The geo_distance
filter draws a circle around the specified location and
finds all documents that have a geo-point within that circle:
GET /attractions/restaurant/_search
{
"query": {
"filtered": {
"filter": {
"geo_distance": {
"distance": "1km", (1)
"location": { (2)
"lat": 40.715,
"lon": -73.988
}
}
}
}
}
}
-
Find all
location
fields within1km
of the specified point. See {ref}/common-options.html#distance-units[Distance Units] for a list of the accepted units. -
The central point can be specified as a string, an array, or (as in this example) an object. See [lat-lon-formats].
A geo-distance calculation is expensive. To optimize performance, Elasticsearch draws a box around the circle and first uses the less expensive bounding-box calculation to exclude as many documents as it can. It runs the geo-distance calculation on only those points that fall within the bounding box.
Tip
|
Do your users really require an accurate circular filter to be applied to their results? Using a rectangular bounding box is much more efficient than geo-distance and will usually serve their purposes just as well. |
The distance between two points can be calculated using algorithms, which trade performance for accuracy:
arc
-
The slowest but most accurate is the
arc
calculation, which treats the world as a sphere. Accuracy is still limited because the world isn’t really a sphere. plane
-
The
plane
calculation, which treats the world as if it were flat, is faster but less accurate. It is most accurate at the equator and becomes less accurate toward the poles. sloppy_arc
-
So called because it uses the
SloppyMath
Lucene class to trade accuracy for speed, thesloppy_arc
calculation uses the Haversine formula to calculate distance. It is four to five times as fast asarc
, and distances are 99.9% accurate. This is the default calculation.
You can specify a different calculation as follows:
GET /attractions/restaurant/_search
{
"query": {
"filtered": {
"filter": {
"geo_distance": {
"distance": "1km",
"distance_type": "plane", (1)
"location": {
"lat": 40.715,
"lon": -73.988
}
}
}
}
}
}
-
Use the faster but less accurate
plane
calculation.
Tip
|
Will your users really care if a restaurant is a few meters outside their specified radius? While some geo applications require great accuracy, less-accurate but faster calculations will suit the majority of use cases just fine. |
The only difference between the geo_distance
and geo_distance_range
filters is that the latter has a doughnut shape and excludes documents within
the central hole.
Instead of specifying a single distance
from the center, you specify a
minimum distance (with gt
or gte
) and maximum distance (with lt
or
lte
), just like a range
filter:
GET /attractions/restaurant/_search
{
"query": {
"filtered": {
"filter": {
"geo_distance_range": {
"gte": "1km", (1)
"lt": "2km", (1)
"location": {
"lat": 40.715,
"lon": -73.988
}
}
}
}
}
}
-
Matches locations that are at least
1km
from the center, and less than2km
from the center.