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Elasticsearch 7.0 Cookbook

Elasticsearch 7.0 Cookbook

By : Alberto Paro
4 (2)
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Elasticsearch 7.0 Cookbook

Elasticsearch 7.0 Cookbook

4 (2)
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 (19 chapters)
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The common terms query

When the user is searching some text with a query, not all the terms that the user uses have the same importance. The more common terms are generally removed for query execution, to reduce the noise generated by them. These terms are called stop words and they are generally articles, conjunctions, and common language words (that is, the, a, so, and, or, and so on).

The list of stop words depends on the language, and is independent from your documents. Lucene provides ways to dynamically compute the stop words list based on your indexed document a query time using the common terms query.

Getting ready

You need an up-and-running Elasticsearch installation, as we described in the Downloading and installing...

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