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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 7. Scaling Solr through Sharding, Fault Tolerance, and Integration

In the previous chapters, we went through various aspects of Apache Solr, including its capabilities, features, and different case studies. In Chapter 6, Distributed Search Using Apache Solr, we looked at SolrCloud, which provides excellent scaling capabilities with features such as distributed Solr instances with replication for high availability. The capabilities of Apache Solr have enabled organizations to indulge themselves in Apache Solr-based solution development. This demand in turn triggered the need to integrate Apache Solr-based enterprise search to work with mature high-performance open source software available today to achieve the best of both worlds.

There are many parallel tracks that are going on along with the Apache Solr open source community. These tracks focus on enhancing the integration of Solr with different tools to overall achieve objectives of high-scale Solr. We are going to look...

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