What this book covers
Chapter 1, Google-like Web Search, takes you along the course of building a simple scalable search server. You will learn how to create an index and add some documents to it and you will try out some essential features, such as highlighting and pagination of results. Also, it will cover topics such as setting an analyzer for our text; applying filters to eliminate unwanted characters, such as HTML tags; and so on.
Chapter 2, Building Your Own E-Commerce Solution, covers how to design a scalable e-commerce search solution to generate accurate search results using various filters, such as date-range based and prize-range based filters.
Chapter 3, Relevancy and Scoring, unleashes the power and flexibility of Elasticsearch that will help you implement your own scoring logic.
Chapter 4, Managing Relational Content, covers how to use the document linking or relational features of Elasticsearch.
Chapter 5, Analytics Using Elasticsearch, covers the capability and usage of Elasticsearch in the analytics area with a few use case scenarios.
Chapter 6, Improving the Search Experience, helps you learn how to improve the search quality of a text search. This includes the description of various analyzers and a detailed description of how to mix and match them.
Chapter 7, Spicing Up a Search Using Geo, explores how to use geo information to get the best out of search and scoring.
Chapter 8, Handling Time-based Data, explains the difficulties we face when we use normal indexing in Elasticsearch.
