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Learning Hadoop 2

You're reading from   Learning Hadoop 2 Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Length 382 pages
Edition 1st Edition
Tools
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Author (1):
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GABRIELE MODENA GABRIELE MODENA
Author Profile Icon GABRIELE MODENA
GABRIELE MODENA
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Table of Contents (18) Chapters Close

Learning Hadoop 2
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Introduction FREE CHAPTER 2. Storage 3. Processing – MapReduce and Beyond 4. Real-time Computation with Samza 5. Iterative Computation with Spark 6. Data Analysis with Apache Pig 7. Hadoop and SQL 8. Data Lifecycle Management 9. Making Development Easier 10. Running a Hadoop Cluster 11. Where to Go Next Index

Other interesting projects


Whether you use a bundled distribution or stick with the base Apache Hadoop download, you will encounter many references to other related projects. We've covered several of these such as Hive, Samza, and Crunch in this book; we'll now highlight some of the others.

Note that this coverage seeks to point out the highlights (from the authors' perspective) as well as give a taste of the breadth of types of projects available. As mentioned earlier, keep looking out, as there will be new ones launching all the time.

HBase

Perhaps the most popular Apache Hadoop-related project that we didn't cover in this book is HBase (http://hbase.apache.org). Based on the BigTable model of data storage publicized by Google in an academic paper (sound familiar?), HBase is a nonrelational data store sitting atop HDFS.

While both MapReduce and Hive focus on batch-like data access patterns, HBase instead seeks to provide very low-latency access to data. Consequently HBase can, unlike the aforementioned...

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