Hadoop in Action

KEY SELLING POINTS

Hadoop from the ground up

Covers the newer and bigger Hadoop landscape

Demystifies many concepts and components surrounding Hadoop



AUDIENCE

This book requires basic Java skills. Knowing basic statistical concepts can help with the more advanced examples.

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DESCRIPTION

The massive datasets required for most modern businesses are too large to safely store and efficiently process on a single server. Hadoop is an open source data processing framework that provides a distributed file system that can manage data stored across clusters of servers and implements the MapReduce data processing model so that users can effectively query and utilize big data. The new Hadoop 2.0 is a stable, enterprise-ready platform supported by a rich ecosystem of tools and related technologies such as Pig, Hive, YARN, Spark, Tez, and many more.





Hadoop in Action, Second Edition, provides a comprehensive introduction to Hadoop and shows how to write programs in the MapReduce style. It starts with a few easy examples and then moves quickly to show how Hadoop can be used in more complex data analysis tasks. It covers how YARN, new in Hadoop 2, simplifies and supercharges resource management to make streaming and real-time applications more feasible. Included are best practices and design patterns of MapReduce programming. The book expands on the first edition by enhancing coverage of important Hadoop 2 concepts and systems, and by providing new chapters on data management and data science that reinforce a practical understanding of Hadoop.





KEY SELLING POINTS

Hadoop from the ground up

Covers the newer and bigger Hadoop landscape

Demystifies many concepts and components surrounding Hadoop



AUDIENCE

This book requires basic Java skills. Knowing basic statistical concepts can help with the more advanced examples.





ABOUT THE TECHNOLOGY

Hadoop is an open source framework for writing and running distributed applications that process large amounts of data. Distributed computing is a wide and varied field, but the key distinctions of Hadoop are that it is accessible, robust, scalable, and simple, once users have learned a few basic concepts.