Big Data for Chimps

A Guide to Massive-Scale Data Processing in Practice

Nonfiction, Computers, Database Management, General Computing
Cover of the book Big Data for Chimps by Philip (flip) Kromer, Russell Jurney, O'Reilly Media
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Philip (flip) Kromer, Russell Jurney ISBN: 9781491923900
Publisher: O'Reilly Media Publication: September 28, 2015
Imprint: O'Reilly Media Language: English
Author: Philip (flip) Kromer, Russell Jurney
ISBN: 9781491923900
Publisher: O'Reilly Media
Publication: September 28, 2015
Imprint: O'Reilly Media
Language: English

Finding patterns in massive event streams can be difficult, but learning how to find them doesn’t have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You’ll gain a practical, actionable view of big data by working with real data and real problems.

Perfect for beginners, this book’s approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you’ll also learn how to use Apache Pig to process data.

  • Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster
  • Dive into map/reduce mechanics and build your first map/reduce job in Python
  • Understand how to run chains of map/reduce jobs in the form of Pig scripts
  • Use a real-world dataset—baseball performance statistics—throughout the book
  • Work with examples of several analytic patterns, and learn when and where you might use them
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Finding patterns in massive event streams can be difficult, but learning how to find them doesn’t have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You’ll gain a practical, actionable view of big data by working with real data and real problems.

Perfect for beginners, this book’s approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you’ll also learn how to use Apache Pig to process data.

More books from O'Reilly Media

Cover of the book Designing and Developing for Google Glass by Philip (flip) Kromer, Russell Jurney
Cover of the book HTML and XHTML Pocket Reference by Philip (flip) Kromer, Russell Jurney
Cover of the book Attract Visitors to Your Site: The Mini Missing Manual by Philip (flip) Kromer, Russell Jurney
Cover of the book Perl Cookbook by Philip (flip) Kromer, Russell Jurney
Cover of the book Hands-On Programming with R by Philip (flip) Kromer, Russell Jurney
Cover of the book Learning DCOM by Philip (flip) Kromer, Russell Jurney
Cover of the book Designing for Emerging Technologies by Philip (flip) Kromer, Russell Jurney
Cover of the book Mapping Experiences by Philip (flip) Kromer, Russell Jurney
Cover of the book JavaServer Faces by Philip (flip) Kromer, Russell Jurney
Cover of the book Bandit Algorithms for Website Optimization by Philip (flip) Kromer, Russell Jurney
Cover of the book Agile Data Science 2.0 by Philip (flip) Kromer, Russell Jurney
Cover of the book What Is Node? by Philip (flip) Kromer, Russell Jurney
Cover of the book Raspberry Pi für Einsteiger by Philip (flip) Kromer, Russell Jurney
Cover of the book Mobile Design Pattern Gallery by Philip (flip) Kromer, Russell Jurney
Cover of the book QuickBooks 2006: The Missing Manual by Philip (flip) Kromer, Russell Jurney
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy