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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
Tools
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Toc

Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

Chapter 3. Advanced Pig

Running Java MapReduce jobs on Hadoop provides the most flexibility with the least abstraction. However, abstractions are necessary to infer patterns, accomplish common data manipulation tasks, reduce complexity, and flatten the learning curve. Pig is a platform that provides a framework and high-level abstractions to build MapReduce programs for Hadoop. It has a scripting language called Pig Latin. Pig Latin can be compared to SQL in terms of operator capabilities.

Developed at Yahoo! around the year 2006, Pig was used as a framework to specify ad hoc MapReduce workflows. In the following year, it was moved to Apache Software Foundation. The latest release of Pig is 0.12.1.

Tip

The official release of Pig is currently incompatible with Hadoop 2.2.0. It expects libraries from Hadoop 1.2.1. Running any Pig script fails, with the following exception:

Unexpected System Error Occured: java.lang.IncompatibleClassChangeError: Found interface org.apache.hadoop.mapreduce...
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