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GeoJSON Object
몽고DB에서 GeoJSON Objects는 지리적 위치 정보를 나타내는 JSON 형식의 데이터입니다. GeoJSON은 다양한 지리 정보 데이터 유형을 포함하는 오픈 소스 데이터 형식으로, 지리적 위치 정보를 다루는 많은 애플리케이션에서 사용됩니다.
몽고DB는 GeoJSON Objects를 지원하며, GeoJSON 형식의 데이터를 저장하고 쿼리하기 위한 강력한 기능을 제공합니다. 모든 GeoJSON 객체는 몽고DB의 지리 공간 인덱스(Spatial Index)를 사용하여 쿼리할 수 있습니다.
- type 필드 : GeoJSON Object 타입
- "Point", "LineString", "Polygon", "MultiPoint", "MultiLineString", "MultiPolygon", "GeometryCollection"
- coordinates 필드 : 위치 정보 저장
- 내장 객체의 필드명은 GeoJSON에서 지정되므로 변경 불가
{
"name" : "New York City",
"loc" : { "type" : "Point", //점
"coordinates" : [50, 2] //경도, 위도
}
}
{
"name" : "Hudson River",
"loc" : { "type" : "LineString", //선
"coordinates" : [[0,1],[0,2],[1,2]] //점의 배열
}
}
{
"name" : "New England",
"loc" : { "type" : "Polygon", //다각형
"coordinates" : [[0,1],[0,2],[1,2],[0,1]] //점의 배열
}
}2dsphere
WGS84 좌표계를 기반으로 지표면을 모델링하는 구면 기하학으로 작동
지구와 같은 구에서 geometry를 계산하는 쿼리 지원
> db.openStreetMap.createIndex({"loc" : "2dsphere"})2d
2차원 평면 상에서 geometry를 계산하는 쿼리 지원
> db.openStreetMap.createIndex({"loc" : "2d"})6.1.1 공간 정보 쿼리 유형
"$geoIntersects" : 쿼리 위치와 교차하는 도큐먼트 조회
> db.openStreetMap.find({"loc" :
{"$geoIntersects" : {"$geometry" : eastVillage}}})"$geoWithin" : 특정 지역에 완전히 포함된 항목 조회, 겹치는 지역은 반환 X
> db.openStreetMap.find({"loc" :
{"$geoWithin" : {"$geometry" : eastVillage}}})"$near" : 주변 위치를 조회. 정렬을 포함하는 유일한 연산자 (거리가 가까운 곳부터 정렬)
> db.openStreetMap.find({"loc" :
{"$near" : {"$geometry" : eastVillage}}})6.1.2 공간 정보 인덱스 사용
2d vs 구면 기하학
- 인덱스 유형에 따라 구면 또는 2D 구조를 사용
- 공간 정보 연산자가 사용하는 기하 구조 유형
- 2d 인덱스는 구에서 평면 기하학과 거리 계산을 모두 지원 ($nearSphere를 사용)
- 구면 기하학을 사용하는 쿼리는 2dsphere 인덱스 사용이 성능 정확성 향상
- $geoNear 연산자는 집계 연산자
- $near 연산자는 샤딩을 사용해 배포된 컬렉션에서는 작동 불가
- geoNear, $geoNear 집계 연산자를 사용하려면 컬렉션에 2dsphere, 2d 인덱스가 최대 1개만 존재해야함
- $near, $geoWithin 공간 정보 연산자는 공간 정보 인덱스 여러개 허용
- geoNear, $geoNear 위치 필드를 포함하지 않으므로 공간 정보 인덱스 제한
왜곡
- 구면 기하는 지도에 시각화하면 왜곡이 있는데 지구와 같은 3차원 구를 평면에 투사하는 특성 때문
데이터 탐색
> db.neighborhoods.find({name : "Clinton"})
{
"_id" : ObjectId("55cb9c666c522cafdb053a71"),
"geometry" : {
"coordinates" : [
[
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]
],
"type" : "Polygon"
},
"name" : "Clinton"
}
> db.restaurants.find({name : "Little Pie Company"})
{
"_id" : ObjectId("55cba2476c522cafdb053dea"),
"location" : {
"coordinates" : [ -73.99331699999999, 40.7594404 ],
"type" : "Point"
},
"name" : "Little Pie Company"
}현재 지역 찾기
정확한 위치 정보를 제공한다고 가정할 때 $geoIntersects를 사용해 조회
> db.neighborhoods.findOne({geometry : {$geoIntersects : {$geometry: {type:"Point", coordinates:[-73.93414657,40.82302903]}}}})
{
"_id" : ObjectId("55cb9c666c522cafdb053a68"),
"geometry" : {
"coordinates" : [
[
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]
],
"type" : "Polygon"
},
"name" : "Central Harlem North-Polo Grounds"
}지역 내 모든 레스토랑 찾기
> var neighborhood = db.neighborhoods.findOne({
geometry: {
$geoIntersects : {
$geometry: {
type : "Point",
coordinates : [-73.93414657,40.82302903]
}
}
}
});
> db.restaurants.find({
location : {
$geoWithin : {
$geometry : neighborhood.geometry
}
}
}, {name:1, _id:0});
/* 1 */
{
"name" : "Perfect Taste"
},
/* 2 */
{
"name" : "Event Productions Catering & Food Services"
},
/* 3 */
{
"name" : "Sylvia'S Restaurant"
},
/* 4 */
{
"name" : "Corner Social"
},
/* 5 */
{
"name" : "Cove Lounge"
},
/* 6 */
{
"name" : "Manna'S Restaurant"
},
/* 7 */
{
"name" : "Harlem Bar-B-Q"
},
/* 8 */
{
"name" : "Hong Cheong"
},
/* 9 */
{
"name" : "Lighthouse Fishmarket"
},
/* 10 */
{
"name" : "Mahalaxmi Food Inc"
},
/* 11 */
{
"name" : "Rose Seeds"
},
/* 12 */
{
"name" : "J. Restaurant"
},
/* 13 */
{
"name" : "Harlem Coral Llc"
},
/* 14 */
{
"name" : "Baraka Buffet"
},
/* 15 */
{
"name" : "Make My Cake"
},
/* 16 */
{
"name" : "Hyacinth Haven Harlem"
},
/* 17 */
{
"name" : "Mcdonald'S"
},
/* 18 */
{
"name" : "Ihop"
},
/* 19 */
{
"name" : "Island Spice And Southern Cuisine"
},
/* 20 */
{
"name" : "To Your Health & Happiness"
},
/* 21 */
{
"name" : "Cafe 22"
},
/* 22 */
{
"name" : "Popeyes Chicken & Biscuits"
},
/* 23 */
{
"name" : "Herbalife"
},
/* 24 */
{
"name" : "Elsie'S Caribbean Cafe"
},
/* 25 */
{
"name" : "Shrine/Yatenga"
},
/* 26 */
{
"name" : "Little Harlem Fried Chicken"
},
/* 27 */
{
"name" : "Acts 3 Bagels"
},
/* 28 */
{
"name" : "Uptown Slices"
},
/* 29 */
{
"name" : "Abyssinia Ethiopian Restaurant"
},
/* 30 */
{
"name" : "New Crispy Bamboo"
},
/* 31 */
{
"name" : "Lil Bite'S Cafe"
},
/* 32 */
{
"name" : "Yvonne Yvonne Restaurant"
},
/* 33 */
{
"name" : "Subway"
},
/* 34 */
{
"name" : "Ma Dukes"
},
/* 35 */
{
"name" : "American Legion Veterans Post"
},
/* 36 */
{
"name" : "Keur Sokhna Restaurant"
},
/* 37 */
{
"name" : "Great Wall Kitchen"
},
/* 38 */
{
"name" : "Harlem Karibe Take Out"
},
/* 39 */
{
"name" : "Oui, Oui, Crepes And Pizza"
},
/* 40 */
{
"name" : "White Castle"
},
/* 41 */
{
"name" : "New Ocean"
},
/* 42 */
{
"name" : "Jacob Soul Food Restaurant"
},
/* 43 */
{
"name" : "Jimbo'S Hamburgers"
},
/* 44 */
{
"name" : "Lenox Saphire"
},
/* 45 */
{
"name" : "Subway"
},
/* 46 */
{
"name" : "Lenox Coffee"
},
/* 47 */
{
"name" : "Manna Restaurant Ii"
},
/* 48 */
{
"name" : "Golden Krust Caribbean Bakery & Grill"
},
/* 49 */
{
"name" : "Island Salad"
},
/* 50 */
{
"name" : "China Wok"
}범위 내에서 레스토랑 찾기
- 원형 지역 내 탐색 $centerSphere 와 함께 $geoWithin을 사용
- 정렬되지 않은 순서로 반환
- $centerSphere는 중심과 반경을 radian으로 지정해 원형 영역을 나타내는 구문
- $maxDistance 와 $nearSphere 사용하면 거리 순으로 정렬된 결과 반환
> db.restaurants.find({
location : {
$geoWithin : {
$centerSphere: [
[-73.93414657, 40.82302903], 5/3963.2] //5마일 이내 레스토랑 탐색
}
}
});
var METERS_PER_MILE = 1609.34;
db.restaurants.find({
location : {
$nearSphere : {
$geometry: {
type : "Point",
coordinates : [-73.93414657, 40.82302903]
},
$maxDistance : 5 * METERS_PER_MILE //미터 단위로 변환
}
}
});6.1.3 복합 공간 정보 인덱스
- 다른 인덱스와 마찬가지로 다른 필드와 묶어서 복잡한 쿼리 최적화
- 첫 번째 인덱스 조건으로 결과를 더 많이 필터링 가능하도록 구성
db.openStreetMap.createIndex({"tags": 1, "location" : "2sphere"})
db.openStreetMap.find({"loc" : {"$geoWithin" :
{"$geometry" : hellsKitchen.geometry}},
"tags" : "pizza"})6.1.4 2d 인덱스
- 비구체 지도에는 "2dsphere" 대신 "2d" 인덱스 사용
- 지형이 구체가 아니라 완전히 평평한 표면이라고 가정
- 극 주변은 왜곡이 매우 심하므로 사용하면 안됨
- 인덱스 필드에 요소가 2개인 배열 사용, 경도와 위도
- 점만 인덱싱할 수 있기 때문에 GeoJSON 데이터 저장하지 말자
- 기본적으로 -180과 180 사이에 있다고 가정. 범위 조정 가능
db.hyrule.createIndex("light-years" : "2d"}, {"min" : -1000, "max": 1000})- $geoWithin 평평한 표면에 정의된 영역 내 점을 쿼리하는데 사용
db.hyrule.find({"title" : {
$geoWithin : {
$box : [[10, 10], [100], [100]]
}
}})- $near 는 주변에 있는 점을 쿼리
- 특정 지점으로부터 가장 가까운 좌표 쌍을 포함하는 도큐먼트를 반환
- 거리가 가까운 순으로 정렬
- 제한이 지정되지 않으면 기본적으로 100개 제한
db.hyrule.find({"title" : { $near : [20,21]}})
db.hyrule.find({"title" : { $near : [20,21]}}).limit(10)
https://www.mongodb.com/docs/manual/geospatial-queries/
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