mongodb - Mongoose Geo Near Search - 如何在给定距离内排序？

Question

我正在使用 Mongoose 和带有 maxDistance 的近查询来过滤靠近给定 gps 位置的元素。但是，near 查询会覆盖其他排序。我想要的是在给定点的 maxDistance 内找到所有元素，然后按其他一些属性排序。
这是我目前正在做的一个例子:

架构:

mongoose.Schema({
    name: {
        type: String,
        required: true
    },
    score: {
        type: Number,
        required: true,
        default: 0
    },
    location: {
        type: {
            type: String,
            default: 'Point',
        },
        coordinates: {
            type: [Number]
        }
    },
    ....
});

询问:

model.find({
  "location.coordinates": {
    "$near": {
      "$maxDistance": 1000,
      "$geometry": {
        "type": "Point",
        "coordinates": [
          10,
          10
        ]
      }
    }
  }
}).sort('-score');

在 find 之后添加 .sort 在这里没有帮助，并且无论如何都会按接近的顺序返回项目。

Answer 1

在查找查询中，您需要使用 location而不是 location.coordinates .

router.get("/test", async (req, res) => {
  const lat = 59.9165591;
  const lng = 10.7881978;
  const maxDistanceInMeters = 1000;

  const result = await model
    .find({
      location: {
        $near: {
          $geometry: {
            type: "Point",
            coordinates: [lng, lat],
          },
          $maxDistance: maxDistanceInMeters,
        },
      },
    })
    .sort("-score");

  res.send(result);
});

要使 $near 工作，您需要相关集合上的 2dsphere 索引:

db.collection.createIndex( { "location" : "2dsphere" } )

在mongodb中 $near文档它说:

$near sorts documents by distance. If you also include a sort() for the query, sort() re-orders the matching documents, effectively overriding the sort operation already performed by $near. When using sort() with geospatial queries, consider using $geoWithin operator, which does not sort documents, instead of $near.

由于您对按距离排序不感兴趣，因此 Nic 指出使用 $near 是不必要的，最好使用 $geoWithin像这样:

router.get("/test", async (req, res) => {
  const lat = 59.9165591;
  const lng = 10.7881978;
  const distanceInKilometer = 1;
  const radius = distanceInKilometer / 6378.1;

  const result = await model
    .find({
      location: { $geoWithin: { $centerSphere: [[lng, lat], radius] } },
    })
    .sort("-score");

  res.send(result);
});

为了计算半径，我们将公里除以 6378.1，将英里除以 3963.2，如 here 所述.

因此，这将找到 1 公里半径内的位置。

示例文档:

[
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7741692,
                59.9262198
            ]
        },
        "score": 50,
        "_id": "5ea9d4391e468428c8e8f505",
        "name": "Name1"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7736078,
                59.9246991
            ]
        },
        "score": 70,
        "_id": "5ea9d45c1e468428c8e8f506",
        "name": "Name2"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7635027,
                59.9297932
            ]
        },
        "score": 30,
        "_id": "5ea9d47b1e468428c8e8f507",
        "name": "Name3"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7635027,
                59.9297932
            ]
        },
        "score": 40,
        "_id": "5ea9d4971e468428c8e8f508",
        "name": "Name4"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7768093,
                59.9287668
            ]
        },
        "score": 90,
        "_id": "5ea9d4bd1e468428c8e8f509",
        "name": "Name5"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.795769,
                59.9190384
            ]
        },
        "score": 60,
        "_id": "5ea9d4e71e468428c8e8f50a",
        "name": "Name6"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.1715157,
                59.741873
            ]
        },
        "score": 110,
        "_id": "5ea9d7d216bdf8336094aa92",
        "name": "Name7"
    }
]

输出:(1km以内，按分数降序排列)

[
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7768093,
                59.9287668
            ]
        },
        "score": 90,
        "_id": "5ea9d4bd1e468428c8e8f509",
        "name": "Name5"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7736078,
                59.9246991
            ]
        },
        "score": 70,
        "_id": "5ea9d45c1e468428c8e8f506",
        "name": "Name2"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.795769,
                59.9190384
            ]
        },
        "score": 60,
        "_id": "5ea9d4e71e468428c8e8f50a",
        "name": "Name6"
    },
    {
        "location": {
            "type": "Point",
            "coordinates": [
                10.7741692,
                59.9262198
            ]
        },
        "score": 50,
        "_id": "5ea9d4391e468428c8e8f505",
        "name": "Name1"
    }
]