If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. Num Pages: 132 pages, black & white illustrations. BIC Classification: UNF. Category: (XV) Technical / Manuals. Dimension: 230 x 154 x 10. Weight in Grams: 212. . 2015. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.

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Bibliographic Details

Title: Field Guide to Hadoop
Publisher: O Reilly Media
Publication Date: 2015
Language: English
ISBN 10: 1491947934
ISBN 13: 9781491947937
Binding: Soft cover
Condition: New

About this title

Synopsis

If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You’ll quickly understand how Hadoop’s projects, subprojects, and related technologies work together.

Each chapter introduces a different topic—such as core technologies or data transfer—and explains why certain components may or may not be useful for particular needs. When it comes to data, Hadoop is a whole new ballgame, but with this handy reference, you’ll have a good grasp of the playing field.

Topics include:

Core technologies—Hadoop Distributed File System (HDFS), MapReduce, YARN, and Spark
Database and data management—Cassandra, HBase, MongoDB, and Hive
Serialization—Avro, JSON, and Parquet
Management and monitoring—Puppet, Chef, Zookeeper, and Oozie
Analytic helpers—Pig, Mahout, and MLLib
Data transfer—Scoop, Flume, distcp, and Storm
Security, access control, auditing—Sentry, Kerberos, and Knox
Cloud computing and virtualization—Serengeti, Docker, and Whirr

About the Author

Kevin Sitto is a Field Solutions Engineer with Pivotal Software, providing consulting services to help folks understand and address their big data needs.

He lives in Maryland with his wife and two kids and enjoys making homebrew beer when he's not writing books about big data.

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