Hadoop in 24 Hours
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.


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.


Related Reviews

Data Analytics With Hadoop

Field Guide to Hadoop

Hadoop Application Architectures

Hadoop Essentials

Hadoop for Finance Essentials

Hadoop: The Definitive Guide (4th ed)

Hadoop Interview Guide

Professional Hadoop


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WPF 4.5 Unleashed

Author: Adam Nathan
Publisher: Sams, 2013
Pages: 864
ISBN: 9780672336973
Print: 0672336979
Kindle: B00DW7PLIE
Audience: Anyone wanting to understand WPF
Rating: 5
Reviewer: Mike James

If you work with WPF, which now seems to have an assured future,this is a book you need to know about.

 [ ... ]

Common Information Models for an Open, Analytical and Agile World

Authors: Mandy Chessell, Gandhi Sivakumar, Dan Wolfson, Kerard Hogg and Ray Harishankar
Publisher: IBM Press
Pages: 240
ISBN: 978-0133366150
Print: 0133366154
Kindle: B00VVG07IM
Aimed at: Enterprise architects
Rating: 4
Reviewer: Kay Ewbank

Can Common Information Mod [ ... ]

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