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)

Routing

We discussed before that an index contains one or more shards. During indexing, the document ID is used to determine which shard the document belongs to, using a simple formula as follows:

hash(document_id) % no_of_shards

To retrieve a document using the document ID, the same formula is used to determine the shard the document belongs to, and the document is retrieved:

When executing a search query, the node that receives the request is known as the coordinating node. The coordinating node (Node2) sends the query to all the shards of the index, aggregates the results, and sends them back to the client.

By default, a query has to be executed on all the shards of the index. But if you have a way to group similar data together, routing can be used to send the requests to a single shard instead of all the shards in the index.

For example, you want to use Elasticsearch...