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

Mapreduce Race Condition — Big Job

  • #51197
    Upen K

    We are running a hige M/R job using HDP2.06. Cluster size is about 100 nodes and the job is big enough to consume all the containers in the cluster. When the reduce phase begins, and the map hasn’t finished yet, there comes a situation where reducers are running and awaiting results from unfinished Mappers. But schedulers doesn’t pre empty reduce slots for mappers to finish. W/o the pending mappers NOT completing, they are now engaged into deadlock situation. Looks like a huge bug. Does any one have any solution to this problem.


  • Author
  • #51198
    Kevin Risden

    You need to increase mapreduce.job.reduce.slowstart.completedmaps so that the reducers don’t start until a higher percentage of the mappers complete.

    Sheetal Dolas

    set your slow start number to higher like

    This way your reducers wont start until given % of mappers are finished.

    Additionally, you should avoid jobs that need very high number of mappers. Adjust your split sizes to do same work in less number of mappers

    Upen K

    mapreduce.job.reduce.slowstart.completedmaps=0.8 is a hack not a permanent solution. If the job is very big, even 0.8 may not server the purpose.

    reducing the no. of mappers by increasing the split size will lead to more spills on local disk.

    This is a basic M/R feature that if reducers are awaiting on Mappers to finish, schedulers should pre empt some of the reducers. we are running much bigger job in other cluster with cloudera CDH3U6 (very old) and its running fine.

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.