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Scaling Big Data with Hadoop and Solr, Second Edition Cover

Scaling Big Data with Hadoop and Solr, Second Edition

Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr

Paid access
|Sep 2025
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Key Features

    Book Description

    This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.

    What you will learn

    • Understand Apache Hadoop, its ecosystem, and Apache Solr
    • Explore industrybased architectures by designing a big data enterprise search with their applicability and benefits
    • Integrate Apache Solr with big data technologies such as Cassandra to enable better scalability and high availability for big data
    • Optimize the performance of your big data search platform with scaling data
    • Write MapReduce tasks to index your data
    • Configure your Hadoop instance to handle realworld big data problems
    • Work with Hadoop and Solr using realworld examples to benefit from their practical usage
    • Use Apache Solr as a NoSQL database

    Who this book is for

    This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.

    Table of Contents

    1. Processing big data using Hadoop and MapReduce
    2. Understanding Solr
    3. Enabling Distributed Search using Solr
    4. Using Hadoop to build your big data indexing
    5. Improving Performance of Search with scaling big data
    6. Appendix A: Use cases and Case Studies
    PDF ISBN: 978-1-78355-340-2
    Publisher: Packt Publishing Limited
    Copyright owner: © 2015 Packt Publishing Limited
    Publication date: 2025
    Language: English
    Pages: 166