Book Image

Elasticsearch 5.x Cookbook - Third Edition

By : Alberto Paro
Book Image

Elasticsearch 5.x Cookbook - Third 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. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch.
Table of Contents (25 chapters)
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

Executing filters aggregations


The filters aggregation answers the common requirement to split buckets documents using custom filters, which can be every kind of query supported by Elasticsearch.

Getting ready

You need an up-and-running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 2, Downloading and Setup.

To execute curl via the command line, you need to install curl for your operative system.

To correctly execute the following command, you need an index populated with the chapter_08/populate_aggregations.sh script available in the online code.

How to do it...

For executing filters aggregations, we will perform the following steps:

  1. We need to compute a filters aggregation composed by the following queries:

    • Date greater than 2016/01/01 and price greater or equal to 50

    • Date lower than 2016/01/01 and price greater or equal to 50

    • All the documents that are not matched

  2. The query to execute these aggregations is as follows:

            curl -XGET...