Question

我正在尝试从嵌套的mongodb文档中找到最接近的编码。我不断收到的错误如下：

我已经尽力了。我试图添加索引2d，但该索引也不起作用。

var point = GeoJson.Point(GeoJson.Geographic(38.8086, -85.1792));
var locationQuery = new FilterDefinitionBuilder<Book>().NearSphere(tag => tag.CitiesInBook[-1].Location, point,
            5000); 
var query = collection.Find(locationQuery).Limit(10); 
var a =  query.ToList();

计划者返回错误

无法找到$ geoNear查询的索引。”

Answer 1

以下汇总查询适用于图书实体中的嵌入城市。需要注意的一点是，您应该使用正确的键名创建geo2dsphere索引，并在正确的结构中使用c＃类，以便驱动程序进行序列化/反序列化。

#!/bin/bash
currentDateTime=$(date +"%Y%m%d.%k%M")
fileName="Statements-$currentDateTime"
touch ~/MyStatements/$fileName
echo $currentDateTime
echo $fileName
history -a "~/MyStatements/$fileName"
history -a newFile.text

以上查询是由以下MongoDB.Entities代码生成的：

db.Book.aggregate({
    "$geoNear": {
        "near": {
            "type": "Point",
            "coordinates": [
                48.857908,
                2.295243
            ]
        },
        "distanceField": "SearchResult.DistanceKM",
        "spherical": true,
        "maxDistance": NumberInt("20000"),
        "includeLocs": "SearchResult.Location"
    }
})

Answer 2

这是使用MongoDB.Entities的解决方案。我使用的是书籍与城市之间的一对多关系，而不是将城市嵌入书籍实体中。

using MongoDB.Driver;
using MongoDB.Entities;

namespace StackOverflow
{
    public class Program
    {
        public class Book : Entity
        {
            public string Name { get; set; }
            public Many<City> Cities { get; set; }

            public Book() => this.InitOneToMany(() => Cities);
        }

        public class City : Entity
        {
            public string Name { get; set; }
            public Coordinates2D Location { get; set; }
            public double DistanceKM { get; set; }
        }

        static void Main(string[] args)
        {
            new DB("test");

            //create an index
            DB.Index<City>()
              .Key(c => c.Location, KeyType.Geo2DSphere)
              .Option(o => o.Background = false)
              .Create();

            var paris = new City
            {
                Name = "paris",
                Location = new Coordinates2D(48.8539241, 2.2913515)
            };
            paris.Save();

            var versailles = new City
            {
                Name = "versailles",
                Location = new Coordinates2D(48.796964, 2.137456)
            };
            versailles.Save();

            var poissy = new City
            {
                Name = "poissy",
                Location = new Coordinates2D(48.928860, 2.046889)
            };
            poissy.Save();

            var scifi = new Book { Name = "sci-fi" };
            scifi.Save();
            scifi.Cities.Add(paris);
            scifi.Cities.Add(versailles);
            scifi.Cities.Add(poissy);

            var horror = new Book { Name = "horror" };
            horror.Save();
            horror.Cities.Add(poissy);

            var eiffelTower = new Coordinates2D(48.857908, 2.295243);

            //find matching city IDs within 20kms of eiffel tower.
            var cities = DB.GeoNear<City>(
                            NearCoordinates: eiffelTower,
                            DistanceField: c => c.DistanceKM,
                            MaxDistance: 20000);

            //get books with matching cities
            var books = DB.Entity<Book>()
                          .Cities.ParentsFluent<Book>(cities)
                          .ToList();
        }
    }
}

以上程序向mongodb发出以下聚合查询：

第一个查询：

{
    "$geoNear": {
        "near": {
            "type": "Point",
            "coordinates": [
                48.857908,
                2.295243
            ]
        },
        "distanceField": "DistanceKM",
        "spherical": true,
        "maxDistance": NumberInt("20000")
    }
}, {
    "$lookup": {
        "from": "[Book~City(Cities)]",
        "localField": "_id",
        "foreignField": "ChildID",
        "as": "Results"
    }
}, {
    "$replaceRoot": {
        "newRoot": {
            "$arrayElemAt": [
                "$Results",
                NumberInt("0")
            ]
        }
    }
}, {
    "$lookup": {
        "from": "Book",
        "localField": "ParentID",
        "foreignField": "_id",
        "as": "Results"
    }
}, {
    "$replaceRoot": {
        "newRoot": {
            "$arrayElemAt": [
                "$Results",
                NumberInt("0")
            ]
        }
    }
}, {
    "$group": {
        "_id": "$_id",
        "doc": {
            "$first": "$$ROOT"
        }
    }
}, {
    "$replaceRoot": {
        "newRoot": "$doc"
    }
}

尝试使用mongodb的filter.near

2 个答案: