$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查找距离中心[ -73.99279 , 40.719296 ]最多2米并且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，并且
• 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. 下面的示例使用选项minDistance指定文档与中心点的最小距离。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.以下聚合查找距离中心[ -73.99279 , 40.719296 ]至少2米并且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
     }
   }
])

$geoNear with the let option$geoNear和let选项

In this example:在这个例子中：

• 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 $geoNear stage.指定为$geoNear阶段中的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:聚合返回包含以下内容的所有文档：

• 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.等同于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带绑定let选项

The let option can bind a variable which can be used in a $geoNear query.let选项可以绑定可以在$geoNear查询中使用的变量。

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

• let to define $pt.以定义$pt。
• $geoNear in the pipeline.pipeline中的$geoNear。
• $pt to define near in the $geoNear pipeline stage.在$geoNear管道阶段定义near的$pt。

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:聚合返回包含以下内容的文档：

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

{
   _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字段上具有2d索引。

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

{
   "_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，而不是传统字段值。The pipeline also uses $limit to return at most 5 documents.管道还使用$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
   }
}