Book description
This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop. With Pig, you can batch-process data without having to create a full-fledged application—making it easy for you to experiment with new datasets.
Programming Pig introduces new users to Pig, and provides experienced users with comprehensive coverage on key features such as the Pig Latin scripting language, the Grunt shell, and User Defined Functions (UDFs) for extending Pig. If you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig.
- Delve into Pig’s data model, including scalar and complex data types
- Write Pig Latin scripts to sort, group, join, project, and filter your data
- Use Grunt to work with the Hadoop Distributed File System (HDFS)
- Build complex data processing pipelines with Pig’s macros and modularity features
- Embed Pig Latin in Python for iterative processing and other advanced tasks
- Create your own load and store functions to handle data formats and storage mechanisms
- Get performance tips for running scripts on Hadoop clusters in less time
Publisher resources
Table of contents
- Programming Pig
- Dedication
- Preface
- 1. Introduction
- 2. Installing and Running Pig
- 3. Grunt
- 4. Pig’s Data Model
- 5. Introduction to Pig Latin
- 6. Advanced Pig Latin
- 7. Developing and Testing Pig Latin Scripts
- 8. Making Pig Fly
- 9. Embedding Pig Latin in Python
- 10. Writing Evaluation and Filter Functions
- 11. Writing Load and Store Functions
- 12. Pig and Other Members of the Hadoop Community
- A. Built-in User Defined Functions and Piggybank
- B. Overview of Hadoop
- Index
- About the Author
- Colophon
- Copyright
Product information
- Title: Programming Pig
- Author(s):
- Release date: October 2011
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781449302641
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