1

案子

我已使用 2dsphere 索引将位置坐标存储在 MongoDB 集合中。我想获取包含在地图特定范围内的记录。我有一个固定的经纬度坐标点。我已经在 MongoDB 聚合中$geoWithin使用了该方法。$box我能够正确获取数据。

问题

我需要在我拥有的一个固定纬度和经度的每条记录中添加距离字段。

{
  "$match": {
    "location": {
      "$geoWithin": {
        "$box": [
          [
            0.024719919885622943,
            51.54643953472475
          ],
          [
            -0.1589577534542408,
            51.47239969138267
          ]
        ]
      }
    }
  }
}

现在我有坐标数组[-0.0649729793707321, 51.50160291888072]

我需要从上述点开始的每条记录的距离。如何使用 MongoDB 聚合找到这个距离场？

数据库记录的示例文档

{
    "_id" : ObjectId("5e342ac2e0dcfa65273751ea"),
    "location" : {
        "type" : "Point",
        "coordinates" : [ 
            -0.123507, 
            51.5083228
        ]
    },
    "status" : 1,
    "price" : {
        "value" : 27,
        "type" : "day",
        "base" : 3.38
    },
    "name" : "Initial Space with Wormup",
    "venuePolicy" : "Venue Policies",
    "updatedAt" : ISODate("2020-02-20T12:28:16.024Z"),
    "createdAt" : ISODate("2020-01-31T13:25:22.600Z"),
    "dimension" : {
        "width" : 100
    },
    "description" : "<p>Hi,&nbsp;</p><p>please find attached document for testing purpose",
}
4

1 回答 1

2

这个应该工作：

db.collection.aggregate([
   {
      "$match": {
         "location": {
            "$geoWithin": {
               "$box": [
                  [0.024719919885622943, 51.54643953472475],
                  [-0.1589577534542408, 51.47239969138267]
               ]
            }
         }
      }
   },
   { $set: { lon: -0.0649729793707321 } },
   { $set: { lat: 51.50160291888072 } },
   {
      $set: {
         distance: {
            $let: {
               vars: {
                  dlon: { $degreesToRadians: { $subtract: [{ $arrayElemAt: ["$location.coordinates", 0] }, "$lon"] } },
                  dlat: { $degreesToRadians: { $subtract: [{ $arrayElemAt: ["$location.coordinates", 1] }, "$lat"] } },
                  lat1: { $degreesToRadians: { $arrayElemAt: ["$location.coordinates", 1] } },
                  lat2: { $degreesToRadians: "$lat" }
               },
               in: {
                  // Haversine formula: sin²(dLat / 2) + sin²(dLon / 2) * cos(lat1) * cos(lat2);
                  $add: [
                     { $pow: [{ $sin: { $divide: ["$$dlat", 2] } }, 2] },
                     { $multiply: [{ $pow: [{ $sin: { $divide: ["$$dlon", 2] } }, 2] }, { $cos: "$$lat1" }, { $cos: "$$lat2" }] }
                  ]
               }
            }
         }
      }
   },
   {
      $set: {
         distance: {
            // Distance in Meters given by "6372.8 * 1000"
            $multiply: [6372.8, 1000, 2, { $asin: { $sqrt: "$distance" } }]
         }
      }
   },
])

请注意，$box仅用于Legacy Coordinate Pairs。对于正确的查询（即正确使用2dsphere索引），您应该使用$geometry：

db.collection.createIndex({ location: "2dsphere" })
db.collection.find(
   {
      "location": {
         "$geoWithin": {
            "$geometry": {
               type: "Polygon",
               coordinates: [[
                  [-0.1589577534542408, 51.47239969138267],
                  [-0.1589577534542408, 51.54643953472475],
                  [0.024719919885622943, 51.54643953472475],
                  [0.024719919885622943, 51.47239969138267],
                  [-0.1589577534542408, 51.47239969138267]
               ]]
            }
         }
      }
   }
).explain().queryPlanner.winningPlan.inputStage.indexName

--> location_2dsphere // which means index is used


db.collection.find(
   {
      "location": {
         "$geoWithin": {
            "$box": [
               [0.024719919885622943, 51.54643953472475],
               [-0.1589577534542408, 51.47239969138267]
            ]
         }
      }
   }
).explain().queryPlanner.winningPlan.stage

--> COLLSCAN // which means full collection scan

或正确使用旧坐标：

db.collection.createIndex({ "location.coordinates": "2d" })
db.collection.find(
   {
      "location.coordinates": { // <- note this difference
         "$geoWithin": {
            "$box": [
               [0.024719919885622943, 51.54643953472475],
               [-0.1589577534542408, 51.47239969138267]
            ]
         }
      }
   }
).explain().queryPlanner.winningPlan.inputStage.indexName

--> location.coordinates_2d
于 2020-02-27T13:42:46.260 回答