Book Image

Apache Solr 4 Cookbook

By : Rafał Kuć
Book Image

Apache Solr 4 Cookbook

By: Rafał Kuć

Overview of this book

<p>Apache Solr is a blazing fast, scalable, open source Enterprise search server built upon Apache Lucene. Solr is wildly popular because it supports complex search criteria, faceting, result highlighting, query-completion, query spell-checking, and relevancy tuning, amongst other numerous features.<br /><br />"Apache Solr 4 Cookbook" will show you how to get the most out of your search engine. Full of practical recipes and examples, this book will show you how to set up Apache Solr, tune and benchmark performance as well as index and analyze your data to provide better, more precise, and useful search data.<br /><br />"Apache Solr 4 Cookbook" will make your search better, more accurate and faster with practical recipes on essential topics such as SolrCloud, querying data, search faceting, text and data analysis, and cache configuration.<br /><br />With numerous practical chapters centered on important Solr techniques and methods, Apache Solr 4 Cookbook is an essential resource for developers who wish to take their knowledge and skills further. Thoroughly updated and improved, this Cookbook also covers the changes in Apache Solr 4 including the awesome capabilities of SolrCloud.</p>
Table of Contents (18 chapters)
Apache Solr 4 Cookbook
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
Index

Getting the number of documents matching the query and subquery


Imagine a situation where you have an application that has a search feature for cars. One of the requirements is not only to show search results, but also to show the number of cars with the price period chosen by the user. There is also another thing—those queries must be fast because of the number of queries that will be run. Can Solr handle that? The answer is yes. This recipe will show you how to do it.

How to do it...

For getting the number of documents matching the query and subquery, follow these steps:

  1. Let's start with creating an index with the following structure (just add this to your schema.xml file in the field definition section; we will use the price field to do the faceting):

    <field name="id" type="string" indexed="true" stored="true" required="true" />
    <field name="name" type="text" indexed="true" stored="true" />
    <field name="price" type="float" indexed="true" stored="true" />
  2. Now let's index...