Learning Elasticsearch

Key Features
Get to grips with the basics of Elasticsearch concepts and its APIs, and use them to create efficient applications
Create large-scale Elasticsearch clusters and perform analytics using aggregation
This comprehensive guide will get you up and running with Elasticsearch 5.x in no time
Book Description
Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently.
You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data.
Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments.
What you will learn
See how to set up and configure Elasticsearch and Kibana
Know how to ingest structured and unstructured data using Elasticsearch
Understand how a search engine works and the concepts of relevance and scoring
Find out how to query Elasticsearch with a high degree of performance and scalability
Improve the user experience by using autocomplete, geolocation queries, and much more
See how to slice and dice your data using Elasticsearch aggregations.
Grasp how to use Kibana to explore and visualize your data
Know how to host on Elastic Cloud and how to use the latest X-Pack features such as Graph and Alerting
About the Author
Abhishek Andhavarapu is a software engineer at eBay who enjoys working on highly scalable distributed systems. He has a master's degree in Distributed Computing and has worked on multiple enterprise Elasticsearch applications, which are currently serving hundreds of millions of requests per day.
He began his journey with Elasticsearch in 2012 to build an analytics engine to power dashboards and quickly realized that Elasticsearch is like nothing out there for search and analytics. He has been a strong advocate since then and wrote this book to share the practical knowledge he gained along the way.
Table of Contents
Introduction to Elasticsearch
Setting up Elasticsearch and Kibana
Modeling your data and Document Relations
Indexing an Updating your data
Organizing your data and bulk data ingestion
All about search
More than a search engine (Geofilters, Autocomplete and more)
How to slice and dice your data using aggregations
Production and Beyond
Exploring Elastic Stack (Elastic Cloud, Security, Graph and Alerting)