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 cluster's 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 Packt's 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.
Yifeng Jiang
Yifeng Jiang is a Hadoop and HBase Administrator and Developer at Rakuten—the 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
