<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-mongodb</artifactId> </dependency>
@Document(collection="coffeeShop") public class CoffeeShop { @Id private String id; private String name; @GeoSpatialIndexed private double[] location; //.... }
spherical为true则距离单位为空间弧度,false则距离单位为水平单位度
spherical为false,参数为千米数除以111
public GeoResults<CoffeeShop> near2(double[] poi){ NearQuery near = NearQuery .near(new Point(poi[0],poi[1])) .spherical(false) .num(1); GeoResults<CoffeeShop> results = mongoTemplate.geoNear(near, CoffeeShop.class); return results; }
输出html
GeoResults: [averageDistance: 0.08294719588991498, results: GeoResult [content: com.codecraft.domain.CoffeeShop@747f6c5a, distance: 0.08294719588991498, ]]
不指定spherical,默认为false,结果中的dis须要乘以111换算为km
public GeoResults<CoffeeShop> near2(double[] poi){ NearQuery near = NearQuery .near(new Point(poi[0],poi[1])) .spherical(false) .distanceMultiplier(111) .num(1); GeoResults<CoffeeShop> results = mongoTemplate.geoNear(near, CoffeeShop.class); return results; }
输出java
GeoResults: [averageDistance: 9.207138743780563 org.springframework.data.geo.CustomMetric@28768e25, results: GeoResult [content: com.codecraft.domain.CoffeeShop@310d57b1, distance: 9.207138743780563 org.springframework.data.geo.CustomMetric@28768e25, ]]
即北京阿里绿地中心距离三里屯星巴克距离9km
若要设置最大距离,则spring
public GeoResults<CoffeeShop> near2(double[] poi){ NearQuery near = NearQuery .near(new Point(poi[0],poi[1])) .spherical(false) .maxDistance(5/111.0d) .distanceMultiplier(111) .num(1); GeoResults<CoffeeShop> results = mongoTemplate.geoNear(near, CoffeeShop.class); return results; }
结果为空
须要数据存储为(经度,纬度),否则报错
org.springframework.dao.DataIntegrityViolationException: Write failed with error code 16755 and error message 'Can't extract geo keys: { _id: ObjectId('58df9c50b45cbc069f6ff548'), _class: "com.codecraft.domain.CoffeeShop", name: "深圳市南山区星巴克(海岸城店)", location: [ 22.52395, 113.943442 ] } can't project geometry into spherical CRS: [ 22.52395, 113.943442 ]'; nested exception is com.mongodb.WriteConcernException: Write failed with error code 16755 and error message 'Can't extract geo keys: { _id: ObjectId('58df9c50b45cbc069f6ff548'), _class: "com.codecraft.domain.CoffeeShop", name: "深圳市南山区星巴克(海岸城店)", location: [ 22.52395, 113.943442 ] } can't project geometry into spherical CRS: [ 22.52395, 113.943442 ]' at org.springframework.data.mongodb.core.MongoExceptionTranslator.translateExceptionIfPossible(MongoExceptionTranslator.java:85)
使用mongodb
public GeoResults<CoffeeShop> nearRadian(double[] poi){ NearQuery near = NearQuery .near(new Point(poi[0],poi[1])) .spherical(true) .maxDistance(10,Metrics.KILOMETERS) //MILES以及KILOMETERS自动设置spherical(true) .distanceMultiplier(6371) .num(1); GeoResults<CoffeeShop> results = mongoTemplate.geoNear(near, CoffeeShop.class); return results; }
@Test public void testInitGeo() { //http://map.yanue.net/toLatLng/ CoffeeShop shop1 = new CoffeeShop("深圳市南山区星巴克(海岸城店)",new double[]{113.943442,22.52395}); CoffeeShop shop2 = new CoffeeShop("广州市白云区星巴克(万达广场店)",new double[]{113.274643,23.180251}); CoffeeShop shop3 = new CoffeeShop("北京市朝阳区星巴克(三里屯店)",new double[]{116.484385,39.923778}); CoffeeShop shop4 = new CoffeeShop("上海市浦东新区星巴克(滨江店)",new double[]{121.638481,31.230895}); CoffeeShop shop5 = new CoffeeShop("南京市鼓楼区星巴克(山西路店)",new double[]{118.788924,32.075343}); CoffeeShop shop6 = new CoffeeShop("厦门市思明区星巴克(中华城店)",new double[]{118.089813,24.458157}); CoffeeShop shop7 = new CoffeeShop("杭州市西湖区星巴克(杭州石函店)",new double[]{120.143005,30.280273}); coffeeShopDao.save(Lists.newArrayList(shop1,shop2,shop3,shop4,shop5,shop6,shop7)); } @Test public void testNear(){ //经度\纬度 double[] bjAli = new double[]{116.492644,40.006313}; double[] szAli = new double[]{113.950723,22.558888}; double[] shAli = new double[]{121.387616,31.213301}; double[] hzAli = new double[]{120.033345,30.286398}; Arrays.asList(bjAli,szAli,shAli,hzAli).stream().forEach(d -> { GeoResults<CoffeeShop> results = locationService.nearRadian(d); System.out.println(results); }); }
另外,对于spherical与非spherical查询,貌似没啥区别,就是spherical在使用时入参无需关心单位换算,稍微方便点。