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

Setting up Ganglia to monitor an HBase cluster


One of the most important parts of HBase operation tasks is to monitor the cluster and make sure it is running as expected. HBase inherits its monitoring APIs from Hadoop. It exposes a lot of metrics, which gives the insight information of the cluster's current status, including region-based statistics, RPC details, and the Java Virtual Machine (JVM) memory and garbage collection data.

These metrics are then subsequently configured to expose to JMX and Ganglia, which makes the metrics visible through graphs. Ganglia is the recommended tool for monitoring large-scale clusters. Ganglia itself is a scalable, distributed system; it is said to be able to handle clusters with 2000 nodes.

We will describe how to use Ganglia to monitor an HBase cluster in this recipe. We will install Ganglia Monitoring Daemon (Gmond) on each node in the cluster, which will gather the server and HBase metrics of that node. These metrics are then subsequently polled...