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Sorting by Distance
editSorting by Distance
editSearch results can be sorted by distance from a point:
While you can sort by distance, Scoring by Distance is usually a better solution.
GET /attractions/restaurant/_search { "query": { "filtered": { "filter": { "geo_bounding_box": { "type": "indexed", "location": { "top_left": { "lat": 40.8, "lon": -74.0 }, "bottom_right": { "lat": 40.4, "lon": -73.0 } } } } } }, "sort": [ { "_geo_distance": { "location": { "lat": 40.715, "lon": -73.998 }, "order": "asc", "unit": "km", "distance_type": "plane" } } ] }
Calculate the distance between the specified |
|
Return the distance in |
|
Use the faster but less accurate |
You may ask yourself: why do we specify the distance unit
? For sorting, it
doesn’t matter whether we compare distances in miles, kilometers, or light
years. The reason is that the actual value used for sorting is returned with
each result, in the sort
element:
... "hits": [ { "_index": "attractions", "_type": "restaurant", "_id": "2", "_score": null, "_source": { "name": "New Malaysia", "location": { "lat": 40.715, "lon": -73.997 } }, "sort": [ 0.08425653647614346 ] }, ...
You can set the unit
to return these values in whatever form makes sense for
your application.
Geo-distance sorting can also handle multiple geo-points, both in the document
and in the sort parameters. Use the sort_mode
to specify whether it should
use the min
, max
, or avg
distance between each combination of locations.
This can be used to return “friends nearest to my work and home locations.”
Scoring by Distance
editIt may be that distance is the only important factor in deciding the order in which results are returned, but more frequently we need to combine distance with other factors, such as full-text relevance, popularity, and price.
In these situations, we should reach for the
function_score
query that allows us to blend all
of these factors into an overall score. See The Closer, The Better for an
example that uses geo-distance to influence scoring.
The other drawback of sorting by distance is performance: the distance has to
be calculated for all matching documents. The function_score
query, on the
other hand, can be executed during the rescore
phase,
limiting the number of calculations to just the top n results.