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Apache Solr for Indexing Data

You're reading from   Apache Solr for Indexing Data Enhance your Solr indexing experience with advanced techniques and the built-in functionalities available in Apache Solr

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Product type Paperback
Published in Dec 2015
Publisher
ISBN-13 9781783553235
Length 160 pages
Edition 1st Edition
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Author (1):
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Anshul Johri Anshul Johri
Author Profile Icon Anshul Johri
Anshul Johri
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Table of Contents (13) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Understanding Analyzers, Tokenizers, and Filters 3. Indexing Data 4. Indexing Data – The Basic Technique and Using Index Handlers 5. Indexing Data with the Help of Structured Datasources – Using DIH 6. Indexing Data Using Apache Tika 7. Apache Nutch 8. Commits, Real-Time Index Optimizations, and Atomic Updates 9. Advanced Topics – Multilanguage, Deduplication, and Others 10. Distributed Indexing 11. Case Study of Using Solr in E-Commerce Index

Chapter 3. Indexing Data

In the previous chapter, we saw the various analyzers, tokenizers, and filters provided by Solr that help us select the most important data from a given document. In this chapter, we'll see how Solr provides us a way to index this data so that we can run queries on top of it. We'll cover the following topics in this chapter:

  • Defining field types in Solr
  • Creating a custom musicCatalogue example
  • Facet searching

The Solr indexing process can mainly be broken down into two major parts:

  • Converting the document from its native format to XML or JSON, both of which are supported by Solr
  • Adding documents into Solr datastore using API or HTTP POST

To better understand the preceding two parts, we'll create an example of a music catalogue that contains metadata related to songs. The music catalogue will contain metadata related to a song that can later be used to retrieve important information regarding the song.

We'll also see how Solr provides various...

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