Yifeng Jiang - HBase Administration Cookbook
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- Book:HBase Administration Cookbook
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Master HBase configuration and administration for optimum database performance
- Move large amounts of data into HBase and learn how to manage it efficiently
- Set up HBase on the cloud, get it ready for production, and run it smoothly with high performance
- Maximize the ability of HBase with the Hadoop eco-system including HDFS, MapReduce, Zookeeper, and Hive
In Detail
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.
What you will learn from this book
- Set up a fully distributed, highly available HBase cluster and load data into it using the normal client API or your own MapReduce job
- Access data in HBase via HBase Shell or Hive using its SQL-like query language
- Backup and restore HBase table, along with its data distribution, and move or replicate data between different HBase clusters
- Gather metrics then show them in graphs, monitor the clusters status, and get notified if thresholds are exceeded
- Tune your kernel settings with JVM GC, Hadoop, and HBase configuration to maximize the performance
- Discover troubleshooting tools and tips in order to avoid the most commonly-found problems with HBase
- Gain optimum performance with data compression, region splits, and by manually managing compaction
- Learn advanced configuration and tuning for read and write-heavy clusters
Approach
As part of Packts cookbook series, each recipe offers a practical, step-by-step solution to common problems found in HBase administration.
Who this book is written for
This book is for HBase administrators, developers, and will even help Hadoop administrators. You are not required to have HBase experience, but are expected to have a basic understanding of Hadoop and MapReduce.
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Copyright 2012 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: August 2012
Production Reference: 1080812
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK..
ISBN 978-1-84951-714-0
www.packtpub.com
Cover Image by Asher Wishkerman ( <> )
Author
Yifeng Jiang
Reviewers
Masatake Iwasaki
Tatsuya Kawano
Michael Morello
Shinichi Yamashita
Acquisition Editor
Sarah Cullington
Lead Technical Editor
Pramila Balan
Technical Editors
Merin Jose
Kavita Raghavan
Manmeet Singh Vasir
Copy Editors
Brandt D'Mello
Insiya Morbiwala
Project Coordinator
Yashodhan Dere
Proofreader
Aaron Nash
Indexer
Hemangini Bari
Graphics
Manu Joseph
Valentina D'silva
Production Coordinator
Arvindkumar Gupta
Cover Work
Arvindkumar Gupta
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.
Little did I know, when I was first asked by Packt Publishing whether I would be interested in writing a book about HBase administration on September 2011, how much work and stress (but also a lot of fun) it was going to be.
Now that the book is finally complete, I would like to thank those people without whom it would have been impossible to get done.
First, I would like to thank the HBase developers for giving us such a great piece of software. Thanks to all of the people on the mailing list providing good answers to my many questions, and all the people working on tickets and documents.
I would also like to thank the team at Packt Publishing for contacting me to get started with the writing of this book, and providing support, guidance, and feedback.
Many thanks to Rakuten, my employer, who provided me with the environment to work on HBase and the chance to write this book.
Thank you to Michael Stack for helping me with a quick review of the book.
Thank you to the book's reviewersMichael Morello, Tatsuya Kawano, Kenichiro Hamano, Shinichi Yamashita, and Masatake Iwasaki.
To Yotaro Kagawa: Thank you for supporting me and my family from the very start and ever since.
To Xinping and Lingyin: Thank you for your support and all your patienceI love you!
Masatake Iwasaki is a Software Engineer at NTT DATA CORPORATION, providing technical consultation for open source softwares such as Hadoop, HBase, and PostgreSQL.
Tatsuya Kawano is an HBase contributor and evangelist in Japan. He has been helping the Japanese Hadoop and HBase community to grow since 2010.
He is currently working for Gemini Mobile Technologies as a Research & Development software engineer. He is also developing Cloudian, a fully S3 API-complaint cloud storage platform, and Hibari DB, an open source, distributed, key-value store.
He has co-authored a Japanese book named "Basic Knowledge of NOSQL" in 2012, which introduces 16 NoSQL products, such as HBase, Cassandra, Riak, MongoDB, and Neo4j to novice readers.
He has studied graphic design in New York, in the late 1990s. He loves playing with 3D computer graphics as much as he loves developing high-availability, scalable, storage systems.
Michael Morello holds a Masters degree in Distributed Computing and Artificial Intelligence. He is a Senior Java/JEE Developer with a strong Unix and Linux background. His areas of research are mostly related to large-scale systems and emerging technologies dedicated to solving scalability, performance, and high availability issues.
I would like to thank my wife and my little angel for their love and support.
Shinichi Yamashita is a Chief Engineer at the OSS Professional Service unit in NTT DATA Corporation, in Japan. He has more than 7 years of experience in software and middleware (Apache, Tomcat, PostgreSQL, Hadoop eco system) engineering.
Shinicha has written a few books on Hadoop in Japan.
I would like to thank my colleagues.
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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.
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