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Mastering Elasticsearch 5.x

You're reading from Mastering Elasticsearch 5.x Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions

Product type Paperback

Published in Feb 2017

Publisher Packt

ISBN-13 9781786460189

Length 428 pages

Edition 3rd Edition

Languages

Java

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Bharvi Dixit

View More author details

Table of Contents (13) Chapters

Preface

1. Revisiting Elasticsearch and the Changes FREE CHAPTER

2. The Improved Query DSL

3. Beyond Full Text Search

4. Data Modeling and Analytics

5. Improving the User Search Experience

6. The Index Distribution Architecture

7. Low-Level Index Control

8. Elasticsearch Administration

9. Data Transformation and Federated Search

10. Improving Performance

11. Developing Elasticsearch Plugins

12. Introducing Elastic Stack 5.0

Controlling multimatching

It is often required to search the terms in more than one field in a single query. This can be easily done using the multi_match query available in Elasticsearch. But, what's more important is to know and control the score calculation while using the multi_match queries. The multi_match query is built over a simple match query to allow for searching inside multiple fields.

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Authors (1)

Bharvi Dixit

Bharvi Dixit

Bharvi Dixit is an IT professional with extensive experience of working on search servers, NoSQL databases, and cloud services. He holds a master's degree in computer science and is currently working with Sentieo, a USA-based financial data and equity research platform, where he leads the overall platform and architecture of the company spanning across hundreds of servers. At Sentieo, he also plays a key role in the search and data team. He is also the organizer of Delhi's Elasticsearch Meetup Group, where he speaks about Elasticsearch and Lucene and is continuously building the community around these technologies. Bharvi also works as a freelance Elasticsearch consultant and has helped more than half a dozen organizations adapt Elasticsearch to solve their complex search problems around different use cases, such as creating search solutions for big data-automated intelligence platforms in the area of counter-terrorism and risk management, as well as in other domains, such as recruitment, e-commerce, finance, social search, and log monitoring. He has a keen interest in creating scalable backend platforms. His other areas of interests are search engineering, data analytics, and distributed computing. Java and Python are the primary languages in which he loves to write code. He has also built a proprietary software for consultancy firms. In 2013, he started working on Lucene and Elasticsearch, and in 2016, he authored his first book, Elasticsearch Essentials, which was published by Packt. He has also worked as a technical reviewer for the book Learning Kibana 5.0 by Packt. You can connect with him on LinkedIn at https://in.linkedin.com/in/bharvidixit or can follow him on Twitter @d_bharvi.

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