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

Parallel Reducer execution never goes above two…

  • #50719
    Rupert Bailey

    I can’t seem to get my HDP instance to run any more than two reducers in parallel, even though I’ve got 4 processors 8GB ram and small JVM’s allocated to the instance. I am running a 10M row teragen’ed terasort requesting 4 reducer instances with the following command:

    hadoop jar /usr/lib/hadoop/hadoop-examples.jar terasort -Dmapred.reduce.tasks=4 ./terasort-input ./terasort-output

    Values that I have set in the mapred-site.xml file are:

    (4 reducers appear on localhost:50030/scheduler for this default queue)

    I have the following specifications:

    Hadoop Version: 1.3.2
    Install Method: Ambari
    Nodes: 1
    Operating System: Centos 6.5 Desktop
    Virtual Machine: VMWare.vmx 8GB allocated ram, 4 allocated virtual CPU’s
    Physical Machine: 16GB Ram 2 Core Hyperthreaded i5-3320 (4 threads)

    What do I need to tweek to get this to run 4 reducers at once? I have been able to make it do 4 reducers, but only two at once.

  • Author
  • #50771
    Rupert Bailey

    Okay the solution was to increase mapred.cluster.reduce.memory.mb

    mapred.cluster.reduce.memory.mb=768MB #allowed 2 reducers to run at once
    mapred.cluster.reduce.memory.mb=1536MB #allowed all 4 reducers to run at once.

    So it seems this is a cluster wide memory setting that sets the limit of reducer task memory across the cluster of each slot allocation. But that’s a guess Feel free to comment if you understand why this is the case. :)

The forum ‘MapReduce’ is closed to new topics and 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.