$geoNear (aggregation)

Maximum Distance最大距离

The places collection above has a 2dsphere index. 上面的places集合有一个2dsphere索引。The following aggregation uses $geoNear to find documents with a location at most 2 meters from the center [ -73.99279 , 40.719296 ] and category equal to Parks.以下聚合使用$geoNear查找位置距离中心[ -73.99279 , 40.719296 ]最多2米且category等于Parks的文档。

db.places.aggregate([
   {
     $geoNear: {
        near: { type: "Point", coordinates: [ -73.99279 , 40.719296 ] },
        distanceField: "dist.calculated",
        maxDistance: 2,
        query: { category: "Parks" },
        includeLocs: "dist.location",
        spherical: true
     }
   }
])

The aggregation returns the following:聚合返回以下内容：

{
   "_id" : 8,
   "name" : "Sara D. Roosevelt Park",
   "category" : "Parks",
   "location" : {
      "type" : "Point",
      "coordinates" : [ -73.9928, 40.7193 ]
   },
   "dist" : {
      "calculated" : 0.9539931676365992,
      "location" : {
         "type" : "Point",
         "coordinates" : [ -73.9928, 40.7193 ]
      }
   }
}

The matching document contains two new fields:匹配的文档包含两个新字段：

• dist.calculated field that contains the calculated distance, and包含计算距离的字段，以及
• dist.location field that contains the location used in the calculation.包含计算中使用的位置的字段。

Minimum Distance最小距离

The following example uses the option minDistance to specify the minimum distance from the center point that the documents can be. 以下示例使用选项minDistance来指定与文档可能位于的中心点的最小距离。The following aggregation finds all documents with a location at least 2 meters from the center [ -73.99279 , 40.719296 ] and category equal to Parks.以下聚合查找位置距离中心[ -73.99279 , 40.719296 ]至少2米且category等于Parks的所有文档。

db.places.aggregate([
   {
     $geoNear: {
        near: { type: "Point", coordinates: [ -73.99279 , 40.719296 ] },
        distanceField: "dist.calculated",
        minDistance: 2,
        query: { category: "Parks" },
        includeLocs: "dist.location",
        spherical: true
     }
   }
])

$geoNear with the let option带有let选项的$geoNear

In this example:在本例中：

• The let option is used to set an array value of [-73.99279,40.719296] to the variable $pt.let选项用于将数组值[-73.99279,40.719296]设置为变量$pt。
• $pt is specified as a let option to the near parameter in the $geoNear stage.被指定为$geoNear阶段中near参数的let选项。

db.places.aggregate(
[
   {
      "$geoNear":
      {
         "near":"$$pt",
         "distanceField":"distance",
         "maxDistance":2,
         "query":{"category":"Parks"},
         "includeLocs":"dist.location",
         "spherical":true
      }
   }
],
{
   "let":{ "pt": [ -73.99279, 40.719296 ] }
}
)

The aggregation returns all documents with:聚合返回所有文档，其中包含：

• A location at most 2 meters from the point defined in the let variable距离let变量中定义的点最多2米的位置
• A category equal to Parks.一个等于Parks的category。

{
   _id: ObjectId("61715cf9b0c1d171bb498fd7"),
   name: 'Sara D. Roosevelt Park',
   location: { type: 'Point', coordinates: [ -73.9928, 40.7193 ] },
   category: 'Parks',
   distance: 1.4957325341976439e-7,
   dist: { location: { type: 'Point', coordinates: [ -73.9928, 40.7193 ] } }
},
{
   _id: ObjectId("61715cf9b0c1d171bb498fd6"),
   name: 'Central Park',
   location: { type: 'Point', coordinates: [ -73.97, 40.77 ] },
   category: 'Parks',
   distance: 0.0009348548688841822,
   dist: { location: { type: 'Point', coordinates: [ -73.97, 40.77 ] } }
}

$geoNear with Bound let Option$geoNear与边界let选项

The let option can bind a variable which can be used in a $geoNear query.let选项可以绑定一个变量，该变量可以在$geoNear查询中使用。

In this example, $lookup uses:在本例中，$lookup使用：

• let to define $pt.let用来定义$pt。
• $geoNear in the pipeline.pipeline中的$geoNear。
• $pt to define near in the $geoNear pipeline stage.用来定义$geoNear管道阶段中的near

db.places.aggregate( [
   {
      $lookup: {
         from: "places",
         let: { pt: "$location" },
         pipeline: [
            {
               $geoNear: {
                  near: "$$pt",
                  distanceField: "distance"
               }
            }
         ],
         as: "joinedField"
      }
   },
   {
      $match: { name: "Sara D. Roosevelt Park" }
   }
] );

The aggregation returns a document with:聚合返回一个文档，其中包含：

• The 'Sara D. Roosevelt Park' document as the main document.以“萨拉·D·罗斯福公园”文件为主要文档。
• Every document in the places collection as subDocuments using the $pt variable for calculating distance.places集合中的每个文档都是使用$pt变量计算距离的子文档。

{
   _id: ObjectId("61715cf9b0c1d171bb498fd7"),
      name: 'Sara D. Roosevelt Park',
      location: { type: 'Point', coordinates: [ -73.9928, 40.7193 ] },
      category: 'Parks',
      joinedField: [
         {
         _id: ObjectId("61715cf9b0c1d171bb498fd7"),
         name: 'Sara D. Roosevelt Park',
         location: { type: 'Point', coordinates: [ -73.9928, 40.7193 ] },
         category: 'Parks',
         distance: 0
         },
         {
         _id: ObjectId("61715cf9b0c1d171bb498fd6"),
         name: 'Central Park',
         location: { type: 'Point', coordinates: [ -73.97, 40.77 ] },
         category: 'Parks',
         distance: 5962.448255234964
         },
         {
         _id: ObjectId("61715cfab0c1d171bb498fd8"),
         name: 'Polo Grounds',
         location: { type: 'Point', coordinates: [ -73.9375, 40.8303 ] },
         category: 'Stadiums',
         distance: 13206.535424939102
         }
      ]
}

Specify Which Geospatial Index to Use指定要使用的地理空间索引

Consider a places collection that has a 2dsphere index on the location field and a 2d index on the legacy field.考虑一个places集合，该集合在location字段上具有2dsphere索引，在legacy字段上有2d索引。

A document in the places collection resembles the following:places集合中的文档类似于以下内容：

{
   "_id" : 3,
   "name" : "Polo Grounds",
   "location": {
      "type" : "Point",
      "coordinates" : [ -73.9375, 40.8303 ]
   },
   "legacy" : [ -73.9375, 40.8303 ],
   "category" : "Stadiums"
}

The following example uses the key option to specify that the aggregation should use the location field values for the $geoNear operation rather than the legacy field values. 以下示例使用key选项指定聚合应使用$geoNear操作的location字段值，而不是旧字段值。The pipeline also uses $limit to return at most 5 documents.该管道还使用$limit返回最多5个文档。

db.places.aggregate([
   {
     $geoNear: {
        near: { type: "Point", coordinates: [ -73.98142 , 40.71782 ] },
        key: "location",
        distanceField: "dist.calculated",
        query: { "category": "Parks" }
     }
   },
   { $limit: 5 }
])

The aggregation returns the following:聚合返回以下内容：

{
   "_id" : 8,
   "name" : "Sara D. Roosevelt Park",
   "location" : {
      "type" : "Point",
      "coordinates" : [
         -73.9928,
         40.7193
      ]
   },
   "category" : "Parks",
   "dist" : {
      "calculated" : 974.175764916902
   }
}
{
   "_id" : 1,
   "name" : "Central Park",
   "location" : {
      "type" : "Point",
      "coordinates" : [
         -73.97,
         40.77
      ]
   },
   "legacy" : [
      -73.97,
      40.77
   ],
   "category" : "Parks",
   "dist" : {
      "calculated" : 5887.92792958097
   }
}