Book Image

Elasticsearch 7.0 Cookbook - Fourth Edition

By : Alberto Paro
Book Image

Elasticsearch 7.0 Cookbook - Fourth Edition

By: Alberto Paro

Overview of this book

Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics. Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch.
Table of Contents (23 chapters)
Title Page

Managing nested objects

There is a special type of embedded object: the nested one. This resolves a problem related to Lucene indexing architecture, in which all the fields of embedded objects are viewed as a single object. During search, in Lucene, it is not possible to distinguish between values and different embedded objects in the same multi-valued array.

If we consider the previous order example, it's not possible to distinguish an item name and its quantity with the same query, as Lucene puts them in the same Lucene document object. We need to index them in different documents and then join them. This entire trip is managed by nested objects and nested queries.

Getting ready

You need an up-and-running Elasticsearch installation...