Elasticsearch Essentials by Bharvi Dixit

Elasticsearch Essentials Bharvi Dixit ebook
Page: 165
Format: pdf
Publisher: Packt Publishing, Limited
ISBN: 9781784391010

Sorting your data Data in Elasticsearch is by default sorted by a relevance score, which is computed using the Lucene scoring formula, TF/IDF. Summary In this chapter, we learned about one of the most powerful features ofElasticsearch, that is, aggregation frameworks. Summary In this chapter, you learned how to create data backups of anElasticsearch cluster and restore them back into the same or another cluster. Creating a cluster Since you have learned a major part of cluster configuration, let's begin to create a full-blown production-ready cluster. An Introduction to Kibana Kibana is a tool that is part of the ELK stack, which consists of Elasticsearch, Logstash, and Kibana. Introducing Zen-Discovery Elasticsearch is highly scalable and distributed in nature. What you need for this book This book was written using Elasticsearch version 2.0.0, and all the examples and functions should work with it. CRUD operations using Java In this section, we will go through the Elasticsearch Java client to perform the CRUD operations. Until now we have worked with simple geo-location and rectangle searches. Leaders, and operators who want to understand the essentials of Elasticsearch, performance monitoring, and tuning this technology without digging into each. Geo-shapes are completely different from geo-points. Additional functionality for forums running XenForo Enhanced Search (ElasticSearch). More focused about the search and data analytics capabilities of Elasticsearch.