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Learning Hadoop 2

You're reading from   Learning Hadoop 2 Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Length 382 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. Storage 3. Processing – MapReduce and Beyond 4. Real-time Computation with Samza 5. Iterative Computation with Spark 6. Data Analysis with Apache Pig 7. Hadoop and SQL 8. Data Lifecycle Management 9. Making Development Easier 10. Running a Hadoop Cluster 11. Where to Go Next Index

Running Pig


Pig is a tool that translates statements written in Pig Latin and executes them either on a single machine in standalone mode or on a full Hadoop cluster when in distributed mode. Even in the latter, Pig's role is to translate Pig Latin statements into MapReduce jobs and therefore it doesn't require the installation of additional services or daemons. It is used as a command-line tool with its associated libraries.

Cloudera CDH ships with Apache Pig version 0.12. Alternatively, the Pig source code and binary distributions can be obtained at https://pig.apache.org/releases.html.

As can be expected, the MapReduce mode requires access to a Hadoop cluster and HDFS installation. MapReduce mode is the default mode executed when running the Pig command at the command-line prompt. Scripts can be executed with the following command:

$ pig -f <script>

Parameters can be passed via the command line using -param <param>=<val>, as follows:

$ pig –param input=tweets.txt

Parameters...

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