Book Image

Learning Elasticsearch

By : Abhishek Andhavarapu
Book Image

Learning Elasticsearch

By: Abhishek Andhavarapu

Overview of this book

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.
Table of Contents (11 chapters)
10
Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Organizing your data

In this section, we will discuss how to divide your data into multiple indices. Elasticsearch provides index aliases, which make it very easy to query multiple indices at once. It also supports index templates to configure automatic index creation. We will also discuss how to deal with time-based data, such as logs, which is a common Elasticsearch use case.

Index alias

An index alias is a pointer to one or more indexes. A search operation executed against an alias is executed across all the indexes the alias points to. The coordinating node executes the request on all indices, collects the results, and sends them back to the client. The index operation, on the other hand, cannot be executed on an alias...