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ElasticSearch Cookbook

You're reading from ElasticSearch Cookbook As a user of ElasticSearch in your web applications you'll already know what a powerful technology it is, and with this book you can take it to new heights with a whole range of enhanced solutions from plugins to scripting.

Product type Paperback

Published in Dec 2013

Publisher Packt

ISBN-13 9781782166627

Length 422 pages

Edition 1st Edition

Languages

Java

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Alberto Paro

View More author details

Table of Contents (14) Chapters

Preface

1. Getting Started FREE CHAPTER

2. Downloading and Setting Up ElasticSearch

3. Managing Mapping

4. Standard Operations

5. Search, Queries, and Filters

6. Facets

7. Scripting

8. Rivers

9. Cluster and Nodes Monitoring

10. Java Integration

11. Python Integration

12. Plugin Development

Index

Introduction

ElasticSearch has a powerful way to extend its capabilities with custom scripts that can be written in several programming languages. The most common ones are MVEL, JavaScript, and Python.

We already have a taste of the scripting capabilities of ElasticSearch, in the previous chapter, using scripting for facets. In this chapter we will see how it's possible to create custom scoring algorithms, special processed return fields, custom sorting or complex update operations on records.

The scripting concept of ElasticSearch can be seen as an advanced stored procedures system in the NoSQL world; so, for an advanced use of ElasticSearch, it is very important to master it.

The rest of the chapter is locked

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Authors (1)

Alberto Paro

Alberto Paro

Alberto Paro is an engineer, manager, and software developer. He currently works as technology architecture delivery associate director of the Accenture Cloud First data and AI team in Italy. He loves to study emerging solutions and applications, mainly related to cloud and big data processing, NoSQL, Natural language processing (NLP), software development, and machine learning. In 2000, he graduated in computer science engineering from Politecnico di Milano. Then, he worked with many companies, mainly using Scala/Java and Python on knowledge management solutions and advanced data mining products, using state-of-the-art big data software. A lot of his time is spent teaching how to effectively use big data solutions, NoSQL data stores, and related technologies.

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