Book Image

ElasticSearch Cookbook

By : Alberto Paro
Book Image

ElasticSearch Cookbook

By: Alberto Paro

Overview of this book

ElasticSearch is one of the most promising NoSQL technologies available and is built to provide a scalable search solution with built-in support for near real-time search and multi-tenancy. This practical guide is a complete reference for using ElasticSearch and covers 360 degrees of the ElasticSearch ecosystem. We will get started by showing you how to choose the correct transport layer, communicate with the server, and create custom internal actions for boosting tailored needs. Starting with the basics of the ElasticSearch architecture and how to efficiently index, search, and execute analytics on it, you will learn how to extend ElasticSearch by scripting and monitoring its behaviour. Step-by-step, this book will help you to improve your ability to manage data in indexing with more tailored mappings, along with searching and executing analytics with facets. The topics explored in the book also cover how to integrate ElasticSearch with Python and Java applications. This comprehensive guide will allow you to master storing, searching, and analyzing data with ElasticSearch.
Table of Contents (19 chapters)
ElasticSearch Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Introduction


After having the mappings set and the data inserted in the indices, now we can enjoy the search.

In this chapter we will cover the different types of search queries and filters, validate queries, return highlights and limiting fields. This chapter is the core part of the book; and in this chapter the user will understand the difference between query and filter and how to improve quality and speed in search. ElasticSearch allows usage of a rich DSL that covers all common needs: from standard term query to complex GeoShape filtering.

This chapter is divided in to two parts: the first part shows some API calls related search, the second part goes in deep with the query DSL.

To prepare a good base for searching, in online code there are scripts to prepare indices and data for the next recipes.