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)

Caching

In Elasticsearch 5.0, a lot of refactoring has been done to support better caching. The different types of cache available are as follows:

  • Node Query cache: Queries that run in filter context are cached here
  • Shard request cache: The results of the entire query are cached here

Node Query cache

Queries, such as numeric or date range, which run in the filter context are great candidates for caching. Since they have no scoring phase, they can be reused. The Node query cache is a smart cache; you do not have to worry about invalidating the cache. Individual queries that run in filter context are cached here. This cache is maintained at a node level and defaults to 10% of the heap and can be configured using the elasticsearch...