[[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 <> 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 <> 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": 51.00982963107526, "lon": 3.9662130922079086 } } } } -------------------------------------------------- // 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 <> 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": 4.909563297405839 } } }, { "key": "Paris", "doc_count": 2, "centroid": { "location": { "lat": 48.86055548675358, "lon": 2.3316944623366 } } }, { "key": "Antwerp", "doc_count": 1, "centroid": { "location": { "lat": 51.22289997059852, "lon": 4.40519998781383 } } } ] } } } -------------------------------------------------- // TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/]