With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world’s most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store.
This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Who This Book Is For
Anyone who wants to build efficient search and analytics applications can choose this book. This book is also beneficial for skilled developers, especially ones experienced with Lucene or Solr, who now want to learn Elasticsearch quickly.
What You Will Learn
- Get to know about advanced Elasticsearch concepts and its REST APIs
- Write CRUD operations and other search functionalities using the ElasticSearch Python and Java clients
- Dig into wide range of queries and find out how to use them correctly
- Design schema and mappings with built-in and custom analyzers
- Excel in data modeling concepts and query optimization
- Master document relationships and geospatial data
- Build analytics using aggregations
- Setup and scale Elasticsearch clusters using best practices
- Learn to take data backups and secure Elasticsearch clusters