Geo Centroid Aggregation
editGeo Centroid Aggregation
editA metric aggregation that computes the weighted centroid from all coordinate values for a Geo-point field.
Example:
PUT /museums
{
"mappings": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
POST /museums/_bulk?refresh
{"index":{"_id":1}}
{"location": "52.374081,4.912350", "city": "Amsterdam", "name": "NEMO Science Museum"}
{"index":{"_id":2}}
{"location": "52.369219,4.901618", "city": "Amsterdam", "name": "Museum Het Rembrandthuis"}
{"index":{"_id":3}}
{"location": "52.371667,4.914722", "city": "Amsterdam", "name": "Nederlands Scheepvaartmuseum"}
{"index":{"_id":4}}
{"location": "51.222900,4.405200", "city": "Antwerp", "name": "Letterenhuis"}
{"index":{"_id":5}}
{"location": "48.861111,2.336389", "city": "Paris", "name": "Musée du Louvre"}
{"index":{"_id":6}}
{"location": "48.860000,2.327000", "city": "Paris", "name": "Musée d'Orsay"}
POST /museums/_search?size=0
{
"aggs" : {
"centroid" : {
"geo_centroid" : {
"field" : "location"
}
}
}
}
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The |
The above aggregation demonstrates how one would compute the centroid of the location field for all documents with a crime type of burglary
The response for the above aggregation:
{
...
"aggregations": {
"centroid": {
"location": {
"lat": 51.00982965203002,
"lon": 3.9662131341174245
},
"count": 6
}
}
}
The geo_centroid aggregation is more interesting when combined as a sub-aggregation to other bucket aggregations.
Example:
POST /museums/_search?size=0
{
"aggs" : {
"cities" : {
"terms" : { "field" : "city.keyword" },
"aggs" : {
"centroid" : {
"geo_centroid" : { "field" : "location" }
}
}
}
}
}
The above example uses geo_centroid as a sub-aggregation to a
terms bucket aggregation
for finding the central location for museums in each city.
The response for the above aggregation:
{
...
"aggregations": {
"cities": {
"sum_other_doc_count": 0,
"doc_count_error_upper_bound": 0,
"buckets": [
{
"key": "Amsterdam",
"doc_count": 3,
"centroid": {
"location": {
"lat": 52.371655656024814,
"lon": 4.909563297405839
},
"count": 3
}
},
{
"key": "Paris",
"doc_count": 2,
"centroid": {
"location": {
"lat": 48.86055548675358,
"lon": 2.3316944623366
},
"count": 2
}
},
{
"key": "Antwerp",
"doc_count": 1,
"centroid": {
"location": {
"lat": 51.22289997059852,
"lon": 4.40519998781383
},
"count": 1
}
}
]
}
}
}
Using geo_centroid as a sub-aggregation of geohash_grid
The geohash_grid
aggregation places documents, not individual geo-points, into buckets. If a
document’s geo_point field contains multiple values, the document
could be assigned to multiple buckets, even if one or more of its geo-points are
outside the bucket boundaries.
If a geocentroid sub-aggregation is also used, each centroid is calculated
using all geo-points in a bucket, including those outside the bucket boundaries.
This can result in centroids outside of bucket boundaries.