定義
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。 インデックス定義で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。
円
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
-180
と180
の間で指定できます。 緯度の値は-90
と90
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]
)
構文
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> } } }
オプション
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 |
---|---|---|---|
| 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。
| 条件付き |
| 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。
| 条件付き |
| 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 $geoIntersects 演算子は異なるジオメトリを使用します。この違いは、Atlas Search とMongoDB が多角形エッジを描画する方法で確認できます。 Atlas Search は 直列距離 に基づいて多角形を描画します は、座標参照システム内の 2 点間の最短のラインです。 MongoDB は、 ジオメトリ タイプ のサードパーティ ライブラリ上に構築された2 dsphere インデックス 、または 平面モードに基づきジオデックスモードを使用して多角形を読み込み、2 d インデックス から収集します。詳細については、 「GeoJSON オブジェクト」 を参照してください。 Atlas Search と MongoDB では、多角形に関係する地理空間クエリで異なる結果が返される場合があります。 GeoJSON オブジェクト内で GeoJSON データを指定する方法については、「 GeoJSON オブジェクト 」を参照してください。
| 条件付き |
| 文字列または複数の文字列の配列 | 検索するインデックス付き geo 型フィールド。 | はい |
| オブジェクト | 一致する検索結果に割り当てる スコア 。 デフォルトでは、結果のスコアは
クエリで | no |
例
次の例では、 sample_airbnb
データベース内のlistingsAndReviews
コレクションを使用します。 クラスターにサンプル データセットがある場合は、ジオタイプ用のカスタム Atlas Search インデックスを作成し、クラスターでサンプル クエリを実行できます。
次のサンプル インデックス定義を使用して、 listingsAndReviews
コレクションのaddress.location
フィールドにインデックスを作成します。
1 { 2 "mappings": { 3 "fields": { 4 "address": { 5 "fields": { 6 "location": { 7 "type": "geo" 8 } 9 }, 10 "type": "document" 11 }, 12 "property_type": { 13 "type": "token" 14 } 15 } 16 } 17 }
box
例
次のクエリでは、 geoWithin
演算子とbox
フィールドを使用して、オーストラリアの境界ボックス内のプロパティを検索します。
クエリには以下が含まれます。
注意
Atlas Search クエリにdefault
という名前のインデックスを指定する必要はありません。 インデックスに別の名前がある場合は、 index
フィールドを指定する必要があります。
基本的な例
次のクエリは、指定された検索条件に一致するドキュメントを返します。
1 db.listingsAndReviews.aggregate([ 2 { 3 "$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 $project: { 24 "_id": 0, 25 "name": 1, 26 "address": 1 27 } 28 } 29 ])
{ "name" : "Surry Hills Studio - Your Perfect Base in Sydney", "address" : { "street" : "Surry Hills, NSW, Australia", "suburb" : "Darlinghurst", "government_area" : "Sydney", "market" : "Sydney", "country" : "Australia", "country_code" : "AU", "location" : { "type" : "Point", "coordinates" : [ 151.21554, -33.88029 ], "is_location_exact" : true } } } { "name" : "Sydney Hyde Park City Apartment (checkin from 6am)", "address" : { "street" : "Darlinghurst, NSW, Australia", "suburb" : "Darlinghurst", "government_area" : "Sydney", "market" : "Sydney", "country" : "Australia", "country_code" : "AU", "location" : { "type" : "Point", "coordinates" : [ 151.21346, -33.87603 ], "is_location_exact" : false } } } { "name" : "THE Place to See Sydney's FIREWORKS", "address" : { "street" : "Rozelle, NSW, Australia", "suburb" : "Lilyfield/Rozelle", "government_area" : "Leichhardt", "market" : "Sydney", "country" : "Australia", "country_code" : "AU", "location" : { "type" : "Point", "coordinates" : [ 151.17956, -33.86296 ], "is_location_exact" : true } } }
メタデータの例
次のクエリは、指定された検索条件に対するプロパティの種類(アパート、家など)の数を返します。
1 db.listingsAndReviews.aggregate([ 2 { 3 "$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
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。
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。
1 db.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
例
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。
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
must
がcoordinates
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。
$project
ステージを使用して次の操作を行います。すべてのフィールドを除外します
name
、address
、property_type
を除く)。返された各ドキュメントに関連性
score
を追加します。
[ { "$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" } }] } } } ]
1 SCORE: 2.238388776779175 _id: "1001265" 2 listing_url: "https://www.airbnb.com/rooms/1001265" 3 name: "Ocean View Waikiki Marina w/prkg" 4 summary: "A short distance from Honolulu's billion dollar mall, 5 and the same dis…" 6 ... 7 property_type: "Condominium" 8 ... 9 address: 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 24 SCORE: 2.238388776779175 _id: "10227000" 25 listing_url: "https://www.airbnb.com/rooms/10227000" 26 name: "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!" 27 summary: "THIS IS A VERY SPACIOUS 1 BEDROOM FULL CONDO (SLEEPS 4) AT THE BEAUTIF…" 28 ... 29 property_type: "Condominium" 30 ... 31 address: 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 46 SCORE: 2.238388776779175 _id: "10266175" 47 listing_url: "https://www.airbnb.com/rooms/10266175" 48 name: "Makaha Valley Paradise with OceanView" 49 summary: "A beautiful and comfortable 1 Bedroom Air Conditioned Condo in Makaha …" 50 ... 51 property_type: "Condominium" 52 ... 53 address: 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 68 SCORE: 2.238388776779175 _id: "1042446" 69 listing_url: "https://www.airbnb.com/rooms/1042446" 70 name: "March 2019 availability! Oceanview on Sugar Beach!" 71 summary: "" 72 ... 73 property_type: "Condominium" 74 ... 75 address: 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 90 SCORE: 2.238388776779175 _id: "10527243" 91 listing_url: "https://www.airbnb.com/rooms/10527243" 92 name: "Tropical Jungle Oasis" 93 summary: "2 bedrooms, one with a queen sized bed, one with 2 single beds. 1 and …" 94 ... 95 property_type: "Condominium" 96 ... 97 address: 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 ... 111 112 SCORE: 2.238388776779175 _id: "1104768" 113 listing_url: "https://www.airbnb.com/rooms/1104768" 114 name: "2 Bdrm/2 Bath Family Suite Ocean View" 115 summary: "This breathtaking 180 degree view of Waikiki is one of a kind. You wil…" 116 ... 117 property_type: "Condominium" 118 ... 119 address: 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 ... 133 134 SCORE: 2.238388776779175 _id: "11207193" 135 listing_url: "https://www.airbnb.com/rooms/11207193" 136 name: "302 Kanai A Nalu Ocean front/view" 137 summary: "Welcome to Kana'i A Nalu a quiet resort that sits on the ocean away fr…" 138 ... 139 property_type: "Condominium" 140 ... 141 address: 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 ... 155 156 SCORE: 2.238388776779175 _id: "11319047" 157 listing_url: "https://www.airbnb.com/rooms/11319047" 158 name: "Sugar Beach Resort 1BR Ground Floor Condo !" 159 summary: "The Sugar Beach Resort enjoys a beachfront setting fit for a postcard." 160 ... 161 property_type: "Condominium" 162 ... 163 address: 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 ... 177 178 SCORE: 2.238388776779175 _id: "11695887" 179 listing_url: "https://www.airbnb.com/rooms/11695887" 180 name: "2 BR Oceanview - Great Location!" 181 summary: "Location, location, location... This is a great 2 bed, 2 bath condo is…" 182 ... 183 property_type: "Condominium" 184 ... 185 address: 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 ... 199 200 SCORE: 2.238388776779175 _id: "11817249" 201 listing_url: "https://www.airbnb.com/rooms/11817249" 202 name: "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC" 203 summary: "Book with confidence this stunning 2 bedroom, 2 bathroom condo at the …" 204 ... 205 property_type: "Condominium" 206 ... 207 address: 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。
1 using MongoDB.Bson; 2 using MongoDB.Bson.IO; 3 using MongoDB.Bson.Serialization; 4 using MongoDB.Bson.Serialization.Attributes; 5 using MongoDB.Bson.Serialization.Conventions; 6 using MongoDB.Driver; 7 using MongoDB.Driver.GeoJsonObjectModel; 8 using MongoDB.Driver.Search; 9 using System; 10 11 public 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 [ ]59 public class AirbnbDocument 60 { 61 [ ]62 public ObjectId Id { get; set; } 63 public String Name { get; set; } 64 [ ] 65 public string PropertyType { get; set; } 66 public Address Address { get; set; } 67 public double Score { get; set; } 68 } 69 [ ]70 public 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 }
1 package main 2 3 import ( 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 12 func 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{{"$meta", "searchScore"}}}}}} // run pipeline cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage}) if err != nil { panic(err) } // print results var results []bson.D if err = cursor.All(context.TODO(), &results); err != nil { panic(err) } for _, result := range results { fmt.Println(result) } }
1 import java.util.Arrays; 2 import static com.mongodb.client.model.Filters.eq; 3 import static com.mongodb.client.model.Aggregates.limit; 4 import static com.mongodb.client.model.Aggregates.project; 5 import static com.mongodb.client.model.Projections.computed; 6 import static com.mongodb.client.model.Projections.excludeId; 7 import static com.mongodb.client.model.Projections.fields; 8 import static com.mongodb.client.model.Projections.include; 9 import com.mongodb.client.MongoClient; 10 import com.mongodb.client.MongoClients; 11 import com.mongodb.client.MongoCollection; 12 import com.mongodb.client.MongoDatabase; 13 import org.bson.Document; 14 15 public class GeoQuery { 16 public static void main( String[] args ) { 17 Document agg = new Document( "$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。
1 import com.mongodb.client.model.Aggregates.limit 2 import com.mongodb.client.model.Aggregates.project 3 import com.mongodb.client.model.Projections.* 4 import com.mongodb.kotlin.client.coroutine.MongoClient 5 import kotlinx.coroutines.runBlocking 6 import org.bson.Document 7 8 fun 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。
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri ="<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async 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 '$meta': 'searchScore' 65 } 66 } 67 } 68 ]; 69 // run pipeline 70 const result = await coll.aggregate(agg); 71 72 // print results 73 await result.forEach((doc) => console.log(doc)); 74 } finally { 75 await client.close(); 76 } 77 } 78 run().catch(console.dir);
次のコード例では、次を行います。
pymongo
、 MongoDBのPythonドライバー、および DNSシードリスト接続文字列を使用してpymongo
をAtlas
に接続するために必要なdns
モジュールをインポートします。Atlas クラスターへの接続を確立するための
MongoClient
クラスのインスタンスを作成します。カーソルを反復処理して、クエリに一致するドキュメントを出力します。
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient('<connection-string>') 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$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 60 result = client["sample_airbnb"]["listingsAndReviews"].aggregate(pipeline) 61 62 # print results 63 for 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。
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。
1 db.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 } } }