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geoWithin 演算子

geoWithin

geoWithin演算子は、指定された形状内の地理的ポイントのクエリをサポートしています。 インデックス定義indexShapesの値がtrueであっても、ポイントのみが返されます。

以下内のポイントをクエリできます。

  • 境界ボックス

  • 多角形

検索する座標を指定する場合は、最初に 経度 、次に 緯度 を指定する必要があります。 経度の値は、両方を含む-180180の間で指定できます。 緯度の値は-9090の間で指定できます。 座標値は整数または double にすることができます。

注意

Atlas Search は以下の機能をサポートしていません。

  • 非デフォルトの座標参照システム(CRS)

  • 平面 XY 座標系 (2 次元)

  • 座標ペアのポイント表記(つまりpointFieldName: [12, 34]

geoWithin の構文は次のとおりです。

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

geoWithin では、次の用語を使用してクエリを作成します。

フィールド
タイプ
説明
必要性

box

オブジェクト

検索するボックスの左下と右上の GeoJSONポイントを指定するオブジェクト。 オブジェクトは次のフィールドを取ります。

GeoJSON オブジェクト内で GeoJSON データを指定する方法については、「 GeoJSON オブジェクト 」を参照してください。

boxcircle 、またはgeometryのいずれかが必要です。

条件付き

circle

オブジェクト

検索する中心点と半径をメートル単位で指定するオブジェクト。 オブジェクトには、次のGeoJSONフィールドが含まれています。

GeoJSON オブジェクト内で GeoJSON データを指定する方法については、「 GeoJSON オブジェクト 」を参照してください。

circlebox 、またはgeometryのいずれかが必要です。

条件付き

geometry

GeoJSON オブジェクト

検索対象の Multi ポリゴンまたは 多角形 を指定する GeoJSON オブジェクト。多角形は最後の位置が最初の位置と同じである閉じたループとして指定する必要があります。

地理空間結果を計算する場合、Atlas Search geoShape 演算子と geoWithin 演算子、およびMongoDB $geoIntersects 演算子は異なるジオメトリを使用します。この違いは、Atlas Search とMongoDB が多角形エッジを描画する方法で確認できます。

Atlas Search は 直列距離 に基づいて多角形を描画します は、座標参照システム内の 2 点間の最短のラインです。

MongoDB は、 ジオメトリ タイプ のサードパーティ ライブラリ上に構築された2 dsphere インデックス 、または 平面モードに基づきジオデックスモードを使用して多角形を読み込み、2 d インデックス から収集します。詳細については、 「GeoJSON オブジェクト」 を参照してください。

Atlas Search と MongoDB では、多角形に関係する地理空間クエリで異なる結果が返される場合があります。

GeoJSON オブジェクト内で GeoJSON データを指定する方法については、「 GeoJSON オブジェクト 」を参照してください。

geometrybox 、またはcircleのいずれかが必要です。

条件付き

path

文字列または複数の文字列の配列

検索するインデックス付き geo 型フィールド。

はい

score

オブジェクト

一致する検索結果に割り当てる スコア 。 デフォルトでは、結果のスコア1です。 次のオプションを使用してスコアを変更できます。

  • boost: 結果のスコアに指定された数値を掛けます。

  • constant: 結果のスコアを指定された数値に置き換えます。

  • function: 結果のスコアを指定された式で置き換えます。

クエリで score を使用する方法については、「結果内のドキュメントのスコアリング」を参照してください。

no

次の例では、 sample_airbnbデータベース内のlistingsAndReviewsコレクションを使用します。 クラスターにサンプル データセットがある場合は、ジオタイプ用のカスタム Atlas Search インデックスを作成し、クラスターでサンプル クエリを実行できます。

次のサンプル インデックス定義を使用して、 listingsAndReviewsコレクションのaddress.locationフィールドにインデックスを作成します。

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": "token"
14 }
15 }
16 }
17}

次のクエリでは、 geoWithin演算子とboxフィールドを使用して、オーストラリアの境界ボックス内のプロパティを検索します。

クエリには以下が含まれます。

  • $limitステージを使用して、出力を3の結果に制限します。

  • $projectステージでは、 nameaddressを除くすべてのフィールドが除外されます。

注意

Atlas Search クエリにdefaultという名前のインデックスを指定する必要はありません。 インデックスに別の名前がある場合は、 indexフィールドを指定する必要があります。

次のクエリは、指定された検索条件に一致するドキュメントを返します。

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
}
}
}

次のクエリは、指定された検索条件に対するプロパティの種類(アパート、家など)の数を返します。

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') }
]
}
}
}
]

次のクエリでは、 geoWithin演算子とcircleフィールドを使用して、カナダ内の指定された座標の半径 1 マイル以内のプロパティを検索します。

クエリには以下が含まれます。

  • 出力を3の結果に制限する$limitステージ

  • $projectステージでは、 nameaddressを除くすべてのフィールドが除外されます。

注意

Atlas Search クエリにdefaultという名前のインデックスを指定する必要はありません。 インデックスに別の名前がある場合は、 indexフィールドを指定する必要があります。

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
}
}
}

次の例では、 geoWithin演算子とgeometryフィールドを使用して、クラウドのプロパティを検索しています。 typeフィールドは、領域が GeoJSON 多角形であるか、マルチポリゴンであるかを指定します。

クエリには、次のものが含まれます。

  • $limitステージを使用して、出力を3の結果に制限します。

  • $projectステージでは、 nameaddressを除くすべてのフィールドが除外されます。

注意

Atlas Search クエリにdefaultという名前のインデックスを指定する必要はありません。 インデックスに別の名前がある場合は、 indexフィールドを指定する必要があります。


➤ このページの [言語の選択] ドロップダウンメニューを使用して、このセクションの例の言語を設定します。


次の Atlas Search クエリは、

  • 複合$searchステージを使用して次の操作を行います。

    • 結果mustcoordinatesのセットで定義されたPolygon内にあることを指定します。

    • タイプcondominiumのプロパティの結果を優先します。

  • $projectステージを使用して次の操作を行います。

    • すべてのフィールドを除外しますnameaddressproperty_typeを除く)。

    • 返された各ドキュメントに関連性scoreを追加します。

[
{
"$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" }
}
}
])
{
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
}
]

MongoDB Compass で次のクエリを実行する方法については、「クエリを定義する」を参照してください。

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}

次のコード例では、次を行います。

  • mongodb パッケージと依存関係をインポートします。

  • Atlas クラスターへの接続を確立します。

  • クエリに一致するドキュメントをAggregateFlowインスタンスから出力します。

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}}

次のコード例では、次を行います。

  • MongoDB の Node.js ドライバーであるmongodbをインポートします。

  • Atlas クラスターへの接続を確立するためのMongoClientクラスのインスタンスを作成します。

  • カーソルを反復処理して、クエリに一致するドキュメントを出力します。

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);

次のコード例では、次を行います。

  • pymongo、 MongoDBのPythonドライバー、および DNSシードリスト接続文字列を使用して pymongoAtlas に接続するために必要な dns モジュールをインポートします。

  • Atlas クラスターへの接続を確立するためのMongoClientクラスのインスタンスを作成します。

    • 複合$searchステージを使用して次の操作を行います。

      • 結果mustcoordinatesのセットで定義されたPolygon内にあることを指定します。

      • タイプcondominiumのプロパティの結果を優先します。

    • $projectステージを使用して次の操作を行います。

      • すべてのフィールドを除外しますnameaddressproperty_typeを除く)。

      • 返された各ドキュメントに関連性scoreを追加します。

  • カーソルを反復処理して、クエリに一致するドキュメントを出力します。

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
}

次の例では、 geoWithin演算子とgeometryフィールドを使用して、クラウドのプロパティを検索しています。 typeフィールドは、領域が GeoJSON 多角形であるか、マルチポリゴンであるかを指定します。

クエリには以下が含まれます。

  • $limitステージを使用して、出力を3の結果に制限します。

  • $projectステージでは、 nameaddressを除くすべてのフィールドが除外されます。

注意

Atlas Search クエリにdefaultという名前のインデックスを指定する必要はありません。 インデックスに別の名前がある場合は、 indexフィールドを指定する必要があります。

1db.listingsAndReviews.aggregate([
2 {
3 "$search": {
4 "geoWithin": {
5 "geometry": {
6 "type": "MultiPolygon",
7 "coordinates": [
8 [[[-157.8412413882,21.2882235819],
9 [-157.8607925468,21.2962046205],
10 [-157.8646640634,21.3077019651],
11 [-157.862776699,21.320776283],
12 [-157.8341758705,21.3133826738],
13 [-157.8349985678,21.3000822569],
14 [-157.8412413882,21.2882235819]]],
15 [[[-157.852898124,21.301208833],
16 [-157.8580050499,21.3050871833],
17 [-157.8587346108,21.3098050385],
18 [-157.8508811028,21.3119240258],
19 [-157.8454308541,21.30396767],
20 [-157.852898124,21.301208833]]]
21 ]
22 },
23 "path": "address.location"
24 }
25 }
26 },
27 {
28 $limit: 3
29 },
30 {
31 $project: {
32 "_id": 0,
33 "name": 1,
34 "address": 1
35 }
36 }
37])
{
"name" : "Heart of Honolulu, 2BD gem! Free Garage Parking!",
"address" : {
"street" : "Honolulu, HI, United States",
"suburb" : "Makiki/Lower Punchbowl/Tantalus",
"government_area" : "Primary Urban Center",
"market" : "Oahu",
"country" : "United States",
"country_code" : "US",
"location" : {
"type" : "Point",
"coordinates" : [ -157.84343, 21.30852 ],
"is_location_exact" : false
}
}
}
{
"name" : "Private Studio closed to town w/ compact parking",
"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" : [ -157.85228, 21.31184 ],
"is_location_exact" : true
}
}
}
{
"name" : "Comfortable Room (2) at Affordable Rates",
"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" : [ -157.83889, 21.29776 ],
"is_location_exact" : false
}
}
}

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geoShape

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