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Learning Hadoop 2

You're reading from  Learning Hadoop 2

Product type Book
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Pages 382 pages
Edition 1st Edition
Languages

Table of Contents (18) Chapters

Learning Hadoop 2
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Introduction 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

Java API to MapReduce


The Java API to MapReduce is exposed by the org.apache.hadoop.mapreduce package. Writing a MapReduce program, at its core, is a matter of subclassing Hadoop-provided Mapper and Reducer base classes, and overriding the map() and reduce() methods with our own implementation.

The Mapper class

For our own Mapper implementations, we will subclass the Mapper base class and override the map() method, as follows:

   class Mapper<K1, V1, K2, V2>
   {
         void map(K1 key, V1 value Mapper.Context context)
               throws IOException, InterruptedException
         ...
   }

The class is defined in terms of the key/value input and output types, and then the map method takes an input key/value pair as its parameter. The other parameter is an instance of the Context class that provides various mechanisms to communicate with the Hadoop framework, one of which is to output the results of a map or reduce method.

Notice that the map method only refers to a single instance of...

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