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Scaling Apache Solr

You're reading from   Scaling Apache Solr Optimize your searches using high-performance enterprise search repositories with Apache Solr

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Product type Paperback
Published in Jul 2014
Publisher
ISBN-13 9781783981748
Length 298 pages
Edition 1st Edition
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Author (1):
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Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Table of Contents (13) Chapters Close

Preface 1. Understanding Apache Solr FREE CHAPTER 2. Getting Started with Apache Solr 3. Analyzing Data with Apache Solr 4. Designing Enterprise Search 5. Integrating Apache Solr 6. Distributed Search Using Apache Solr 7. Scaling Solr through Sharding, Fault Tolerance, and Integration 8. Scaling Solr through High Performance 9. Solr and Cloud Computing 10. Scaling Solr Capabilities with Big Data A. Sample Configuration for Apache Solr Index

Chapter 6. Distributed Search Using Apache Solr

Traditionally, organizations have tried to optimize their business cost on information processing by limiting the information to smaller subsets based on business priority. This was mainly due to the exorbitant cost of storing and processing enterprise data in data stores such as relational databases. Today's technology advancements have reduced the overall cost of data processing through the use of low-cost hardware and open source software. It has also enabled organizations to go beyond smaller data subsets, demanding more data processing capabilities from these systems. Enterprise searches were no exception.

Since enterprise search applications work across multiple applications with different datasets across organizations, it requires lot of data storage and exceptional computation capabilities from the underlying hardware systems. Many organizations optimize cost by preferring to use low-cost distributed systems instead of...

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