Book Image

Apache Solr for Indexing Data

Book Image

Apache Solr for Indexing Data

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 (18 chapters)
Apache Solr for Indexing Data
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, we saw how we can use the data import handler provided by Solr to import data from various datasources. There are a lot of things that we did not cover in this chapter, and they are beyond the scope of this book, such as entity processors, transformers, and many more. You can read more about this advanced feature on the Solr Data Import Handler wiki (https://wiki.apache.org/solr/DataImportHandler).

In the next chapter, we'll see how we can extract data from various file formats, such as .doc, .ppt, .xls, and many more, and index it in Solr using Apache Tika.