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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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 Karanth Karanth
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Karanth
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Table of Contents (21) Chapters Close

Mastering Hadoop
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
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 Hadoop for Microsoft Windows Index

Summary


In this chapter, we went through the advanced features of Pig. We looked into the optimizations that Pig has to offer. The following are a few key takeaways from this chapter:

  • As a rule, try to use Pig in as many situations as you can. Pig's abstractions, development aids, and flexibility can save you both time and money. Stretch Pig's capabilities before reverting to MapReduce jobs.

  • The logical plan optimizations might change the order of statement execution. Use EXPLAIN and ILLUSTRATE extensively to study Pig scripts.

  • Help Pig to execute your script faster by following some of the guidelines mentioned in this chapter. Try to make your UDFs implement the Algebraic or Accumulator interface, ideally both.

  • Understand the data you are trying to process. Specialized support is available for some kinds of data quirks, such as Skewed joins for joins on skewed data.

In the next chapter, we will look at advanced features of a higher-level SQL abstraction on Hadoop MapReduce called Hive.

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