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[[search-aggregations-metrics-geocentroid-aggregation]]
=== Geo Centroid Aggregation
A metric aggregation that computes the weighted https://en.wikipedia.org/wiki/Centroid[centroid] from all coordinate values for a <<geo-point>> field.
Example:
[source,js]
--------------------------------------------------
PUT /museums
{
"mappings": {
"doc": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
}
POST /museums/doc/_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" <1>
}
}
}
}
--------------------------------------------------
// CONSOLE
<1> The `geo_centroid` aggregation specifies the field to use for computing the centroid. (NOTE: field must be a <<geo-point>> type)
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:
[source,js]
--------------------------------------------------
{
...
"aggregations": {
"centroid": {
"location": {
"lat": 51.009829603135586,
"lon": 3.966213036328554
}
}
}
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/]
The `geo_centroid` aggregation is more interesting when combined as a sub-aggregation to other bucket aggregations.
Example:
[source,js]
--------------------------------------------------
POST /museums/_search?size=0
{
"aggs" : {
"cities" : {
"terms" : { "field" : "city.keyword" },
"aggs" : {
"centroid" : {
"geo_centroid" : { "field" : "location" }
}
}
}
}
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
The above example uses `geo_centroid` as a sub-aggregation to a
<<search-aggregations-bucket-terms-aggregation, terms>> bucket aggregation
for finding the central location for museums in each city.
The response for the above aggregation:
[source,js]
--------------------------------------------------
{
...
"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": 4.909563269466162
}
}
},
{
"key": "Paris",
"doc_count": 2,
"centroid": {
"location": {
"lat": 48.86055544484407,
"lon": 2.331694420427084
}
}
},
{
"key": "Antwerp",
"doc_count": 1,
"centroid": {
"location": {
"lat": 51.222899928689,
"lon": 4.405199903994799
}
}
}
]
}
}
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/]
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