Sign Up

Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.

Have an account? Sign In

Have an account? Sign In Now

Sign In

Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.

Sign Up Here

Forgot Password?

Don't have account, Sign Up Here

Forgot Password

Lost your password? Please enter your email address. You will receive a link and will create a new password via email.

Have an account? Sign In Now

You must login to ask a question.

Forgot Password?

Need An Account, Sign Up Here

Please briefly explain why you feel this question should be reported.

Please briefly explain why you feel this answer should be reported.

Please briefly explain why you feel this user should be reported.

Sign InSign Up

The Archive Base

The Archive Base Logo The Archive Base Logo

The Archive Base Navigation

  • Home
  • SEARCH
  • About Us
  • Blog
  • Contact Us
Search
Ask A Question

Mobile menu

Close
Ask a Question
  • Home
  • Add group
  • Groups page
  • Feed
  • User Profile
  • Communities
  • Questions
    • New Questions
    • Trending Questions
    • Must read Questions
    • Hot Questions
  • Polls
  • Tags
  • Badges
  • Buy Points
  • Users
  • Help
  • Buy Theme
  • SEARCH
Home/ Questions/Q 8601517
In Process

The Archive Base Latest Questions

Editorial Team
  • 0
Editorial Team
Asked: June 12, 20262026-06-12T01:51:47+00:00 2026-06-12T01:51:47+00:00

We have a hadoop+hbase cluster on amazon EMR with the default configuration, so that

  • 0

We have a hadoop+hbase cluster on amazon EMR with the default configuration, so that both mapred.child.tmp and hbase.tmp.dir point to /tmp. Our cluster has been running for a while and now /tmp is 500Gb, compared to 70Gb for actual /hbase data.

This kind of difference seems too much, are we supposed to periodically delete some of the /tmp data?

  • 1 1 Answer
  • 0 Views
  • 0 Followers
  • 0
Share
  • Facebook
  • Report

Leave an answer
Cancel reply

You must login to add an answer.

Forgot Password?

Need An Account, Sign Up Here

1 Answer

  • Voted
  • Oldest
  • Recent
  • Random
  1. Editorial Team
    Editorial Team
    2026-06-12T01:51:48+00:00Added an answer on June 12, 2026 at 1:51 am

    After some investigation I found that the largest part of our /tmp data was created by failed mapreduce tasks during Amazon’s automatic backup of Hbase to S3. Our successful mapreduce tasks don’t leave much data in /tmp.

    We have decided to disable Amazon’s automatic backup and implement our own backup script using Hbase tool for importing/exporting tables.

    • 0
    • Reply
    • Share
      Share
      • Share on Facebook
      • Share on Twitter
      • Share on LinkedIn
      • Share on WhatsApp
      • Report

Sidebar

Related Questions

My situation is the following: I have a 20-node Hadoop/HBase cluster with 3 ZooKeepers.
I have setup a Hadoop cluster containing 5 nodes on Amazon EC2. Now, when
I have a cluster that uses Hadoop 1.0.0 and I would like to run
I currently have a number of databases in a hadoop cluster and wish to
I have a third-party class that I am trying to use in Hadoop, and
I have Installed hadoop and hbase cdh3u2. In hadoop i have a file at
I am a newbie to Hadoop. I have been reading that HDFS is mostly
I have hadoop job with tasks that are expected to run for significant length
I am starting on a new Hadoop project that will have multiple hadoop jobs(and
I have sucessfully installed Hypertable on top of Hadoop on a small cluster of

Explore

  • Home
  • Add group
  • Groups page
  • Communities
  • Questions
    • New Questions
    • Trending Questions
    • Must read Questions
    • Hot Questions
  • Polls
  • Tags
  • Badges
  • Users
  • Help
  • SEARCH

Footer

© 2021 The Archive Base. All Rights Reserved
With Love by The Archive Base

Insert/edit link

Enter the destination URL

Or link to existing content

    No search term specified. Showing recent items. Search or use up and down arrow keys to select an item.