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geoWithin

在此页面上

  • 定义
  • 语法
  • 选项
  • 示例
  • box 例子
  • circle 例子
  • geometry 示例

定义

geoWithin

geoWithin 操作符支持查询给定几何图形内的地理点。即使 indexShapes 值在 索引定义中为 true，也仅返回点。

您可以在以下位置查询点：

  • 圆形

  • 边界框

  • 多边形

指定要搜索的坐标时，必须先指定经度，然后指定纬度。 经度值可以介于-180和180之间，两者均包括在内。 纬度值可以介于-90和90之间，两者均包括在内。 坐标值可以是整数或双精度值。

注意

Atlas Search 不支持以下内容：

  • 非默认坐标参考系 (CRS)

  • 平面 XY 坐标系（二维）

  • 坐标对 点表示法（即pointFieldName: [12, 34] ）

语法

geoWithin 通过以下语法实现：

{
  "$search": {
     "index": <index name>, // optional, defaults to "default"
     "geoWithin": {
        "path": "<field-to-search>",
        "box | circle | geometry": <object>,
        "score": <score-options>
     }
  }
}

选项

geoWithin 使用以下词条来构造查询：

字段
类型
说明
必要性

box

对象

指定搜索框左下角和右上角 GeoJSON 点的对象。该对象接受以下字段：

  • bottomLeft - GeoJSON 左下角点。

  • topRight - 右上角的 GeoJSON点。

要了解如何在 GeoJSON 对象中指定 GeoJSON 数据，请参阅GeoJSON 对象。

box 、 circle或geometry是必需的。

视条件而定

circle

对象

对象，用于指定Atlas Search的中心点和半径（以米为单位）。 该对象包含以下GeoJSON字段：

  • center - 指定为 GeoJSON 点的圆心。

  • radius - Radius（半径）是一个数字，以米为单位。 值必须大于或等于0 。

要了解如何在 GeoJSON 对象中指定 GeoJSON 数据，请参阅GeoJSON 对象。

circle 、 box或geometry是必需的。

视条件而定

geometry

GeoJSON 对象

GeoJSON对象，用于指定要在其中进行 的 MultiPolygon 或 Polygon Atlas Search。必须将多边形指定为闭环，其中最后一个位置与第一个位置相同。

计算地理空间结果时， Atlas Search geoShape 和 geoWithin 操作符以及MongoDB $geoIntersects操作符使用不同的几何图形。从Atlas Search和MongoDB绘制多边形边的方式可以看出这种差异。

Atlas Search 根据 笛卡尔距离 绘制多边形 ，这是坐标参考系中两点之间的最短直线。

MongoDB使用基于2 dsphere 索引的测地线模式绘制多边形，该索引构建在测地线类型第三方库之上，或者使用来自2 d 索引的平面模式绘制多边形。要学习；了解详情，请参阅GeoJSON对象。

对于涉及多边形的地理空间查询，Atlas Search 和 MongoDB 可能会返回不同的结果。

要了解如何在 GeoJSON 对象中指定 GeoJSON 数据，请参阅GeoJSON 对象。

geometry 、 box或circle是必需的。

视条件而定

path

字符串或字符串数组

要搜索的一个或多个索引地理类型字段。

是

score

对象

分配给匹配搜索结果的分数。 默认情况下，结果中的分数为1 。 您可以使用以下选项修改分数：

  • boost将生成的分数乘以给定数字。

  • constant将结果分数替换为给定数字。

  • function：使用给定的表达式替换结果分数。

有关在查询中使用 score 的信息，请参阅对结果中的文档进行评分。

no

示例

listingsAndReviewssample_airbnb以下示例使用数据库中的collection集合。如果集群上有样本数据集，则可以为地理类型创建自定义 Atlas Search 索引，并在集群上运行示例查询。

address.locationlistingsAndReviews使用以下示例索引定义为collection中的字段编制索引：

1{
2  "mappings": {
3    "fields": {
4      "address": {
5        "fields": {
6          "location": {
7            "type": "geo"
8          }
9        },
10        "type": "document"
11      },
12      "property_type": {
13        "type": "stringFacet"
14      }
15    }
16  }
17}

box 例子

以下查询使用geoWithin操作符和box字段在澳大利亚的边界框中搜索属性。

查询包括：

  • $limit 阶段将输出限制为 3 个结果。

  • $project 阶段排除 name 和 address 以外的所有字段。

注意

您无需在 Atlas Search 搜索查询中指定名为default的索引。如果索引有任何其他名称，则必须指定index字段。

基本示例

以下查询返回与指定搜索条件匹配的文档。

1db.listingsAndReviews.aggregate([
2  {
3    "$search": {
4      "geoWithin": {
5        "path": "address.location",
6        "box": {
7          "bottomLeft": {
8            "type": "Point",
9            "coordinates": [112.467, -55.050]
10          },
11          "topRight": {
12            "type": "Point",
13            "coordinates": [168.000, -9.133]
14          }
15        }
16      }
17    }
18  },
19  {
20    $limit: 3
21  },
22  {
23    $project: {
24      "_id": 0,
25      "name": 1,
26      "address": 1
27    }
28  }
29])
{
  "name" : "Surry Hills Studio - Your Perfect Base in Sydney",
  "address" : {
    "street" : "Surry Hills, NSW, Australia",
    "suburb" : "Darlinghurst",
    "government_area" : "Sydney",
    "market" : "Sydney",
    "country" : "Australia",
    "country_code" : "AU",
    "location" : {
      "type" : "Point",
      "coordinates" : [ 151.21554, -33.88029 ],
      "is_location_exact" : true
    }
  }
}
{
  "name" : "Sydney Hyde Park City Apartment (checkin from 6am)",
  "address" : {
    "street" : "Darlinghurst, NSW, Australia",
    "suburb" : "Darlinghurst",
    "government_area" : "Sydney",
    "market" : "Sydney",
    "country" : "Australia",
    "country_code" : "AU",
    "location" : {
      "type" : "Point",
      "coordinates" : [ 151.21346, -33.87603 ],
      "is_location_exact" : false
    }
  }
}
{
  "name" : "THE Place to See Sydney's FIREWORKS",
  "address" : {
    "street" : "Rozelle, NSW, Australia",
    "suburb" : "Lilyfield/Rozelle",
    "government_area" : "Leichhardt",
    "market" : "Sydney",
    "country" : "Australia",
    "country_code" : "AU",
    "location" : {
      "type" : "Point",
      "coordinates" : [ 151.17956, -33.86296 ],
      "is_location_exact" : true
    }
  }
}

元数据示例

以下查询返回指定搜索条件的属性类型（例如公寓、独立屋等）的数量。

1db.listingsAndReviews.aggregate([
2  {
3    "$searchMeta": {
4      "facet": {
5        "operator": {
6          "geoWithin": {
7              "path": "address.location",
8              "box": {
9                "bottomLeft": {
10                  "type": "Point",
11                  "coordinates": [112.467, -55.050]
12                },
13                "topRight": {
14                  "type": "Point",
15                  "coordinates": [168.000, -9.133]
16                }
17              }
18            }
19        },
20        "facets": {
21          "propertyTypeFacet": {
22            "type": "string",
23            "path": "property_type"
24          }
25        }
26      }
27    }
28  }
29])
[
  {
    count: { lowerBound: Long('610') },
    facet: {
      propertyTypeFacet: {
        buckets: [
          { _id: 'Apartment', count: Long('334') },
          { _id: 'House', count: Long('168') },
          { _id: 'Townhouse', count: Long('29') },
          { _id: 'Guest suite', count: Long('20') },
          { _id: 'Condominium', count: Long('11') },
          { _id: 'Cabin', count: Long('8') },
          { _id: 'Serviced apartment', count: Long('7') },
          { _id: 'Villa', count: Long('7') },
          { _id: 'Bungalow', count: Long('5') },
          { _id: 'Guesthouse', count: Long('5') }
        ]
      }
    }
  }
]

circle 例子

以下查询使用geoWithin操作符和circle字段搜索加拿大指定坐标一英里半径范围内的房产。

查询包括：

  • $limit 阶段将输出限制为 3 个结果。

  • $project 阶段排除 name 和 address 以外的所有字段。

注意

您无需在 Atlas Search 搜索查询中指定名为default的索引。如果索引有任何其他名称，则必须指定index字段。

1db.listingsAndReviews.aggregate([
2  {
3    "$search": {
4      "geoWithin": {
5        "circle": {
6          "center": {
7            "type": "Point",
8            "coordinates": [-73.54, 45.54]
9          },
10          "radius": 1600
11        },
12        "path": "address.location"
13      }
14    }
15  },
16  {
17    $limit: 3
18  },
19  {
20    $project: {
21      "_id": 0,
22      "name": 1,
23      "address": 1
24    }
25  }
26])
{
  "name" : "Ligne verte - à 15 min de métro du centre ville.",
  "address" : {
    "street" : "Montréal, Québec, Canada",
    "suburb" : "Hochelaga-Maisonneuve",
    "government_area" : "Mercier-Hochelaga-Maisonneuve",
    "market" : "Montreal",
    "country" : "Canada",
    "country_code" : "CA",
    "location" : {
      "type" : "Point",
      "coordinates" : [ -73.54949, 45.54548 ],
      "is_location_exact" : false
    }
  }
}
{
  "name" : "Belle chambre à côté Metro Papineau",
  "address" : {
    "street" : "Montréal, QC, Canada",
    "suburb" : "Gay Village",
    "government_area" : "Ville-Marie",
    "market" : "Montreal",
    "country" : "Canada",
    "country_code" : "CA",
    "location" : {
      "type" : "Point",
      "coordinates" : [ -73.54985, 45.52797 ],
      "is_location_exact" : false
    }
  }
}
{
  "name" : "L'IDÉAL, ( à 2 min du métro Pie-IX ).",
  "address" : {
    "street" : "Montréal, Québec, Canada",
    "suburb" : "Mercier-Hochelaga-Maisonneuve",
    "government_area" : "Mercier-Hochelaga-Maisonneuve",
    "market" : "Montreal",
    "country" : "Canada",
    "country_code" : "CA",
    "location" : {
      "type" : "Point",
      "coordinates" : [ -73.55208, 45.55157 ],
      "is_location_exact" : true
    }
  }
}

geometry 示例

以下示例使用 geoWithin 操作符和 geometry 字段搜索夏威夷州的房产。type 字段指定区域是 GeoJSON 多边形还是多边形集合。

查询包括：

  • $limit 阶段将输出限制为 3 个结果。

  • $project 阶段排除 name 和 address 以外的所有字段。

注意

您无需在 Atlas Search 搜索查询中指定名为default的索引。如果索引有任何其他名称，则必须指定index字段。

➤ 使用本页的“选择语言”下拉菜单设置本节示例的语言。

以下 Atlas Search 搜索查询：

  • 使用复合$search阶段可以：

    • 指定结果must Polygon位于由 集定义的coordinates 内。

    • 优先显示condominium类型属性的结果。

  • 使用 $project 阶段以：

    • 排除除name 、 address和property_type之外的所有字段。

    • 为每个返回的文档添加相关性score 。

[
    {
      "$search": {
        "index": "<INDEX-NAME>",
        "compound": {
          "must": [{
            "geoWithin": {
              "geometry": {
                "type": "Polygon",
                  "coordinates": [[[ -161.323242, 22.512557 ],
                      [ -152.446289, 22.065278 ],
                      [ -156.09375, 17.811456 ],
                      [ -161.323242, 22.512557 ]]]
              },
              "path": "address.location"
            }
          }],
          "should": [{
            "text": {
              "path": "property_type",
              "query": "Condominium"
            }
          }]
        }
      }
    }
]
1SCORE: 2.238388776779175  _id:  "1001265"
2listing_url: "https://www.airbnb.com/rooms/1001265"
3name: "Ocean View Waikiki Marina w/prkg"
4summary: "A short distance from Honolulu's billion dollar mall,
5and the same dis…"
6...
7property_type: "Condominium"
8...
9address: Object
10    street: "Honolulu, HI, United States"
11    suburb: "Oʻahu"
12    government_area: "Primary Urban Center"
13    market: "Oahu"
14    country: "United States"
15    country_code: "US"
16    location: Object
17    type: "Point"
18    coordinates: Array
19        0: -157.83919
20        1: 21.28634
21    is_location_exact: true
22...
23
24SCORE: 2.238388776779175  _id:  "10227000"
25listing_url: "https://www.airbnb.com/rooms/10227000"
26name: "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!"
27summary: "THIS IS A VERY SPACIOUS 1 BEDROOM FULL CONDO (SLEEPS 4) AT THE BEAUTIF…"
28...
29property_type: "Condominium"
30...
31address: Object
32    street: "Lahaina, HI, United States"
33    suburb: "Maui"
34    government_area: "Lahaina"
35    market: "Maui"
36    country: "United States"
37    country_code: "US"
38    location: Object
39    type: "Point"
40    coordinates: Array
41        0: -156.68012
42        1: 20.96996
43    is_location_exact: true
44...
45
46SCORE: 2.238388776779175  _id:  "10266175"
47listing_url: "https://www.airbnb.com/rooms/10266175"
48name: "Makaha Valley Paradise with OceanView"
49summary: "A beautiful and comfortable 1 Bedroom Air Conditioned Condo in Makaha …"
50...
51property_type: "Condominium"
52...
53address: Object
54    street: "Waianae, HI, United States"
55    suburb: "Leeward Side"
56    government_area: "Waianae"
57    market: "Oahu"
58    country: "United States"
59    country_code: "US"
60    location: Object
61    type: "Point"
62    coordinates: Array
63        0: -158.20291
64        1: 21.4818
65    is_location_exact: true
66...
67
68SCORE: 2.238388776779175  _id:  "1042446"
69listing_url: "https://www.airbnb.com/rooms/1042446"
70name: "March 2019 availability! Oceanview on Sugar Beach!"
71summary: ""
72...
73property_type: "Condominium"
74...
75address: Object
76    street: "Kihei, HI, United States"
77    suburb: "Maui"
78    government_area: "Kihei-Makena"
79    market: "Maui"
80    country: "United States"
81    country_code: "US"
82    location: Object
83    type: "Point"
84    coordinates: Array
85        0: -156.46881
86        1: 20.78621
87    is_location_exact: true
88...
89
90SCORE: 2.238388776779175  _id:  "10527243"
91listing_url: "https://www.airbnb.com/rooms/10527243"
92name: "Tropical Jungle Oasis"
93summary: "2 bedrooms, one with a queen sized bed, one with 2 single beds. 1 and …"
94...
95property_type: "Condominium"
96...
97address: Object
98    street: "Hilo, HI, United States"
99    suburb: "Island of Hawaiʻi"
100    government_area: "South Hilo"
101    market: "The Big Island"
102    country: "United States"
103    country_code: "US"
104    location: Object
105    type: "Point"
106    coordinates: Array
107        0: -155.09259
108        1: 19.73108
109    is_location_exact: true
110...
111
112SCORE: 2.238388776779175  _id:  "1104768"
113listing_url: "https://www.airbnb.com/rooms/1104768"
114name: "2 Bdrm/2 Bath  Family Suite Ocean View"
115summary: "This breathtaking 180 degree view of Waikiki is one of a kind. You wil…"
116...
117property_type: "Condominium"
118...
119address: Object
120    street: "Honolulu, HI, United States"
121    suburb: "Waikiki"
122    government_area: "Primary Urban Center"
123    market: "Oahu"
124    country: "United States"
125    country_code: "US"
126    location: Object
127    type: "Point"
128    coordinates: Array
129        0: -157.82696
130        1: 21.27971
131    is_location_exact: true
132...
133
134SCORE: 2.238388776779175  _id:  "11207193"
135listing_url: "https://www.airbnb.com/rooms/11207193"
136name: "302 Kanai A Nalu Ocean front/view"
137summary: "Welcome to Kana'i A Nalu a quiet resort that sits on the ocean away fr…"
138...
139property_type: "Condominium"
140...
141address: Object
142    street: "Wailuku, HI, United States"
143    suburb: "Maui"
144    government_area: "Kihei-Makena"
145    market: "Maui"
146    country: "United States"
147    country_code: "US"
148    location: Object
149    type: "Point"
150    coordinates: Array
151        0: -156.5039
152        1: 20.79664
153    is_location_exact: true
154...
155
156SCORE: 2.238388776779175  _id:  "11319047"
157listing_url: "https://www.airbnb.com/rooms/11319047"
158name: "Sugar Beach Resort 1BR Ground Floor Condo !"
159summary: "The Sugar Beach Resort enjoys a beachfront setting fit for a postcard."
160...
161property_type: "Condominium"
162...
163address: Object
164    street: "Kihei, HI, United States"
165    suburb: "Maui"
166    government_area: "Kihei-Makena"
167    market: "Maui"
168    country: "United States"
169    country_code: "US"
170    location: Object
171    type: "Point"
172    coordinates: Array
173        0: -156.46697
174        1: 20.78484
175    is_location_exact: true
176...
177
178SCORE: 2.238388776779175  _id:  "11695887"
179listing_url: "https://www.airbnb.com/rooms/11695887"
180name: "2 BR Oceanview - Great Location!"
181summary: "Location, location, location... This is a great 2 bed, 2 bath condo is…"
182...
183property_type: "Condominium"
184...
185address: Object
186    street: "Kihei, HI, United States"
187    suburb: "Kihei/Wailea"
188    government_area: "Kihei-Makena"
189    market: "Maui"
190    country: "United States"
191    country_code: "US"
192    location: Object
193    type: "Point"
194    coordinates: Array
195        0: -156.44917
196        1: 20.73013
197    is_location_exact: true
198...
199
200SCORE: 2.238388776779175  _id:  "11817249"
201listing_url: "https://www.airbnb.com/rooms/11817249"
202name: "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC"
203summary: "Book with confidence this stunning 2 bedroom, 2 bathroom condo at the …"
204...
205property_type: "Condominium"
206...
207address: Object
208    street: "Kihei, HI, United States"
209    suburb: "Maui"
210    government_area: "Kihei-Makena"
211    market: "Maui"
212    country: "United States"
213    country_code: "US"
214    location: Object
215    type: "Point"
216    coordinates: Array
217        0: -156.4409
218        1: 20.69735
219    is_location_exact: true
220...
db.listingsAndReviews.aggregate([
    {
      "$search": {
        "index": "<INDEX-NAME>",
        "compound": {
          "must": [{
            "geoWithin": {
              "geometry": {
                "type": "Polygon",
                "coordinates": [[[ -161.323242, 22.512557 ],
                              [ -152.446289, 22.065278 ],
                              [ -156.09375, 17.811456 ],
                              [ -161.323242, 22.512557 ]]]
              },
              "path": "address.location"
            }
          }],
          "should": [{
            "text": {
              "path": "property_type",
              "query": "Condominium"
            }
          }]
        }
      }
    },
    {
      "$limit": 10
    },
    {
      $project: {
        "_id": 0,
        "name": 1,
        "address": 1,
        "property_type": 1,
        score: { $meta: "searchScore" }
      }
    }
])
<<<<<<<< HEAD:source/includes/fts/geo/procedures/steps-fts-tutorial-run-geo-query-compass.yaml
stepnum: 1
title: "Connect to your cluster in |compass|."
ref: connect-to-database-deployment-fts-compass
content: |
  Open |compass| and
  connect to your {+cluster+}. For detailed instructions on connecting,
  see :ref:`atlas-connect-via-compass`.
---
stepnum: 2
title: "Use the ``listingsAndReviews`` collection in the ``sample_airbnb`` database."
ref: use-sample-airbnb-compass
content: |
  On the :guilabel:`Database` screen, click the ``sample_airbnb``
  database, then click the ``listingsAndReviews`` collection.
---
stepnum: 3
title: "Run an |fts| query on the ``listingsAndReviews`` collection."
ref: run-geo-query-compass
content: |
  The following query:
  .. include:: /includes/fts/facts/fact-fts-tutorial-run-geo-query-results.rst
  To run this |fts| query in |compass|:
  a. Click the :guilabel:`Aggregations` tab.
  #. Click :guilabel:`Select...`, then configure each of the following 
     pipeline stages by selecting the stage from the dropdown and adding
     the query for that stage. Click :guilabel:`Add Stage` to add 
     additional stages.
     .. list-table::
        :header-rows: 1
        :widths: 25 75
        * - Pipeline Stage
          - Query
        * - ``$search``
          - .. code-block:: javascript
               {
                   'index': 'geo-json-tutorial',
                   'compound': {
                     'must': [
                       {
                         'geoWithin': {
                           'geometry': {
                             'type': 'Polygon', 
                             'coordinates': [
                               [
                                 [
                                   -161.323242, 22.512557
                                 ], [
                                   -152.446289, 22.065278
                                 ], [
                                   -156.09375, 17.811456
                                 ], [
                                   -161.323242, 22.512557
                                 ]
                               ]
                             ]
                           }, 
                           'path': 'address.location'
                         }
                       }
                     ], 
                     'should': [
                       {
                         'text': {
                           'path': 'property_type', 
                           'query': 'Condominium'
                         }
                       }
                     ]
                   }
               }
        * - ``$limit``
          - .. code-block:: javascript
               10
        * - ``$project``
          - .. code-block:: javascript
               {
                '_id': 0, 
                'name': 1, 
                'address': 1, 
                'property_type': 1, 
                'score': {
                  '$meta': 'searchScore'
                }
               }
  If you enabled :guilabel:`Auto Preview`, |compass| displays the 
  following documents next to the ``$project``
  pipeline stage:
  .. code-block:: json
     :copyable: false
     :linenos:
     {
========
[
    {
>>>>>>>> 44b896764 (DOCSP-47238 Performance Options reference section + tutorial example migration):source/includes/fts/geo/shell-query-output.js
       name: 'Ocean View Waikiki Marina w/prkg',
       property_type: 'Condominium',
       address: {
         street: 'Honolulu, HI, United States',
         suburb: 'Oʻahu',
         government_area: 'Primary Urban Center',
         market: 'Oahu',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -157.83919, 21.28634 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!',
       property_type: 'Condominium',
       address: {
         street: 'Lahaina, HI, United States',
         suburb: 'Maui',
         government_area: 'Lahaina',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.68012, 20.96996 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'Makaha Valley Paradise with OceanView',
       property_type: 'Condominium',
       address: {
         street: 'Waianae, HI, United States',
         suburb: 'Leeward Side',
         government_area: 'Waianae',
         market: 'Oahu',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -158.20291, 21.4818 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'March 2019 availability! Oceanview on Sugar Beach!',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.46881, 20.78621 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'Tropical Jungle Oasis',
       property_type: 'Condominium',
       address: {
         street: 'Hilo, HI, United States',
         suburb: 'Island of Hawaiʻi',
         government_area: 'South Hilo',
         market: 'The Big Island',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -155.09259, 19.73108 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: '2 Bdrm/2 Bath  Family Suite Ocean View',
       property_type: 'Condominium',
       address: {
         street: 'Honolulu, HI, United States',
         suburb: 'Waikiki',
         government_area: 'Primary Urban Center',
         market: 'Oahu',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -157.82696, 21.27971 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: '302 Kanai A Nalu Ocean front/view',
       property_type: 'Condominium',
       address: {
         street: 'Wailuku, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.5039, 20.79664 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'Sugar Beach Resort 1BR Ground Floor Condo !',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.46697, 20.78484 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: '2 BR Oceanview - Great Location!',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Kihei/Wailea',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.44917, 20.73013 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.4409, 20.69735 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
    }
]

要学习；了解如何在MongoDB Compass中运行以下查询，请参阅定义查询。

1using MongoDB.Bson;
2using MongoDB.Bson.IO;
3using MongoDB.Bson.Serialization;
4using MongoDB.Bson.Serialization.Attributes;
5using MongoDB.Bson.Serialization.Conventions;
6using MongoDB.Driver;
7using MongoDB.Driver.GeoJsonObjectModel;
8using MongoDB.Driver.Search;
9using System;
10
11public class GeoQuery 
12{
13    private const string MongoConnectionString = "<connection-string>";
14    
15    public static void Main(string[] args) 
16    {
17        // allow automapping of the camelCase database fields to our AirbnbDocument
18        var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };
19        ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);
20
21        // connect to your Atlas cluster
22        var mongoClient = new MongoClient(MongoConnectionString);
23        var airbnbDatabase = mongoClient.GetDatabase("sample_airbnb");
24        var airbnbCollection = airbnbDatabase.GetCollection<AirbnbDocument>("listingsAndReviews");
25
26        // declare data for the compound query
27        string property_type = "Condominium";
28        var coordinates = new GeoJson2DCoordinates[]
29        {
30          new(-161.323242, 22.512557),
31          new(-152.446289, 22.065278),
32          new(-156.09375, 17.811456),
33          new(-161.323242, 22.512557)
34        };
35        var polygon = GeoJson.Polygon(coordinates);
36
37        // define and run pipeline
38        var results = airbnbCollection.Aggregate()
39            .Search(Builders<AirbnbDocument>.Search.Compound()
40                .Must(Builders<AirbnbDocument>.Search.GeoWithin(airbnb => airbnb.Address.Location, polygon))
41                .Should((Builders<AirbnbDocument>.Search.Text(airbnb => airbnb.PropertyType, property_type))),
42                indexName: "<INDEX-NAME>")
43            .Limit (10)
44            .Project<AirbnbDocument>(Builders<AirbnbDocument>.Projection
45                .Include(airbnb => airbnb.PropertyType)
46                .Include(airbnb => airbnb.Address.Location)
47                .Include(airbnb => airbnb.Name)
48                .Exclude(airbnb => airbnb.Id)
49                .MetaSearchScore(airbnb => airbnb.Score))
50            .ToList();
51
52        // print results
53        foreach (var x in results) {
54            Console.WriteLine(x.ToJson());
55        }
56    }
57}
58[BsonIgnoreExtraElements]
59public class AirbnbDocument 
60{
61    [BsonIgnoreIfDefault]
62    public ObjectId Id { get; set; }
63    public String Name { get; set; }
64    [BsonElement("property_type")] 
65    public string PropertyType { get; set; }
66    public Address Address { get; set; }
67    public double Score { get; set; }
68}
69[BsonIgnoreExtraElements]
70public class Address 
71{
72    public GeoJsonPoint<GeoJson2DCoordinates> Location { get; set; }
73}
{ 
    "name" : "Ocean View Waikiki Marina w/prkg", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-157.83919, 21.286339999999999],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point", 
        "coordinates" : [-156.68011999999999, 20.96996], 
        "is_location_exact" : true 
      }
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "Makaha Valley Paradise with OceanView",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-158.20291, 21.4818],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "March 2019 availability! Oceanview on Sugar Beach!",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-156.46880999999999, 20.786210000000001], 
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "Tropical Jungle Oasis", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-155.09259, 19.731079999999999],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "2 Bdrm/2 Bath  Family Suite Ocean View",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-157.82696000000001, 21.279710000000001], 
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "302 Kanai A Nalu Ocean front/view", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-156.50389999999999, 20.79664],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "Sugar Beach Resort 1BR Ground Floor Condo !",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-156.46697, 20.784839999999999], 
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "2 BR Oceanview - Great Location!", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-156.44917000000001, 20.730129999999999],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-156.4409, 20.69735],
        "is_location_exact" : true 
      }
    }, 
    "score" : 2.2383887767791748  
}
1package main
2
3import (
4	"context"
5	"fmt"
6
7	"go.mongodb.org/mongo-driver/v2/bson"
8	"go.mongodb.org/mongo-driver/v2/mongo"
9	"go.mongodb.org/mongo-driver/v2/mongo/options"
10)
11
12func main() {
13	// connect to your Atlas cluster
14	client, err := mongo.Connect(options.Client().ApplyURI("<connection-string>"))
15	if err != nil {
16		panic(err)
17	}
18	defer client.Disconnect(context.TODO())
19
20	// set namespace
21	collection := client.Database("sample_airbnb").Collection("listingsAndReviews")
22
23	// define polygon
24	polygon := [][][]float64{{
25		{-161.323242, 22.512557},
26		{-152.446289, 22.065278},
27		{-156.09375, 17.811456},
28		{-161.323242, 22.512557},
29	}}
30
31	// define pipeline
32	searchStage := bson.D{{"$search", bson.M{
33		"index": "<INDEX-NAME>",
34		"compound": bson.M{
35			"must": bson.M{
36				"geoWithin": bson.M{
37					"geometry": bson.M{
38						"type":        "Polygon",
39						"coordinates": polygon,
40					},
41					"path": "address.location",
42				},
43			},
44			"should": bson.M{
45				"text": bson.M{
46					"path":  "property_type",
47					"query": "Condominium",
48				}},
49		},
50	},
51	}}
52	limitStage := bson.D{{"$limit", 10}}
53	projectStage := bson.D{{"$project", bson.D{{"name", 1}, {"address", 1}, {"property_type", 1}, {"_id", 0}, {"score", bson.D{{"$meta", "searchScore"}}}}}}
54
55	// run pipeline
56	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage})
57	if err != nil {
58		panic(err)
59	}
60
61	// print results
62	var results []bson.D
63	if err = cursor.All(context.TODO(), &results); err != nil {
64		panic(err)
65	}
66	for _, result := range results {
67		fmt.Println(result)
68	}
69}
package main
import (
	"context"
	"fmt"
	"go.mongodb.org/mongo-driver/v2/bson"
	"go.mongodb.org/mongo-driver/v2/mongo"
	"go.mongodb.org/mongo-driver/v2/mongo/options"
)
func main() {
	// connect to your Atlas cluster
	client, err := mongo.Connect(options.Client().ApplyURI("<connection-string>"))
	if err != nil {
		panic(err)
	}
	defer client.Disconnect(context.TODO())
	// set namespace
	collection := client.Database("sample_airbnb").Collection("listingsAndReviews")
	// define polygon
	polygon := [][][]float64{{
		{-161.323242, 22.512557},
		{-152.446289, 22.065278},
		{-156.09375, 17.811456},
		{-161.323242, 22.512557},
	}}
	// define pipeline
	searchStage := bson.D{{"$search", bson.M{
		"index": "<INDEX-NAME>",
		"compound": bson.M{
			"must": bson.M{
				"geoWithin": bson.M{
					"geometry": bson.M{
						"type":        "Polygon",
						"coordinates": polygon,
					},
					"path": "address.location",
				},
			},
			"should": bson.M{
				"text": bson.M{
					"path":  "property_type",
					"query": "Condominium",
				}},
		},
	},
	}}
	limitStage := bson.D{{"$limit", 10}}
	projectStage := bson.D{{"$project", bson.D{{"name", 1}, {"address", 1}, {"property_type", 1}, {"_id", 0}, {"score", bson.D{{"$meta", "searchScore"}}}}}}
	// run pipeline
	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage})
	if err != nil {
		panic(err)
	}
	// print results
	var results []bson.D
	if err = cursor.All(context.TODO(), &results); err != nil {
		panic(err)
	}
	for _, result := range results {
		fmt.Println(result)
	}
}
1import java.util.Arrays;
2import static com.mongodb.client.model.Filters.eq;
3import static com.mongodb.client.model.Aggregates.limit;
4import static com.mongodb.client.model.Aggregates.project;
5import static com.mongodb.client.model.Projections.computed;
6import static com.mongodb.client.model.Projections.excludeId;
7import static com.mongodb.client.model.Projections.fields;
8import static com.mongodb.client.model.Projections.include;
9import com.mongodb.client.MongoClient;
10import com.mongodb.client.MongoClients;
11import com.mongodb.client.MongoCollection;
12import com.mongodb.client.MongoDatabase;
13import org.bson.Document;
14
15public class GeoQuery {
16        public static void main( String[] args ) {
17                Document agg = new Document( "$search",
18                new Document( "index", "<INDEX-NAME>")
19                .append("compound",
20                    new Document("must", Arrays.asList(new Document("geoWithin", 
21                    new Document("geometry", 
22                        new Document("type", "Polygon")
23                            .append("coordinates", Arrays.asList(Arrays.asList(Arrays.asList(-161.323242d, 22.512557d), Arrays.asList(-152.446289d, 22.065278d), Arrays.asList(-156.09375d, 17.811456d), Arrays.asList(-161.323242d, 22.512557d)))))
24                            .append("path", "address.location"))))
25                .append("should", Arrays.asList(new Document("text", 
26                    new Document("path", "property_type")
27                        .append("query", "Condominium"))))));
28        
29                String uri = "<connection-string>";
30
31                try (MongoClient mongoClient = MongoClients.create(uri)) {
32                        MongoDatabase database = mongoClient.getDatabase("sample_airbnb");
33                        MongoCollection<Document> collection = database.getCollection("listingsAndReviews");
34                                        
35                        collection.aggregate(Arrays.asList(agg, 
36                            limit(10), 
37                            project(fields(excludeId(), include("name", "address", "property_type"), computed("score", new Document("$meta", "searchScore"))))))
38                            .forEach(doc -> System.out.println(doc.toJson() + "\n"));    
39                }
40        }
41}

以下代码示例：

  • 导入mongodb包和依赖项。

  • 建立与您的 Atlas 集群的连接。

  • 打印与 AggregateFlow 实例中的查询相匹配的文档。

1import com.mongodb.client.model.Aggregates.limit
2import com.mongodb.client.model.Aggregates.project
3import com.mongodb.client.model.Projections.*
4import com.mongodb.kotlin.client.coroutine.MongoClient
5import kotlinx.coroutines.runBlocking
6import org.bson.Document
7
8fun main() {
9    // connect to your Atlas cluster
10    val uri = "<connection-string>"
11    val mongoClient = MongoClient.create(uri)
12
13    // set namespace
14    val database = mongoClient.getDatabase("sample_airbnb")
15    val collection = database.getCollection<Document>("listingsAndReviews")
16
17    runBlocking {
18        // define pipeline
19        val agg = Document(
20            "\$search",
21            Document("index", "<INDEX-NAME>")
22                .append(
23                    "compound",
24                    Document(
25                        "must", listOf(
26                            Document(
27                                "geoWithin",
28                                Document(
29                                    "geometry",
30                                    Document("type", "Polygon")
31                                        .append(
32                                            "coordinates",
33                                            listOf(
34                                                listOf(
35                                                    listOf(-161.323242, 22.512557),
36                                                    listOf(-152.446289, 22.065278),
37                                                    listOf(-156.09375, 17.811456),
38                                                    listOf(-161.323242, 22.512557)
39                                                )
40                                            )
41                                        )
42                                )
43                                    .append("path", "address.location")
44                            )
45                        )
46                    )
47                        .append(
48                            "should", listOf(
49                                Document(
50                                    "text",
51                                    Document("path", "property_type")
52                                        .append("query", "Condominium")
53                                )
54                            )
55                        )
56                )
57        )
58        
59        // run pipeline and print results
60        val resultsFlow = collection.aggregate<Document>(
61            listOf(
62                agg,
63                limit(10),
64                project(fields(
65                    excludeId(),
66                    include("name", "address", "property_type"),
67                    computed("score", Document("\$meta", "searchScore"))
68                ))
69            )
70        )
71        resultsFlow.collect { println(it) }
72    }
73    mongoClient.close()
74}
Document{{name=Ocean View Waikiki Marina w/prkg, property_type=Condominium, address=Document{{street=Honolulu, HI, United States, suburb=Oʻahu, government_area=Primary Urban Center, market=Oahu, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-157.83919, 21.28634], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!, property_type=Condominium, address=Document{{street=Lahaina, HI, United States, suburb=Maui, government_area=Lahaina, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.68012, 20.96996], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=Makaha Valley Paradise with OceanView, property_type=Condominium, address=Document{{street=Waianae, HI, United States, suburb=Leeward Side, government_area=Waianae, market=Oahu, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-158.20291, 21.4818], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=March 2019 availability! Oceanview on Sugar Beach!, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.46881, 20.78621], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=Tropical Jungle Oasis, property_type=Condominium, address=Document{{street=Hilo, HI, United States, suburb=Island of Hawaiʻi, government_area=South Hilo, market=The Big Island, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-155.09259, 19.73108], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=2 Bdrm/2 Bath  Family Suite Ocean View, property_type=Condominium, address=Document{{street=Honolulu, HI, United States, suburb=Waikiki, government_area=Primary Urban Center, market=Oahu, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-157.82696, 21.27971], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=302 Kanai A Nalu Ocean front/view, property_type=Condominium, address=Document{{street=Wailuku, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.5039, 20.79664], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=Sugar Beach Resort 1BR Ground Floor Condo !, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.46697, 20.78484], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=2 BR Oceanview - Great Location!, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Kihei/Wailea, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.44917, 20.73013], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.4409, 20.69735], is_location_exact=true}}}}, score=2.238388776779175}}

以下代码示例：

  • 导入 mongodb，即 MongoDB 的 Node.js 驱动程序。

  • 创建一个 MongoClient 类实例，以建立与 Atlas 集群的连接。

  • 遍历游标以打印与查询匹配的文档。

1const { MongoClient } = require("mongodb");
2
3// connect to your Atlas cluster
4const uri ="<connection-string>";
5
6const client = new MongoClient(uri);
7
8async function run() {
9    try {
10        await client.connect();
11
12        // set namespace
13        const database = client.db("sample_airbnb");
14        const coll = database.collection("listingsAndReviews");
15
16        // define pipeline
17        const agg = [
18            {
19              '$search': {
20                'index': '<INDEX-NAME>',
21                'compound': {
22                  'must': [
23                    {
24                      'geoWithin': {
25                        'geometry': {
26                          'type': 'Polygon', 
27                          'coordinates': [
28                            [
29                              [
30                                -161.323242, 22.512557
31                              ], [
32                                -152.446289, 22.065278
33                              ], [
34                                -156.09375, 17.811456
35                              ], [
36                                -161.323242, 22.512557
37                              ]
38                            ]
39                          ]
40                        }, 
41                        'path': 'address.location'
42                      }
43                    }
44                  ], 
45                  'should': [
46                    {
47                      'text': {
48                        'path': 'property_type', 
49                        'query': 'Condominium'
50                      }
51                    }
52                  ]
53                }
54              }
55            }, {
56              '$limit': 10
57            }, {
58              '$project': {
59                '_id': 0, 
60                'name': 1, 
61                'address': 1, 
62                'property_type': 1, 
63                'score': {
64                  '$meta': 'searchScore'
65                }
66              }
67            }
68          ];
69        // run pipeline
70        const result = await coll.aggregate(agg);
71
72        // print results
73        await result.forEach((doc) => console.log(doc));
74    } finally {
75        await client.close();
76    }
77}
78run().catch(console.dir);

以下代码示例：

  • 导入 pymongo 、MongoDB 的 Python 驱动程序和 dns 模块，这是使用 DNS 种子列表连接字符串将pymongo 连接到Atlas 所必需的。

  • 创建一个 MongoClient 类实例，以建立与 Atlas 集群的连接。

    • 使用复合$search阶段可以：

      • 指定结果must Polygon位于由 集定义的coordinates 内。

      • 优先显示condominium类型属性的结果。

    • 使用 $project 阶段以：

      • 排除除name 、 address和property_type之外的所有字段。

      • 为每个返回的文档添加相关性score 。

  • 遍历游标以打印与查询匹配的文档。

1import pymongo
2
3# connect to your Atlas cluster
4client = pymongo.MongoClient('<connection-string>')
5
6# define pipeline
7pipeline = [
8    {
9        '$search': {
10            'index': '<INDEX-NAME>',
11            'compound': {
12                'must': [
13                    {
14                        'geoWithin': {
15                            'geometry': {
16                                'type': 'Polygon', 
17                                'coordinates': [
18                                    [
19                                        [
20                                            -161.323242, 22.512557
21                                        ], [
22                                            -152.446289, 22.065278
23                                        ], [
24                                            -156.09375, 17.811456
25                                        ], [
26                                            -161.323242, 22.512557
27                                        ]
28                                    ]
29                                ]
30                            }, 
31                            'path': 'address.location'
32                        }
33                    }
34                ], 
35                'should': [
36                    {
37                        'text': {
38                            'path': 'property_type', 
39                            'query': 'Condominium'
40                        }
41                    }
42                ]
43            }
44        }
45    }, {
46        '$limit': 10
47    }, {
48        '$project': {
49            '_id': 0, 
50            'name': 1, 
51            'address': 1, 
52            'property_type': 1, 
53            'score': {
54                '$meta': 'searchScore'
55            }
56        }
57    }
58]
59# run pipeline
60result = client["sample_airbnb"]["listingsAndReviews"].aggregate(pipeline)
61
62# print results
63for i in result:
64    print(i)
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Primary Urban Center",
        "location": {
            "coordinates": [
                -157.83919,
                21.28634
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Oahu",
        "street": "Honolulu, HI, United States",
        "suburb": "O\u02bbahu"
    },
    "name": "Ocean View Waikiki Marina w/prkg",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Lahaina",
        "location": {
            "coordinates": [
                -156.68012,
                20.96996
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Lahaina, HI, United States",
        "suburb": "Maui"
    },
    "name": "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Waianae",
        "location": {
            "coordinates": [
                -158.20291,
                21.4818
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Oahu",
        "street": "Waianae, HI, United States",
        "suburb": "Leeward Side"
    },
    "name": "Makaha Valley Paradise with OceanView",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.46881,
                20.78621
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Maui"
    },
    "name": "March 2019 availability! Oceanview on Sugar Beach!",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "South Hilo",
        "location": {
            "coordinates": [
                -155.09259,
                19.73108
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "The Big Island",
        "street": "Hilo, HI, United States",
        "suburb": "Island of Hawai\u02bbi"
    },
    "name": "Tropical Jungle Oasis",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Primary Urban Center",
        "location": {
            "coordinates": [
                -157.82696,
                21.27971
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Oahu",
        "street": "Honolulu, HI, United States",
        "suburb": "Waikiki"
    },
    "name": "2 Bdrm/2 Bath  Family Suite Ocean View",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.5039,
                20.79664
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Wailuku, HI, United States",
        "suburb": "Maui"
    },
    "name": "302 Kanai A Nalu Ocean front/view",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.46697,
                20.78484
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Maui"
    },
    "name": "Sugar Beach Resort 1BR Ground Floor Condo !",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.44917,
                20.73013
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Kihei/Wailea"
    },
    "name": "2 BR Oceanview - Great Location!",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.4409,
                20.69735
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Maui"
    },
    "name": "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC",
    "property_type": "Condominium",
    "score": 2.238388776779175
}

以下示例使用 geoWithin 操作符和 geometry 字段搜索夏威夷州的房产。type 字段指定区域是 GeoJSON 多边形还是多边形集合。

查询包括：

  • $limit 阶段将输出限制为 3 个结果。

  • $project 阶段排除 name 和 address 以外的所有字段。

注意

您无需在 Atlas Search 搜索查询中指定名为default的索引。如果索引有任何其他名称，则必须指定index字段。

1.. input::
2   :language: json
3   :linenos:
4
5   db.listingsAndReviews.aggregate([
6     {
7       "$search": {
8         "geoWithin": {
9           "geometry": {
10             "type": "MultiPolygon",
11             "coordinates": [
12                   [[[-157.8412413882,21.2882235819],
13                   [-157.8607925468,21.2962046205],
14                   [-157.8646640634,21.3077019651],
15                   [-157.862776699,21.320776283],
16                   [-157.8341758705,21.3133826738],
17                   [-157.8349985678,21.3000822569],
18                   [-157.8412413882,21.2882235819]]],
19                   [[[-157.852898124,21.301208833],
20                   [-157.8580050499,21.3050871833],
21                   [-157.8587346108,21.3098050385],
22                   [-157.8508811028,21.3119240258],
23                   [-157.8454308541,21.30396767],
24                   [-157.852898124,21.301208833]]]
25             ]
26           },
27           "path": "address.location"
28         }
29       }
30     },
31     {
32       $limit: 3
33     },
34     {
35       $project: {
36         "_id": 0,
37         "name": 1,
38         "address": 1
39       }
40     }
41   ])
42
43.. output::
44   :language: javascript
45   :visible: false
46
47   {
48       "name" : "Heart of Honolulu, 2BD gem! Free Garage Parking!",
49       "address" : {
50         "street" : "Honolulu, HI, United States",
51         "suburb" : "Makiki/Lower Punchbowl/Tantalus",
52         "government_area" : "Primary Urban Center",
53         "market" : "Oahu",
54         "country" : "United States",
55         "country_code" : "US",
56         "location" : {
57           "type" : "Point",
58           "coordinates" : [ -157.84343, 21.30852 ],
59           "is_location_exact" : false
60         }
61       }
62     }
63     {
64       "name" : "Private Studio closed to town w/ compact parking",
65       "address" : {
66         "street" : "Honolulu, HI, United States",
67         "suburb" : "Oʻahu",
68         "government_area" : "Primary Urban Center",
69         "market" : "Oahu",
70         "country" : "United States",
71         "country_code" : "US",
72         "location" : {
73           "type" : "Point",
74           "coordinates" : [ -157.85228, 21.31184 ],
75           "is_location_exact" : true
76         }
77       }
78     }
79     {
80       "name" : "Comfortable Room (2) at Affordable Rates",
81       "address" : {
82         "street" : "Honolulu, HI, United States",
83         "suburb" : "Oʻahu",
84         "government_area" : "Primary Urban Center",
85         "market" : "Oahu",
86         "country" : "United States",
87         "country_code" : "US",
88         "location" : {
89           "type" : "Point",
90           "coordinates" : [ -157.83889, 21.29776 ],
91           "is_location_exact" : false
92         }
93       }
94     }

后退

geoShape

来年

in