Mapping a geo point field
ElasticSearch natively supports the use of geolocation types: special types that allow you to localize your document in geographic coordinates (latitude and longitude) around the world.
There are two main document types used in the geographic world: point and shape. In this recipe, we'll see geo point, the base element of geolocation.
Getting ready
You need a working ElasticSearch cluster.
How to do it...
The type of the field must be set to geo_point in order to define a geo point.
You can extend the earlier order example by adding a new field that stores the location of a customer. The following will be the result:
{
"order": {
"properties": {
"id": {
"type": "string",
"store": "yes",
"index": "not_analyzed"
},
"date": {
"type": "date",
"store": "no",
"index": "not_analyzed"
},
"customer_id": {
"type": "string",
"store": "yes",
"index": "not_analyzed"
},
"customer_ip": {
"type": "ip",
"store": "yes",
"index": "not_analyzed"
},
"customer_location": {
"type": "geo_point",
"store": "yes"
},
"sent": {
"type": "boolean",
"store": "no",
"index": "not_analyzed"
}
}
}
}
How it works...
When ElasticSearch indexes a document with a geo point field (latitude, longitude), it processes the latitude and longitude coordinates and creates special accessory field data to quickly query these coordinates.
Depending on the properties, given a latitude and longitude it's possible to compute the geohash value (http://en.wikipedia.org/wiki/Geohash). The index process also optimizes these values for special computation, such as distance and ranges, and in a shape match.
Geo point has special parameters that allow you to store additional geographic data:
lat_lon(by default,false): This allows you to store the latitude and longitude in the.latand.lonfields. Storing these values improves performance in many memory algorithms used in distance and shape calculus.geohash(by default,false): This allows you to store the computed geohash value.geohash_precision(by default,12): This defines the precision to be used in a geohash calculus. For example, given a geo point value [45.61752, 9.08363], it will store:customer_location = "45.61752, 9.08363"customer_location.lat = 45.61752customer_location.lon = 9.08363customer_location.geohash = "u0n7w8qmrfj"
There's more...
Geo point is a special type and can accept several formats as input:
- Latitude and longitude as properties:
"customer_location": { "lat": 45.61752, "lon": 9.08363 }, - Latitude and longitude as a string:
"customer_location": "45.61752,9.08363",
- Latitude and longitude as geohash string
- Latitude and longitude as a GeoJSON array (note that in this latitude and longitude are reversed):
"customer_location": [9.08363, 45.61752]