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Apache Solr for Indexing Data

Apache Solr for Indexing Data

By : Handiekar, Johri
1 (1)
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Apache Solr for Indexing Data

Apache Solr for Indexing Data

1 (1)
By: Handiekar, Johri

Overview of this book

Apache Solr is a widely used, open source enterprise search server that delivers powerful indexing and searching features. These features help fetch relevant information from various sources and documentation. Solr also combines with other open source tools such as Apache Tika and Apache Nutch to provide more powerful features. This fast-paced guide starts by helping you set up Solr and get acquainted with its basic building blocks, to give you a better understanding of Solr indexing. You’ll quickly move on to indexing text and boosting the indexing time. Next, you’ll focus on basic indexing techniques, various index handlers designed to modify documents, and indexing a structured data source through Data Import Handler. Moving on, you will learn techniques to perform real-time indexing and atomic updates, as well as more advanced indexing techniques such as de-duplication. Later on, we’ll help you set up a cluster of Solr servers that combine fault tolerance and high availability. You will also gain insights into working scenarios of different aspects of Solr and how to use Solr with e-commerce data. By the end of the book, you will be competent and confident working with indexing and will have a good knowledge base to efficiently program elements.
Table of Contents (13 chapters)
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12
Index

What this book covers

Chapter 1, Getting Started, covers the basic setup and installation needed to run Solr. It also covers the directory structure and the main configuration files used by Solr.

Chapter 2, Understanding Analyzers, Tokenizers, and Filters, shows you the basic building blocks of Solr, such as analyzers, tokenizers, and filters. These help in the indexing of data. This chapter also covers the most commonly used components in detail and how they work together.

Chapter 3, Indexing Data, helps you get a better understanding of how indexing works in Solr by building a real-life example that covers various aspects, for example, the copy field, facet, indexing time boosting, and so on.

Chapter 4, Indexing Data – The Basic Techniques and Using Index Handlers, covers various techniques by which we can index data in Solr. This chapter explains the various request handlers that are used by Solr to index CSV, JSON, and XML data type documents.

Chapter 5, Indexing Data Using Structured Datasource Using DIH, covers how we can use indexed data from a database by using the data import handler available in Solr.

Chapter 6, Indexing Data Using Apache Tika, illustrates the integration of Apache Tika with Solr for the indexing of documents.

Chapter 7, Apache Nutch, covers the integration of Apache Nutch with Solr for indexing crawl data from the Internet.

Chapter 8, Commits, Real-Time Index Optimizations, and Atomic Updates, shows us how we can use the real-time indexing features available in Solr and utilize these features to provide a real-time search experience.

Chapter 9, Advanced Topics – Multilanguage, Deduplication, and Others, covers advanced topics such as indexing multilanguage documents and removing duplicate documents from Solr.

Chapter 10, Distributed Indexing, tells us how we can utilize SolrCloud to provide a high-availability and fault-tolerant cluster.

Chapter 11, Case Study of Using Solr in E-Commerce, covers a case study by going through easy-to-use, simple examples that can be used in an e-commerce website.

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