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

HBase Forum

Mappers which are reading the Hbase table's regions are not running local

  • #56862
    SambaSivaRao Y
    Participant

    Hi,

    We are having MR job which reads the Table’s data, after performing some operations commits the data back.
    We are having two regions servers and The table is having 20milion records on two Machines in 15 regions ( 8 regions on Machine1 and 7 regions on Machine2).
    When we run the MR job,Some Mappers on Machine1 are reading the regions on Machine2. This is causing the MR job to take hours of time to complete.

    The mappers are reading like this every time.

    Can someone help us on this.

    Thanks,
    SambaSiva

The forum ‘HBase’ 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.