一种用于计算Geo-point数据类型字段中所有座标值的加权centroid(矩心或中心)的指标聚合。
示例:
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
}
}
}
}
1 用于指定参与centroid计算的字段，注意：该字段必须是Geo-point数据类型。
针对犯罪类型为盗窃(burglary)的所有文档，上述聚合会计算盗窃比较严重的近似中心点位置。
其响应为:
{
...
"aggregations": {
"centroid": {
"location": {
"lat": 51.00982963107526,
"lon": 3.9662130922079086
},
"count": 6
}
}
}
当作为其它桶聚合的子聚合时，geo_centroid聚合会更有趣。
示例:
POST /museums/_search?size=0
{
"aggs" : {
"cities" : {
"terms" : { "field" : "city.keyword" },
"aggs" : {
"centroid" : {
"geo_centroid" : { "field" : "location" }
}
}
}
}
}
为了查找每个城市中博物馆的中心位置，上述示例会将geo_centroid作为terms桶聚合的子聚合。
其响应为：
{
...
"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
}
}
]
}
}
}
全部指标聚合，请参考
单值指标聚合
多值指标聚合
地理位置相关聚合
可执行Map-Reduce计算的聚合
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