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)
Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Ingest Node

Traditionally, Logstash is used to preprocess your data before indexing into Elasticsearch. Using Logstash, you can define pipelines to extract, transform, and index your data into Elasticsearch.

In Elasticsearch 5.0, the ingest node has been introduced. Using the ingest node, pipelines to modify the documents before indexing can be defined. A pipeline is a series of processors, each processor working on one or more fields in the document. The most commonly used Logstash filters are available as processors. For example, using a grok filter to extract data from an Apache log file into a document, extracting fields from JSON, changing the date format, calculating geo-distance from a location, and so on. The possibilities are endless. Elasticsearch supports many processors out of the box. You can also develop your own processors using any JVM-supported languages.

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