我正在尝试使用mongoDb的$ geoNear聚合运算符以下列方式计算用户与当前位置的距离:
'$geoNear': {
near: currentLocation,
distanceField: 'distance',
spherical: true,
}
使用currentLocation类似于:
{ "type" : "Point", "coordinates" : [ -122.1575745, 37.4457966 ] }
我的收藏品属于以下类型(使用猫鼬):
users = [{
....
location : { // GeoJSON Point or I think it is ;)
type: {
type: String
},
coordinates: []
}
....
}]
我正在使用索引(再次使用mongoose的语法):
userSchema.index({
location: '2dsphere'
});
现在我面临的问题是,如果我使用如上所述的currentLocation查询(以GeoJSON的形式),我得到奇怪的距离(非常大的数字),但如果我使用currentLocation.coordinates,即使用传统坐标对( [-122.1575745,37.4457966]),我得到了正确的结果。但mongoDb docs for geoNear明确表示我们可以使用 GeoJSON点或遗留坐标对进行查询。
我很想知道GeoJSON点与遗留坐标对之间究竟有什么区别?
E.g Collection:
{ "_id" : ObjectId("5277679914c6d8f00b000003"), "location" : { "type" : "Point", "coordinates" : [ 106.6202887, -6.1293536 ] } }
{ "_id" : ObjectId("5277810148219d011c000003"), "location" : { "type" : "Point", "coordinates" : [ 106.6202887, -6.1293536 ] } }
{ "_id" : ObjectId("5281c7ba2dfd7bdc64000003"), "location" : { "type" : "Point", "coordinates" : [ -86.9248483, 33.4480108 ] } }
{ "_id" : ObjectId("5281c8b82dfd7bdc64000004"), "location" : { "type" : "Point", "coordinates" : [ -74.0087126, 40.7136487 ] } }
{ "_id" : ObjectId("5281c9782dfd7bdc64000005"), "location" : { "type" : "Point", "coordinates" : [ -122.1575745, 37.4457966 ] } }
结果不正确:
[{"location":{"type":"Point","coordinates":[-122.1575745,37.4457966]},"dis":13.69288259318155},
{"location":{"type":"Point","coordinates":[-86.9248483,33.4480108]},"dis":12697164592.388557},
{"location":{"type":"Point","coordinates":[-74.0087126,40.7136487]},"dis":16328789117.58145},
{"location":{"type":"Point","coordinates":[106.6202887,-6.1293536]},"dis":55446284682.14049},
{"location":{"type":"Point","coordinates":[106.6202887,-6.1293536]},"dis":55446284682.14049}]
答案 0 :(得分:5)
让我们创建一些示例文档和地理空间索引:
> db.foo.insert({name: "Warsaw", location: {"type" : "Point", "coordinates" : [21.016667, 52.233333]}})
> db.foo.insert({name: "Stockholm", location: {"type" : "Point", "coordinates" : [18.068611, 59.329444]}})
> db.foo.ensureIndex({"location": "2dsphere"})
华沙PL和斯德哥尔摩SE之间的距离约为810公里,所以让我们检查它是否按预期工作。首先,我们可以获取斯德哥尔摩的文件。
> Stockholm = db.foo.findOne({name: "Stockholm"})
现在我们可以使用geoNear运行查询:
> db.runCommand({ geoNear: 'foo', near: Stockholm.location.coordinates, spherical: true })
{
"ns" : "test.foo",
"results" : [
{
"dis" : 6.558558954334308e-10,
"obj" : {
"_id" : ObjectId("52876ab0b12c6fc62f5d9311"),
"name" : "Stockholm",
"location" : {
"type" : "Point",
"coordinates" : [
18.068611,
59.329444
]
}
}
},
{
"dis" : 0.12715355275490586,
"obj" : {
"_id" : ObjectId("5287697eb12c6fc62f5d9310"),
"name" : "Warsaw",
"location" : {
"type" : "Point",
"coordinates" : [
21.016667,
52.233333
]
}
}
}
],
"stats" : {
"time" : 9,
"nscanned" : 3,
"avgDistance" : 0.06357677670538088,
"maxDistance" : 0.12715355275490586
},
"ok" : 1
}
斯德哥尔摩和斯德哥尔摩之间的距离正如预期的那样接近0
。斯德哥尔摩和华沙之间的距离为0.12715355275490586
。使用传统坐标对运行查询时,得到弧度的结果,因此我们必须将此值乘以地球半径:
> 0.12715355275490586 * 6371.0
810.0952846015052
到目前为止一切顺利。让我们检查一下我们是否使用geojson作为查询获得了类似的结果。
> db.runCommand({ geoNear: 'foo', near: Stockholm.location, spherical: true })
{
"ns" : "test.foo",
"results" : [
{
"dis" : 0.004183114486663965,
"obj" : {
"_id" : ObjectId("52876ab0b12c6fc62f5d9311"),
"name" : "Stockholm",
"location" : {
"type" : "Point",
"coordinates" : [
18.068611,
59.329444
]
}
}
},
{
"dis" : 810998.0748260651,
"obj" : {
"_id" : ObjectId("5287697eb12c6fc62f5d9310"),
"name" : "Warsaw",
"location" : {
"type" : "Point",
"coordinates" : [
21.016667,
52.233333
]
}
}
}
],
"stats" : {
"time" : 4,
"nscanned" : 3,
"avgDistance" : 405499.0395045898,
"maxDistance" : 810998.0748260651
},
"ok" : 1
}
Stockholm和Stockholm之间的距离再次接近0
。斯德哥尔摩到华沙的距离是810998.0748260651。使用GeoJSON运行geoNear查询时,距离以米为单位计算。 810998.0748260651大致相当于810公里所以这里没什么奇怪的。
> 810998.0748260651 / 1000
810.9980748260651
两种解决方案之间的差异可能更小,但它只是一个FP算术。
> Math.abs(810.0952846015052 - 810.9980748260651)
0.902790224559908
对find
运算符使用$near
命令时。在旧版坐标对上创建简单2d
索引时,可以使用{$near: Stockholm.location.coordinates}
和{$near: {$geometry: Stockholm.location}
查询。如果您2dsperhical
只有{$near: {$geometry: Stockholm.location}
可以使用。