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Programming Pig

Dataflow Scripting with Hadoop

By: Alan Gates, Daniel Dai

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eText | 9 November 2016 | Edition Number 2

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For many organizations, Hadoop is the first step for dealing with massive amounts of data. The next step? Processing and analyzing datasets with the Apache Pig scripting platform. With Pig, you can batch-process data without having to create a full-fledged application, making it easy to experiment with new datasets.

Updated with use cases and programming examples, this second edition is the ideal learning tool for new and experienced users alike. You'll find comprehensive coverage on key features such as the Pig Latin scripting language and the Grunt shell. When 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
Use Pig with Apache Tez to build high-performance batch and interactive data processing applications
Create your own load and store functions to handle data formats and storage mechanisms