIXProcess.waitForProcessExit(Native Method)
        at java.lang.UNIXProcess.lambda$initStreams$4(UNIXProcess.java:301)
        at java.lang.UNIXProcess$$Lambda$7/1447689627.run(Unknown Source)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1147)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:622)
        at java.lang.Thread.run(Thread.java:834
{code}

Our configuration as follows:
{code:java}
net.topology.node.switch.mapping.impl = ScriptBasedMapping, 
net.topology.script.file.name = 'a python script'
{code}



2. Optimization
In order to solve these two problems, we have optimized the CachedDNSToSwitchMapping
(1) Added the DataNode IP list  to the file of  dfs.hosts configured. when NameNode starts
it  preloads DataNode rack information to the cache, get a batch of racks of hosts when running
script once (the corresponding configuration is net.topology.script.number,the default value
of 100)

(2) Step (1) has ensured that the cache has all the DataNodes’ rack,  so if the cache did
not hit, then the host must be a client machine, then directly return /default-rack,

(3) Each time you add new DataNodes you need to add the new DataNodes’ IP address to the
file specified by dfs.hosts, and then run command of bin/hdfs dfsadmin -refreshNodes, it will
put the newly added DataNodes’ rack into cache
(4) Add new configuration items dfs.namenode.topology.resolve-non-cache-host, the value is
false to open the above function, and the value is true to turn off the above functions, default
value is true to keep compatibility




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