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Elasticsearch Essentials

You're reading from  Elasticsearch Essentials

Product type Book
Published in Jan 2016
Publisher
ISBN-13 9781784391010
Pages 240 pages
Edition 1st Edition
Languages

Table of Contents (18) Chapters

Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
1. Getting Started with Elasticsearch 2. Understanding Document Analysis and Creating Mappings 3. Putting Elasticsearch into Action 4. Aggregations for Analytics 5. Data Looks Better on Maps: Master Geo-Spatiality 6. Document Relationships in NoSQL World 7. Different Methods of Search and Bulk Operations 8. Controlling Relevancy 9. Cluster Scaling in Production Deployments 10. Backups and Security Index

Summary


In this chapter, we learned about one of the most powerful features of Elasticsearch, that is, aggregation frameworks. We went through the most important metric and bucket aggregations along with examples of doing analytics on our Twitter dataset with Python and Java API.

This chapter covered many fundamental as well complex examples of the different facets of analytics, which can be built using a combination of full-text searches, term-based searches, and multilevel aggregations. Elasticsearch is awesome for analytics but one should always keep in mind the memory implications, which we covered in the last section of this chapter, to avoid the over killing of nodes.

In the next chapter, we will learn to work with geo spatial data in Elasticsearch and we will also cover analytics with geo aggregations.

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