The Hortonworks Community Connection is now live. A completely rebuilt Q&A forum, Knowledge Base, Code Hub and more, backed by the experts in the industry.

You will be redirected here in 10 seconds. If your are not redirected, click here to visit the new site.

The legacy Hortonworks Forum is now closed. You can view a read-only version of the former site by clicking here. The site will be taken offline on January 31,2016

MapReduce Forum

HDP 1.3 JobTracker hitting Out of Memory

  • #38131

    We are using HDP 1.3, and JT is Version:
    We are seeing a steady growth of the JobTracker heap , and finally it hits Java heap space error.

    The below are the cluster specs;
    Nodes – 4
    Map Tasks – 32
    Reduce Tasks – 12
    Job Submissions a day = 2000 (around 100 jobs out of this runs with 250+ maps tasks)
    Job Tracker heap = 2G

    With some good amount of jobs,the JT is lasting hardly for 3-4 days.
    Looking at the heap, there are like many instances ~8K of DFSClient which gets me suspicous.

    Any help appreciated.

  • Author
  • #38242
    Robert Molina

    Hi Vivek,
    Are you using ambari installation or manual? If manual see if increasing the Xmx for jobtracker in the file helps.

    Kind Regards,


    I am using manual. The initial Xmx was 2G, for which it hit OOM. Increasing it to 4G also results in an OOM.
    There are tens and thousands of DFSClients lying in the Jobtracker heap.


    Anyone can suggest anything on this ?


    Hi Vivek,

    Please configure mapred.jobtracker.retirejob.interval to no more that one day 21600000 (24x60x60x1000) or even less. And mapred.jobtracker.complete.maximum should be set to a low number as well. In addition, mapred.jobtracker.completeuserjobs.maximum should be set to no more than 5 as this property is on a user level.



    Hi Abdelrahman,
    Thanks for the suggestion , but looks like out defaults are of the value that you have mentioned. The below are the confs
    mapred.jobtracker.retirejob.interval = 21600000
    mapred.job.tracker.retiredjobs.cache.size = 30
    mapred.jobtracker.completeuserjobs.maximum = 5
    mapred.job.tracker.jobhistory.lru.cache.size 5

    Sorry I couldn’t figure out the value for the property mapred.jobtracker.complete.maximum.
    Is there any implication on mapreduce.job.restart.recover = true (default value)



    Hi Vivek,

    There is no implication on mapreduce.job.restart.recover = true that I know off. And the configuration ” mapred.jobtracker.complete.maximum.” is a typo.



    So even with all these conf set we are still hitting the OOM. Is this incident reported
    To me from the heap dump this looks like
    (I am verifying this)
    Will there be any HDP release which will have this fix ?


    Koelli Mungee

    Hi Vivek,

    Thanks, please let us know how you have verified that it is the same issue. We did ship in HDP 1.3.2. I believe you are on HDP 1.3.0.

    Can you also paste in the HADOOP_JOBTRACKER_OPTS?


    Jason Morse

    We just had an oom on our job tracker as well. Is this a bug in 1.3.0?


    Hi All,

    Please find my JOBTRACKER OPTS;
    HADOOP_JOBTRACKER_OPTS=”-server -XX:ParallelGCThreads=8 -XX:+UseConcMarkSweepGC -XX:ErrorFile=/var/log/hadoop/$USER/hs_err_pid%p.log -XX:NewSize=200m -XX:MaxNewSize=200m -Xloggc:/var/log/hadoop/$USER/gc.log-`date +’%Y%m%d%H%M’` -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -Xmx4096m,DRFAS -Dmapred.audit.logger=INFO,MRAUDIT -Dhadoop.mapreduce.jobsummary.logger=INFO,JSA ${HADOOP_JOBTRACKER_OPTS}”

    I have verified that the problem is with MAPREDUCE-5351, with below two params the JT is no longer having any issues.



    The JT is still running with > 10K job submissions , out of which 3K is having around 250 Map Tasks each. And heap used so far is 360MB :)

    Koelli, Thanks for letting me know this.I am on HDP 1.3.0 Let me checkout HDP 1.3.2. Since we are already on production need to see how to upgrade and test.


    Koelli Mungee

    Thanks for the update Vivek.

    Jason, yes, MAPREDUCE-5351 exists in HDP 1.3.0 and shipped in HDP 1.3.2


The topic ‘HDP 1.3 JobTracker hitting Out of Memory’ is closed to new replies.

Support from the Experts

A HDP Support Subscription connects you experts with deep experience running Apache Hadoop in production, at-scale on the most demanding workloads.

Enterprise Support »

Become HDP Certified

Real world training designed by the core architects of Hadoop. Scenario-based training courses are available in-classroom or online from anywhere in the world

Training »

Hortonworks Data Platform
The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly enterprise grade having been built, tested and hardened with enterprise rigor.
Get started with Sandbox
Hortonworks Sandbox is a self-contained virtual machine with Apache Hadoop pre-configured alongside a set of hands-on, step-by-step Hadoop tutorials.
Modern Data Architecture
Tackle the challenges of big data. Hadoop integrates with existing EDW, RDBMS and MPP systems to deliver lower cost, higher capacity infrastructure.