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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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Toc

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

schema.xml

Broadly, schema.xml contains the following information:

  • Different types of field names of schema, and data types (<fields>…<field>)
  • Definition of user/seeded defined data types (<types>…<fieldTypes>)
  • Dynamic fields (<fields>….<dynamicField>)
  • Information about unique key to define each document uniquely (<uniqueKey>)
  • Information regarding query parser for Solr (<solrQueryParser>)
  • Default search field to be used when the user does not pass the field name (<defaultSearchField>)
  • Information about copying the field from one field to another (<copyField>)

In the Configuring the Apache Solr for enterprise section of Chapter 2, Getting Started with Apache Solr, we have already explained the important attributes of schema.xml. The following is a sample of the schema.xml file; the fields will look like the ones shown in the following screenshot:

schema.xml

You can remove all copy fields, if not needed. The unique key is used...

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