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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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Author (1):
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Bharvi Dixit Bharvi Dixit
Author Profile Icon Bharvi Dixit
Bharvi Dixit
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Table of Contents (18) Chapters Close

Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
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

Geo-shapes


Geo-shapes are completely different from geo-points. Until now we have worked with simple geo-location and rectangle searches. However, with geo-shapes, the sky is the limit. On a map, you can simply draw a line, polygon, or circle and ask Elasticsearch to populate the data according to the co-ordinates of your queries, as seen in the following image:

Let's see some of the most important geo-shapes.

Point

A point is a single geographical coordinate, such as your current location shown by your smart-phone. A point in Elasticsearch is represented as follows:

{
    "location" : {
        "type" : "point",
        "coordinates" : [28.498564, 77.0812823]
    }
}

Linestring

A linestring can be defined in two ways. If it contains two coordinates, it will be a straight line, but if it contains more than two points, it will be an arbitrary path:

{
    "location" : {
        "type" : "linestring",
        "coordinates" : [[-77.03653, 38.897676], [-77.009051, 38.889939]]
    }
}

Circles

A circle...

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