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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

Introduction


Elasticsearch functionalities can be easily integrated in any Java application in several ways, both via a REST API and native ones.

In Java it's easy to call a REST HTTP interface with one of the many of libraries available, such as the Apache HttpComponents client http://hc.apache.org/. In this field there's no such thing as the most used library; typically, developers choose the library that best suits their preferences or that they know very well.

Each JVM language can also use the native protocol (discussed in C) to integrate Elasticsearch with their applications.

Chapter 1, Getting Started is one of the faster protocols available to communicate with Elasticsearch due to many factors such as its binary nature, its fast native serializer or deserializer of the data, its asynchronous approach to communicating, and the hop reduction (native client nodes are able to communicate directly with the node that contains the data without executing the double hop needed in REST calls...

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