Dear Wiki user, You have subscribed to a wiki page or wiki category on "Hadoop Wiki" for change notification.
The "Books" page has been changed by Jitesh Gawali: http://wiki.apache.org/hadoop/Books?action=diff&rev1=7&rev2=8 == Books in Print == Here are the books that are currently in print -in order of publishing-, along with the Hadoop version they were written against. One problem anyone writing a book will encounter is that Hadoop is a very fast-moving target, and that things can change fast. Usually this is for the better, when a book says "Hadoop can't" they really mean "the version of Hadoop we worked with couldn't", and that the situation may have improved since then. If you have any query about Hadoop, don't be afraid to ask on the relevant user mailing lists. + + === Hadoop Real World Solutions Cookbook === + + '''Name:''' [[http://www.packtpub.com/hadoop-real-world-solutions-cookbook/book|Hadoop Real World Solutions Cookbook]] + + '''Author:''' Jonathan Owens, Brian Femiano, Jon Lentz + + '''Hadoop Version:''' CDH3 + + '''Publisher:''' Packt Publishing + + '''Date of Publishing:''' February 7, 2013 + + '''Sample Chapter:''' [[http://www.packtpub.com/sites/default/files/9781849519120_Chapter_06.pdf|Chapter 6: Big Data Analysis]] + + Collection of real world code analytics and design patterns using various tools from the Hadoop community. Each recipe walks the reader through the implementation, or in some cases debugging and configuration tuning. The book covers various tools including !MapReduce, Hive, Pig, MRUnit, serialization using Avro/Thrift/ProtoBuffs, Giraph, Accumulo and several others. + === Hadoop MapReduce Cookbook === @@ -20, +37 @@ '''Date of Publishing:''' January 25, 2013 - '''Sample Chapter:''' [[https://www.packtpub.com/sites/default/files/9781849517287_Chapter_06.pdf|Chapter 6]] + '''Sample Chapter:''' [[https://www.packtpub.com/sites/default/files/9781849517287_Chapter_06.pdf|Chapter 6: Analytics]] Hadoop !MapReduce Cookbook is a one-stop guide to processing large and complex data sets using the Hadoop ecosystem. The book introduces you to simple examples and then dives deep to solve in-depth big data use cases.
