| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240 | [[search-aggregations-metrics-geocentroid-aggregation]]=== Geo Centroid AggregationA metric aggregation that computes the weighted {wikipedia}/Centroid[centroid] from all coordinate values for geo fields.Example:[source,console]--------------------------------------------------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" <1>      }    }  }}--------------------------------------------------<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,console-result]--------------------------------------------------{  ...  "aggregations": {    "centroid": {      "location": {        "lat": 51.00982965203002,        "lon": 3.9662131341174245      },      "count": 6    }  }}--------------------------------------------------// 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,console]--------------------------------------------------POST /museums/_search?size=0{  "aggs": {    "cities": {      "terms": { "field": "city.keyword" },      "aggs": {        "centroid": {          "geo_centroid": { "field": "location" }        }      }    }  }}--------------------------------------------------// TEST[continued]The above example uses `geo_centroid` as a sub-aggregation to a<<search-aggregations-bucket-terms-aggregation, terms>> bucket aggregationfor finding the central location for museums in each city.The response for the above aggregation:[source,console-result]--------------------------------------------------{  ...  "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          }        }      ]    }  }}--------------------------------------------------// TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/][discrete][role="xpack"]==== Geo Centroid Aggregation on `geo_shape` fieldsThe centroid metric for geo-shapes is more nuanced than for points. The centroid of a specific aggregation bucketcontaining shapes is the centroid of the highest-dimensionality shape type in the bucket. For example, if a bucket containsshapes comprising of polygons and lines, then the lines do not contribute to the centroid metric. Each type of shape'scentroid is calculated differently. Envelopes and circles ingested via the <<ingest-circle-processor>> are treatedas polygons.|===|Geometry Type | Centroid Calculation|[Multi]Point|equally weighted average of all the coordinates|[Multi]LineString|a weighted average of all the centroids of each segment, where the weight of each segment is its length in degrees|[Multi]Polygon|a weighted average of all the centroids of all the triangles of a polygon where the triangles are formed by every two consecutive vertices and the starting-point. holes have negative weights. weights represent the area of the triangle in deg^2 calculated|GeometryCollection|The centroid of all the underlying geometries with the highest dimension. If Polygons and Lines and/or Points, then lines and/or points are ignored. If Lines and Points, then points are ignored|===Example:[source,console]--------------------------------------------------PUT /places{  "mappings": {    "properties": {      "geometry": {        "type": "geo_shape"      }    }  }}POST /places/_bulk?refresh{"index":{"_id":1}}{"name": "NEMO Science Museum", "geometry": "POINT(4.912350 52.374081)" }{"index":{"_id":2}}{"name": "Sportpark De Weeren", "geometry": { "type": "Polygon", "coordinates": [ [ [ 4.965305328369141, 52.39347642069457 ], [ 4.966979026794433, 52.391721758934835 ], [ 4.969425201416015, 52.39238958618537 ], [ 4.967944622039794, 52.39420969150824 ], [ 4.965305328369141, 52.39347642069457 ] ] ] } }POST /places/_search?size=0{  "aggs": {    "centroid": {      "geo_centroid": {        "field": "geometry"      }    }  }}--------------------------------------------------// TEST[source,console-result]--------------------------------------------------{  ...  "aggregations": {    "centroid": {      "location": {        "lat": 52.39296147599816,        "lon": 4.967404240742326      },      "count": 2    }  }}--------------------------------------------------// TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/][WARNING].Using `geo_centroid` as a sub-aggregation of `geohash_grid`====The <<search-aggregations-bucket-geohashgrid-aggregation,`geohash_grid`>>aggregation places documents, not individual geo-points, into buckets. If adocument's `geo_point` field contains <<array,multiple values>>, the documentcould be assigned to multiple buckets, even if one or more of its geo-points areoutside the bucket boundaries.If a `geocentroid` sub-aggregation is also used, each centroid is calculatedusing all geo-points in a bucket, including those outside the bucket boundaries.This can result in centroids outside of bucket boundaries.====
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