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Search results can be sorted by distance from a point:
|
Tip
|
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": { (1)
"lat": 40.715,
"lon": -73.998
},
"order": "asc",
"unit": "km", (2)
"distance_type": "plane" (3)
}
}
]
}
Calculate the distance between the specified lat/lon point and the
geo-point in the location field of each document.
Return the distance in km in the sort keys for each result.
Use the faster but less accurate plane calculation.
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 (1)
]
},
...
This restaurant is 0.084km from the location we specified.
You can set the unit to return these values in whatever form makes sense for
your application.
|
Tip
|
Geo-distance sorting can also handle multiple geo-points, both in the document
and in the sort parameters. Use the |
It 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 [decay-functions] 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.
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