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HBase Administration Cookbook

You're reading from HBase Administration Cookbook

Product type Book

Published in Aug 2012

Publisher Packt

ISBN-13 9781849517140

Pages 332 pages

Edition 1st Edition

Languages

Concepts

Database Administration

Author (1):

Yifeng Jiang

Table of Contents (16) Chapters

HBase Administration Cookbook

Credits

About the Author

Acknowledgement

About the Reviewers

www.PacktPub.com

Preface

Setting Up HBase Cluster

Data Migration

Using Administration Tools

Backing Up and Restoring HBase Data

Monitoring and Diagnosis

Maintenance and Security

Troubleshooting

Basic Performance Tuning

Advanced Configurations and Tuning

Backing up NameNode metadata

As HBase runs within HDFS, in addition to taking care of the HBase cluster, it is also important to keep your HDFS running on a healthy status. NameNode is the most important component in an HDFS cluster. A NameNode crash makes the entire HDFS cluster inaccessible. The metadata of an HDFS cluster, including the filesystem image and edit log, is managed by NameNode.

We need to protect our NameNode metadata for two situations:

Metadata lost in the event of a crash
Metadata corruption by any reason

For the first situation, we can set up NameNode to write its metadata to its local disk, along with an NFS mount. As described in the Setting up multiple, highly available (HA) masters recipe, in Chapter 1, Setting Up HBase Cluster, we can even set up multiple NameNode nodes to achieve high availability.

Our solution for the second situation, is to back up the metadata frequently so that we can restore the NameNode state in case of metadata corruption.

We will describe...

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Authors (1)

Yifeng Jiang

Yifeng Jiang is a Hadoop and HBase Administrator and Developer at Rakutenthe largest e-commerce company in Japan. After graduating from the University of Science and Technology of China with a B.S. in Information Management Systems, he started his career as a professional software engineer, focusing on Java development. In 2008, he started looking over the Hadoop project. In 2009, he led the development of his previous company's display advertisement data infrastructure using Hadoop and Hive. In 2010, he joined his current employer, where he designed and implemented the Hadoop- and HBase-based, large-scale item ranking system. He is also one of the members of the Hadoop team in the company, which operates several Hadoop/HBase clusters

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