Book Image

ElasticSearch Cookbook

By : Alberto Paro
Book Image

ElasticSearch Cookbook

By: Alberto Paro

Overview of this book

ElasticSearch is one of the most promising NoSQL technologies available and is built to provide a scalable search solution with built-in support for near real-time search and multi-tenancy. This practical guide is a complete reference for using ElasticSearch and covers 360 degrees of the ElasticSearch ecosystem. We will get started by showing you how to choose the correct transport layer, communicate with the server, and create custom internal actions for boosting tailored needs. Starting with the basics of the ElasticSearch architecture and how to efficiently index, search, and execute analytics on it, you will learn how to extend ElasticSearch by scripting and monitoring its behaviour. Step-by-step, this book will help you to improve your ability to manage data in indexing with more tailored mappings, along with searching and executing analytics with facets. The topics explored in the book also cover how to integrate ElasticSearch with Python and Java applications. This comprehensive guide will allow you to master storing, searching, and analyzing data with ElasticSearch.
Table of Contents (19 chapters)
ElasticSearch Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Using the geo_distance filter


When you are working with geo locations, one of the common tasks is to filter results based on its distance from a location. The geo_distance filter is used to achieve this goal.

Getting ready

You need a working ElasticSearch cluster and the data populated with the geo populate script.

How to do it...

Searching documents in which pin.location is 200km distant from the lat value 40 and the lon value 70, is done using a similar query as follows:

curl -XGET 'http://127.0.0.1:9200/test-mindex/_search -d '{
    "query": {
        "filtered": {
            "filter": {
                "geo_distance": {
                    "pin.location": {
                        "lat": 40,
                        "lon": 70
                    },
                    "distance": "200km",
                    "optimize_bbox": "memory"
                }
            },
            "query": {
                "match_all": {}
            }
        }
    }
}'

How it works...

As we discussed in the...