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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 5. Integrating Apache Solr

The larger your IT landscapes, the more difficult it can be for its users to find what they need, even with the best navigation mechanisms. A search engine should be capable of integrating with multiple systems of this kind. In the last chapter, we have seen the different data integration patterns that are possible with Apache Solr. Apache Solr is capable of reading data from different data sources. The next level of enterprise search demands deeper integration with Apache Solr. For example, a search user interface in the application uses Apache Solr or the applications run Apache Solr in an embedded mode. These are just different possibilities to explore while moving into a deeper integration. Many organizations would like to retain the user interface and usability of their existing application, while moving the underlying processing layer on Apache Solr.

Apache Solr has an active development community, which means heavy usage of Solr based across...

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