Book Image

HBase Administration Cookbook

By : Yifeng Jiang
Book Image

HBase Administration Cookbook

By: Yifeng Jiang

Overview of this book

As an Open Source distributed big data store, HBase scales to billions of rows, with millions of columns and sits on top of the clusters of commodity machines. If you are looking for a way to store and access a huge amount of data in real-time, then look no further than HBase.HBase Administration Cookbook provides practical examples and simple step-by-step instructions for you to administrate HBase with ease. The recipes cover a wide range of processes for managing a fully distributed, highly available HBase cluster on the cloud. Working with such a huge amount of data means that an organized and manageable process is key and this book will help you to achieve that.The recipes in this practical cookbook start from setting up a fully distributed HBase cluster and moving data into it. You will learn how to use all of the tools for day-to-day administration tasks as well as for efficiently managing and monitoring the cluster to achieve the best performance possible. Understanding the relationship between Hadoop and HBase will allow you to get the best out of HBase so the book will show you how to set up Hadoop clusters, configure Hadoop to cooperate with HBase, and tune its performance.
Table of Contents (16 chapters)
HBase Administration Cookbook
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface

Row counter


The count command in HBase Shell is a straightforward way to count the row numbers on an HBase table. However, running the count command on a table with a huge amount of data might take a long time to complete. A better approach for this case is to use the RowCounter class. This class will kick a MapReduce job to count the row number on a table, which is much more efficient than the count command.

We will describe the usage of RowCounter in this recipe.

Getting ready

Make sure your Hadoop and HBase clusters are running. MapReduce is also required; if it is not running, start it by using the following command on your JobTracker server:

hadoop@master1$ $HADOOP_HOME/bin/start-mapred.sh

Log in to your HBase client node.

How to do it...

To run a row counter MapReduce job on the hly_temp table, follow these steps:

  1. 1. Add a ZooKeeper JAR file to the Hadoop class path on your client node:

    hadoop@client1$ vi $HADOOP_HOME/conf/hadoop-env.sh
    HBASE_HOME=/usr/local/hbase/current
    export HADOOP_CLASSPATH...