Book Image

Elasticsearch Essentials

Book Image

Elasticsearch Essentials

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (18 chapters)
Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Search requests using Java


While it's easy to write a JSON query and directly use it with the Python client, using Java client requires a bit of expertise to create queries using Elasticsearch Java APIs.

In Java, there is the QueryBuilder class that helps you in constructing queries. Once the queries are created, you can execute that query with the client's prepareSearch method.

First of all, you need the following imports in your code:

import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;

Then you can start building queries and executing them:

QueryBuilder query = QueryBuilders.termQuery("screen_name", "d_bharvi");
SearchResponse response = client.prepareSearch()
    .setIndices(indexName).setTypes(docType)
    .setQuery(query).setFrom(0).setSize(10)
    .execute().actionGet();

The preceding code shows an example of creating term queries where we search for a term, d_bharvi, inside the screen_name field...