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Scaling Big Data with Hadoop and Solr, Second Edition

You're reading from Scaling Big Data with Hadoop and Solr, Second Edition Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr

Product type Paperback

Published in Apr 2015

Publisher

ISBN-13 9781783553396

Length 166 pages

Edition 1st Edition

Tools

Solr

Concepts

Big Data

Author (1):

Hrishikesh Vijay Karambelkar

View More author details

Table of Contents (8) Chapters

Preface

1. Processing Big Data Using Hadoop and MapReduce

2. Understanding Apache Solr FREE CHAPTER

3. Enabling Distributed Search using Apache Solr

4. Big Data Search Using Hadoop and Its Ecosystem

5. Scaling Search Performance

A. Use Cases for Big Data Search

Index

Setting up Apache Solr

We will be going through the Apache Solr architecture in the next section; for now, let's install Apache Solr on our machines. Apache Solr is a Java Servlet web application that runs on Apache Lucene, Tika, and other open source libraries. Apache Solr ships with a demo server on jetty, so one can simply run it through the command line. This helps users to run the Solr instance quickly. However, you can choose to customize it and deploy it in your own environment. Apache Solr does not ship with any installer; it has to be run as a part of J2EE Application.

Prerequisites for setting up Apache Solr

Apache Solr requires Java 1.6 or more to run, so it is important to make sure you have the correct version of Java by calling java –version, as shown in the following screenshot:

Prerequisites for setting up Apache Solr

Note

With the latest version of Apache Solr (4.0 or more), JDK 1.5 is not supported anymore. Apache Solr 4.0+ runs on JDK 1.6 + version. Instead of going for the pre-shipped JDK with your...

You have been reading a chapter from

Scaling Big Data with Hadoop and Solr, Second Edition

Published in: Apr 2015

Publisher:

ISBN-13: 9781783553396

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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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