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  • Book Overview & Buying Scaling Big Data with Hadoop and Solr, Second Edition
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Scaling Big Data with Hadoop and Solr, Second Edition

Scaling Big Data with Hadoop and Solr, Second Edition

By : Vijay Karambelkar
3 (4)
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Scaling Big Data with Hadoop and Solr, Second Edition

Scaling Big Data with Hadoop and Solr, Second Edition

3 (4)
By: Vijay Karambelkar
Buy this Book

Overview of this book

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 (8 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Processing Big Data Using Hadoop and MapReduce
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1. Processing Big Data Using Hadoop and MapReduce
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Apache Hadoop's ecosystem
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Configuring Apache Hadoop
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Running Hadoop
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Setting up a Hadoop cluster
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Common problems and their solutions
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Summary
2
2. Understanding Apache Solr
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2. Understanding Apache Solr
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Setting up Apache Solr
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The Apache Solr architecture
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Configuring Solr
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Loading data in Apache Solr
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Querying for information in Solr
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Summary
3
3. Enabling Distributed Search using Apache Solr
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3. Enabling Distributed Search using Apache Solr
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Understanding a distributed search
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Working with SolrCloud
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Sharding algorithm and fault tolerance
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Apache Solr and Big Data – integration with MongoDB
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Summary
4
4. Big Data Search Using Hadoop and Its Ecosystem
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4. Big Data Search Using Hadoop and Its Ecosystem
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Understanding NoSQL
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Working with the Solr HDFS connector
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Big data search using Katta
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Using Solr 1045 Patch – map-side indexing
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Using Solr 1301 Patch – reduce-side indexing
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Distributed search using Apache Blur
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Apache Solr and Cassandra
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Scaling Solr through Storm
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Advanced analytics with Solr
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Summary
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5. Scaling Search Performance
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5. Scaling Search Performance
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Understanding the limits
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Optimizing search schema
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Index optimization
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Optimizing search runtime
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Monitoring Solr instance
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Summary
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A. Use Cases for Big Data Search
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A. Use Cases for Big Data Search
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E-Commerce websites
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Log management for banking
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Index
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Index

Chapter 4. Big Data Search Using Hadoop and Its Ecosystem

Sometime back, Gartner (http://www.gartner.com/newsroom/id/2304615) published an executive program survey report, which revealed that big data and analytics are among the top 10 business priorities for CIOs; similarly, analytics and BI are also at the top of CIO's Technical Priorities. Big data presents three major concerns for any organization: namely the storage of big data, data access or querying, and data analytics. Apache Hadoop provides an excellent implementation framework for the organizations looking to solve these problems. Similarly, there is other software that provides efficient storage and access to big data, such as Apache Cassandra and R Statistical. In this chapter, we will explore the possibilities of Apache Solr in working with big data.

We have already discussed a scaling search with SolrCloud in the previous chapters. In this chapter, we will be focusing on the following topics:

  • Understanding NoSQL...
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Tech Concepts
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Programming languages
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