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Elasticsearch 5.x Cookbook

Elasticsearch 5.x Cookbook

By : Alberto Paro
2.5 (4)
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Elasticsearch 5.x Cookbook

Elasticsearch 5.x Cookbook

2.5 (4)
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)
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Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

Executing a standard search


After inserting documents, the most commonly executed action in Elasticsearch is the search. The official Elasticsearch client APIs for searching are similar to the REST API.

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.

You also need the Python installed packages of the Creating a client recipe of this chapter.

The code of this recipe can be found in the chapter_16/searching.py file.

How to do it…

To execute a standard query, the client method search must be called by passing the query parameters, as we have seen in Chapter 5, Search. The required parameters are index_name, type_name and the query DSL. In this example, we show how to call a match_all query, a term query, and a filter query. We will perform the following steps:

  1. We initialize the client and populate the index:

            import elasticsearch 
            from pprint import pprint...

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