Hadoop in 24 Hours

Author: Jeffrey Aven
Publisher: Sams
Date: April 2017
Pages: 500
ISBN: 978-0672338526
Print: 0672338521
Kindle: B06XYM3XH4
Audience: Big data developers
Rating: 4.5
Reviewer: Kay Ewbank

Hadoop is a complex ecosystem, but this book does a good job of teaching you the way around it. 

The book opens with chapters introducing Hadoop, the Hadoop Cluster Architecture, and deploying Hadoop. The Hadoop Distributed File System (HDFS) is introduced next, followed by techniques for getting data into Hadoop using Flume, Sqoop, and the HDFS RESTful interface. A chapter on data processing in Hadoop introduces MapReduce very nicely.

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Part Two of the book assumes you know enough to actually use Hadoop, and opens with a chapter on programming MapReduce applications using the Java MapReduce API and the MapReduce Streaming API.

Next the author introduces data analysis in HDFS using Apache Pig, from Pig Latin basics through to Pig's built-in functions. A second chapter on Pig looks at more advanced topics such as grouping data, multiple dataset programming, user-defined functions, and the use of macros and variables to automate Pig.

 

 

Two chapters on Hive give a good grounding in analyzing data using Apache Hive, going as far as complex datatypes and optimizing and managing queries in Hive. A chapter on SQL oh Hadoop introduces Impala, Tex, HAWQ and Drill, but it is only an introduction.

The final chapters in this part of the book look at Spark, the Hadoop User Environment (HUE), and NoSQL in the form of HBase and Cassandra.

Hadoop management occupies the rest of the book, starting with YARN, and in particular administering it and scheduling applications using it. The more general Hadoop ecosystem gets a chapter next, with introductions to Oozie and to machine learning and visualization in Hadoop.

Cluster management can be complex in Hadoop, and there's a good chapter on the various cluster management utilities, and a further one on cluster configuration. A chapter on advanced HDFS covers topics such as rack awareness, federation and HDFS caching.

The final chapters cover securing Hadoop, monitoring and troubleshooting, and a set of case studies on integrating Hadoop.

Overall, this is a very good book. There's enough to introduce all the elements of Hadoop and its ecosystem, and while you'd still need to read books specific to some of the sub topics, you get a good grounding in what tools to use and how to use them.

 

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Python Programming and Visualization for Scientists 2nd Ed

Author: Alex DeCaria and Grant Petty
Publisher: Sundog Publishing
Pages: 372
ISBN: 978-0972903356
Print: 0972903356
Audience: Scientists wanting to use Python
Rating: 2
Reviewer: Mike James
Visualization - a difficult topic and difficult to see how to explain the ideas in a book.



Visual Complex Analysis

Author:  Tristan Needham
Publisher: Clarendon Press
Pages: 616
ISBN: 978-0198534464
Print: 0198534469
Kindle: B0BNKJTJK1
Audience: The mathematically able and enthusiastic
Rating: 5
Reviewer: Mike James
What's complex about complex analysis?


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Last Updated ( Saturday, 27 May 2017 )