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Elasticsearch Essentials

You're reading from   Elasticsearch Essentials Harness the power of ElasticSearch to build and manage scalable search and analytics solutions with this fast-paced guide

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781784391010
Length 240 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with Elasticsearch FREE CHAPTER 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

Introducing the aggregation framework


The aggregation functionality is completely different from search and enables you to ask sophisticated questions of the data. The use cases of aggregation vary from building analytical reports to getting real-time analysis of data and taking quick actions.

Also, despite being different in functionality, aggregations can operate along the usual search requests. Therefore, you can search or filter your data, and at the same time, you can also perform aggregation on the same datasets matched by search/filter criteria in a single request. A simple example can be to find the maximum number of hashtags used by users related to tweets that has crime in the text field. Aggregations enable you to calculate and summarize data about the current query on the fly. They can be used for all sorts of tasks such as dynamic counting of result values to building a histogram.

Aggregations come in two flavors: metrics and buckets.

  • Metrics: Metrics are used to do statistics...

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