May 20, 2021 WeChat Mini Program Development Document
Support: Small program 2.7.4, cloud function 0.8.1, Web
The aggregation phase. The record is output from close to far from a given point.
| Property | Type | The default | Required | Description |
|---|---|---|---|---|
| near | GeoPoint | Is | GeoJSON Point, used to determine the point of distance | |
| spherical | true | Is | Required with a value of true | |
| limit | number | Whether | Limit the number of records returned | |
| maxDistance | number | Whether | The maximum distance | |
| minDistance | number | Whether | The minimum distance | |
| query | Object | Whether | Requires that the record meet the condition at the same time (syntax same as where) | |
| distanceMultiplier | number | Whether | Multiplies the number by the distance when you return | |
| distanceField | string | Is | The output field name of the storage distance, which can be represented by a nested field by point notation | |
| includeLocs | string | Whether | List the fields you want to use for distance calculations, which is useful if there are multiple fields in the record that are geographic locations | |
| key | string | Whether | Select the geographic location index to use. If the collection is indexed by more than one geographic location, you must specify one in a way that specifies the corresponding field |
Suppose the collection attractions have the following records:
{
"_id": "geoNear.0",
"city": "Guangzhou",
"docType": "geoNear",
"location": {
"type": "Point",
"coordinates": [
113.30593,
23.1361155
]
},
"name": "Canton Tower"
},
{
"_id": "geoNear.1",
"city": "Guangzhou",
"docType": "geoNear",
"location": {
"type": "Point",
"coordinates": [
113.306789,
23.1564721
]
},
"name": "Baiyun Mountain"
},
{
"_id": "geoNear.2",
"city": "Beijing",
"docType": "geoNear",
"location": {
"type": "Point",
"coordinates": [
116.3949659,
39.9163447
]
},
"name": "The Palace Museum"
},
{
"_id": "geoNear.3",
"city": "Beijing",
"docType": "geoNear",
"location": {
"type": "Point",
"coordinates": [
116.2328567,
40.242373
]
},
"name": "Great Wall"
}
const $ = db.command.aggregate
db.collection('attractions').aggregate()
.geoNear({
distanceField: 'distance', // 输出的每个记录中 distance 即是与给定点的距离
spherical: true,
near: db.Geo.Point(113.3089506, 23.0968251),
query: {
docType: 'geoNear',
},
key: 'location', // 若只有 location 一个地理位置索引的字段，则不需填
includeLocs: 'location', // 若只有 location 一个是地理位置，则不需填
})
.end()
The results are as follows:
{
"_id": "geoNear.0",
"location": {
"type": "Point",
"coordinates": [
113.30593,
23.1361155
]
},
"docType": "geoNear",
"name": "Canton Tower",
"city": "Guangzhou",
"distance": 4384.68131486958
},
{
"_id": "geoNear.1",
"city": "Guangzhou",
"location": {
"type": "Point",
"coordinates": [
113.306789,
23.1564721
]
},
"docType": "geoNear",
"name": "Baiyun Mountain",
"distance": 6643.521654040738
},
{
"_id": "geoNear.2",
"docType": "geoNear",
"name": "The Palace Museum",
"city": "Beijing",
"location": {
"coordinates": [
116.3949659,
39.9163447
],
"type": "Point"
},
"distance": 1894750.4414538583
},
{
"_id": "geoNear.3",
"docType": "geoNear",
"name": "Great Wall",
"city": "Beijing",
"location": {
"type": "Point",
"coordinates": [
116.2328567,
40.242373
]
},
"distance": 1928300.3308822548
}