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

Cluster replication


HBase supports cluster replication, which is a way to copy data between the HBase clusters. For example, it can be used as a way to easily ship edits from a real-time frontend cluster to a batch purpose cluster on the backend.

The basic architecture of an HBase replication is very practical. The master cluster captures write ahead log (WAL), and puts replicable Key/Values (edits of the column family with replication support) from the log into the replication queue. The replication message is then sent to the peer cluster, and then replayed on that cluster using its normal HBase client API. The master cluster also keeps the current position of the WAL being replicated in ZooKeeper for failure recovery.

Because the HBase replication is done asynchronously, the clusters participating in the replication can be geographically distant. It is not a problem if the connections between them are offline for some time, as the master cluster will track the replication, and recover...