Birmingham, UK (PRWEB) August 24, 2012
Packt Publishing has announced the publication of HBase Administration Cookbook written by Yifeng Jiang. The book provides practical examples and simple step-by-step instructions to administrate HBase with ease.
HBase is an open source, non-relational, distributed database modeled after Google's BigTable and is written in Java. It is well suited for sparse data sets, which are common in many big data use cases, developed as part of Apache Software Foundation's Apache Hadoop project runs on top of HDFS (Hadoop Distributed Filesystem), providing BigTable-like capabilities for Hadoop. It provides a fault-tolerant way of storing large quantities of sparse data.
HBase Administration Cookbook is packed with several practical recipes to help readers understand how to move large amounts of data into HBase and manage it efficiently. 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 in achieving that.
The recipes in this practical cookbook start from setting up a fully distributed HBase cluster and moving data into it. It guides 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 to get the best out of HBase so the book will show how to set up Hadoop clusters, configure Hadoop to cooperate with HBase, and tune its performance.
The book with the help of simple examples and support code, guides readers to set up HBase on the cloud, get it ready for production, and run it smoothly with high performance and maximizing the ability of HBase with the Hadoop eco-system including HDFS, MapReduce, Zookeeper, and Hive
Hbase Administration Cookbook covers the following important aspects:
Set up a fully distributed, highly available HBase cluster and load data into it using the normal client API or 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 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
This book is for HBase administrators, developers, and will even help Hadoop administrators. To get complete details about the book, visit the publisher book-page [http://www.packtpub.com/hbase-administration-for-optimum-database-performance-cookbook/book