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

Precreating regions before moving data into HBase


Each HBase row belongs to a particular region. A region holds a range of sorted HBase rows. Regions are deployed and managed by a region server.

When we create a table in HBase, the table starts with a single region. All data inserted into the table goes to the single region, first. Data keeps being inserted, and when it reaches a threshold, the region will be split into two halves. This is called region splitting. Split regions will be distributed to other region servers, so that the load can be balanced among the clusters.

As you can imagine, if we can initialize the table with precreated regions, using an appropriate algorithm, the load of the data migration will be balanced over the entire cluster, which increases data load speed significantly.

We will describe how to create a table with precreated regions in this recipe.

Getting ready

Log in to your HBase client node.

How to do it...

Execute the following command on the client node:

$ $HBASE_HOME...