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Learning Elasticsearch

You're reading from   Learning Elasticsearch Structured and unstructured data using distributed real-time search and analytics

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787128453
Length 404 pages
Edition 1st Edition
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Author (1):
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Abhishek Andhavarapu Abhishek Andhavarapu
Author Profile Icon Abhishek Andhavarapu
Abhishek Andhavarapu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Elasticsearch FREE CHAPTER 2. Setting Up Elasticsearch and Kibana 3. Modeling Your Data and Document Relations 4. Indexing and Updating Your Data 5. Organizing Your Data and Bulk Data Ingestion 6. All About Search 7. More Than a Search Engine (Geofilters, Autocomplete, and More) 8. How to Slice and Dice Your Data Using Aggregations 9. Production and Beyond 10. Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Summary

In this chapter, we discussed Elastic Cloud, which is the scalable cloud offering for Elasticsearch and Kibana. We also discussed various features of X-Pack. With monitoring and alerting, you can make sure your cluster is up and running and that your data is always available.

Although Elasticsearch started as a search engine, it is evolving as an analytics engine. In this chapter, we discussed Graph, which can be used to discover relations in your data. We used the example of an e-commerce store to make recommendations, but this functionality has great potential. For example, for fraud detection or to find out the similarity between customers who like or don't like your product have in common. The graph provides actionable insights into your data.

The alert and notification system that we discussed in this chapter is very flexible. We used alerting to get notified...

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