Book Image

Mastering Apache Solr 7.x

By : Sandeep Nair, Chintan Mehta, Dharmesh Vasoya
Book Image

Mastering Apache Solr 7.x

By: Sandeep Nair, Chintan Mehta, Dharmesh Vasoya

Overview of this book

Apache Solr is the only standalone enterprise search server with a REST-like application interface. providing highly scalable, distributed search and index replication for many of the world's largest internet sites. To begin with, you would be introduced to how you perform full text search, multiple filter search, perform dynamic clustering and so on helping you to brush up the basics of Apache Solr. You will also explore the new features and advanced options released in Apache Solr 7.x which will get you numerous performance aspects and making data investigation simpler, easier and powerful. You will learn to build complex queries, extensive filters and how are they compiled in your system to bring relevance in your search tools. You will learn to carry out Solr scoring, elements affecting the document score and how you can optimize or tune the score for the application at hand. You will learn to extract features of documents, writing complex queries in re-ranking the documents. You will also learn advanced options helping you to know what content is indexed and how the extracted content is indexed. Throughout the book, you would go through complex problems with solutions along with varied approaches to tackle your business needs. By the end of this book, you will gain advanced proficiency to build out-of-box smart search solutions for your enterprise demands.
Table of Contents (14 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Understanding field types


As discussed earlier, we are able to tell Solr how it should interpret the incoming data in a field and how we can query a field using the information specified in field types.

Definitions and properties of field types

Before going to the definitions and properties, we will see what field analysis means.

What Solr should do or how it should interpret data whenever data is indexed is important. For example, a description of a book can contain lots of useless words: helping verbs such as is, was, and are; pronouns such as they, we, and so on; and other general words such as the, a, this, and so on. Querying these words will bring all the data. Similarly what should we do with words that have capital letters?

All of these problems can be catered using field analysis to ignore common words or casing while indexing or querying. We will dive deep into field analysis in the next chapter.

Now, coming back to field types, all analyses on a field are done by the field type, whether...