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You're reading from  Scaling Big Data with Hadoop and Solr, Second Edition

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Published inApr 2015
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ISBN-139781783553396
Edition1st Edition
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Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Hrishikesh Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
Read more about Hrishikesh Vijay Karambelkar

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Optimizing search schema


When Solr is used in the context of a specific requirement (for example, log search for an enterprise application) it holds a specific schema that can be defined in schema.xml and copied over to nodes. The schema is based on the schema attributes indexes and thus plays a vital role in the performance of your Solr instance.

Specifying default search field

In the schema.xml file of the Solr configuration, the system allows you to specify the <defaultSearchField> parameter. This is the parameter that controls when you search without an explicit field name in your query, and which field to pick up for searching. This is an optional parameter; if this is not specified, for all the queries that are not providing the field name, the search will run them on all the available fields in the schema. This will not only consume more CPU time but on the whole, slow down the search performance.

Configuring search schema fields

In custom schema, having a larger number of fields...

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Scaling Big Data with Hadoop and Solr, Second Edition
Published in: Apr 2015Publisher: ISBN-13: 9781783553396

Author (1)

author image
Hrishikesh Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
Read more about Hrishikesh Vijay Karambelkar