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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

Optimizing Solr schema and indexing


Apache Solr schema can also be optimized for reducing the overall footprint of your index and to speed up the search. Let's take a look at some of the possible optimizations.

Stored fields

The schema.xml file also provides a configuration to define whether a field needs to be stored as an optional attribute (stored=true/false). Typically, the fields are stored so that their values can be displayed as search results in the search results page. However, if the size of the fields is large, it unnecessarily increases the size of the index, eating up Solr's memory. For large fields, it is better to store their identifiers and let the search client be responsible for rendering the result; fire a query to another system (database or filesystem) to gather the required field information as a part of the result. This will not only reduce the load on Solr but will also ease the management of the field in another store (like relational databases) which are optimized...

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