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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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Executing top hit aggregations

The top hit aggregation is different from the other aggregation types: all the previous aggregations have metric (simple values) or bucket values; the top hit aggregation returns buckets of search hits (documents).

Generally, the top hit aggregation is used as a sub-aggregation, so that the top matching documents can be aggregated in buckets. The most common scenario for this aggregation is to have, for example, the top n documents grouped by category (very common in search results in e-commerce websites).

Getting ready

You need an up and running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started...

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