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Apache Hadoop 3 Quick Start Guide

You're reading from Apache Hadoop 3 Quick Start Guide Learn about big data processing and analytics

Product type Paperback

Published in Oct 2018

Publisher Packt

ISBN-13 9781788999830

Length 220 pages

Edition 1st Edition

Languages

Java

Tools

Hadoop

Concepts

Big Data

Author (1):

Hrishikesh Vijay Karambelkar

View More author details

Table of Contents (10) Chapters

Preface

1. Hadoop 3.0 - Background and Introduction

2. Planning and Setting Up Hadoop Clusters FREE CHAPTER

3. Deep Dive into the Hadoop Distributed File System

4. Developing MapReduce Applications

5. Building Rich YARN Applications

6. Monitoring and Administration of a Hadoop Cluster

7. Demystifying Hadoop Ecosystem Components

8. Advanced Topics in Apache Hadoop

9. Other Books You May Enjoy

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Understanding Hadoop APIs and packages

Now let's go through some of the key APIs that you will be using while you program in MapReduce. First, let's understand the important packages that are part of Apache Hadoop MapReduce APIs and their capabilities:

...

Java API Packages	Description
`org.apache.Hadoop.mapred`	Primarily provides interfaces for MapReduce, input/output formats, and job-related classes. This is an older API.
`org.apache.Hadoop.mapred.lib`	Contains libraries for Mapper, Reducer, partitioners, and so on. To be avoided—use `mapreduce.lib`.
`org.apache.Hadoop.mapred.pipes`	Job submitter-related classes.
`org.apache.Hadoop.mapred.tools`	Command-line tools associated with MapReduce.
`org.apache.Hadoop.mapred.uploader`	The `org.apache.Hadoop.mapred.uploader` package contains classes related to the MapReduce framework upload tool.

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Authors (1)

Vijay Karambelkar

Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.

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