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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

Data integrating pattern for search

Enterprise search solutions work on multiple data sources. Integration of these data sources with a search engine is an important aspect of search solution design. The data sources can vary from applications to databases and web crawlers. Like ETL tools of data warehouse, the data loading in search solutions goes through similar cycles. The important part here is how and which data should be loaded in the search engine. In this section, we will look at different approaches while working with the integration of data sources with a search engine. Many times, during the design of a search engine, architects end up using one or more of these data integration patterns for the design. Most application integrations fall under one of the following patterns. Each of them offer unique benefits and drawbacks; the architects have to choose the best-suited pattern based on the landscape.

Data import by enterprise search

This type of data integration is used for most...

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