Elasticsearch实战——地理位置查询

Elasticsearch实战——地理位置查询


为了方便学习ES的地理位置查询,这里准备了一些地理坐标为测试数据,每一条数据都包含城市名称和地理坐标两个字段。首先把下面的内容保存到 geo.json文件中:

{"index":{"_index":"geo","_id":"1"}}
{"city":"北京","localtion":"40.019559,116.312282"}
{"index":{"_index":"geo","_id":"2"}}
{"city":"乌鲁木齐","localtion":"43.863737,87.53891"}
{"index":{"_index":"geo","_id":"3"}}
{"city":"西安","localtion":"34.43376,108.879774"}
{"index":{"_index":"geo","_id":"4"}}
{"city":"郑州","localtion":"34.76845,113.589482"}
{"index":{"_index":"geo","_id":"5"}}
{"city":"杭州","localtion":"30.345351,120.102125"}
{"index":{"_index":"geo","_id":"6"}}
{"city":"济南","localtion":"36.688506,117.158558"}
{"index":{"_index":"geo","_id":"7"}}
{"city":"上海","localtion":"31.298035,121.426731"}
{"index":{"_index":"geo","_id":"8"}}
{"city":"武汉","localtion":"30.632158,114.28858"}
{"index":{"_index":"geo","_id":"9"}}
{"city":"广州","localtion":"23.150725,113.221536"}

然后创建一个索引:

PUT geo
{
    
    
  "settings": {
    
    
    "number_of_shards": "1",
    "number_of_replicas": "0"
  },
  "mappings": {
    
    
    "properties": {
    
    
      "city": {
    
    
        "type": "keyword"
      },
      "location": {
    
    
        "type": "geo_point"
      }
    }
  }
}

再执行:

$curl -X POST "localhost:9200/_bulk?pretty" -H 'Content-Type: application/json' --data-binary @geo.json

1. 半径查询(geo_distance query)

geo_distance query可以查找在一个中心点指定半径范围内的地理文档。例如查询距离天津500km以内的城市,搜索结果会返回北京、济南,命令如下:

{
    
    
	"query":{
    
    
		"bool":{
    
    
			"must":{
    
    
				"match_all":{
    
    }
			},
			"filter":{
    
    
				"geo_distance":{
    
    
					"distance":"500km",
					"location":{
    
    
						"lat":"38.993443",
						"lon":"117.158558"
					}
				}
			}
		}
	}
}

按距离天津的距离排序:

{
    
    
  "query": {
    
    
    "bool": {
    
    
      "must": {
    
    
        "match_all": {
    
    }
      },
      "filter": {
    
    
        "geo_distance": {
    
    
          "distance": "500km",
          "location": {
    
    
            "lat": "38.993443",
            "lon": "117.158558"
          }
        }
      }
    }
  },
  "sort": [
    {
    
    
      "_geo_distance": {
    
    
        "location": {
    
    
          "lat": "38.993443",
          "lon": "117.158558"
        },
        "unit": "km"
      }
    }
  ]
}

2. 指定矩形内的查询(geo_bounding_box query)

geo_bounding_box query用于查询落入指定的矩形内的地理坐标。查询中由两个点确定一个矩形,如图中的银川和南昌,在这两个点上分别做垂线(经度)和平行线(维度),相交线会组成一个矩形区域,可以查询到西安、郑州、武汉。

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左上角和右下角查询

{
    
    
	"query":{
    
    
		"bool":{
    
    
			"must":{
    
    
				"match_all":{
    
    }
			},
			"filter":{
    
    
				"geo_bounding_box":{
    
    
					"location":{
    
    
						"top_left":{
    
    
							"lat":"38.532499",
							"lon":"106.193769"
						},
						"bottom_right":{
    
    
							"lat":"28.671728",
							"lon":"115.907542"
						}
					}
				}
			}
		}
	}
}

左下角和右上角查询

{
    
    
  "query": {
    
    
    "bool": {
    
    
      "must": {
    
    
        "match_all": {
    
    }
      },
      "filter": {
    
    
        "geo_bounding_box": {
    
    
          "location": {
    
    
            "top_right": {
    
    
              "lat": "40.807062",
              "lon": "119.108671"
            },
            "bottom_left": {
    
    
              "lat": "22.12604",
              "lon": "101.741623"
            }
          }
        }
      }
    }
  }
}

3. 查询指定多边形内的数据(geo_polygon query)

geo_polygon query用于查找指定多边形内的地理点。例如,呼和浩特、重庆、上海三地组成的三角形,查询位置在改三角形区域内的城市。

[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-MXBETgbX-1578904421241)(D:\work\elasticsearch\geo_polygon.png)]

{
    
    
	"query":{
    
    
		"bool":{
    
    
			"must":{
    
    
				"match_all":{
    
    }
			},
			"filter":{
    
    
				"geo_polygon":{
    
    
					"location":{
    
    
						"points":[
							{
    
    "lat":"40.835015","lon":"111.712958"},
							{
    
    "lat":"29.640695","lon":"106.561715"},
							{
    
    "lat":"31.23482","lon":"121.50032"}
						]
					}
				}
			}
		}
	}
}

4 查询geo_shape类型的数据(geo_shape query)

geo_shapequery用于查询geo_shape类型的地理数据,地理形状之间包含的关系有:相交、包含、不相交三种。创建一个新的索引用于测试,其中location字段的类型设置为geo_shape类型:

PUT geoshape
{
    
    
  "settings": {
    
    
    "number_of_shards": "1",
    "number_of_replicas": "0"
  },
  "mappings": {
    
    
    "properties": {
    
    
      "city": {
    
    
        "type": "keyword"
      },
      "location": {
    
    
        "type": "geo_shape"
      }
    }
  }
}

geo_point类型的字段是:纬度在前,经度在后,但是geo_shape类型中的点是:经度在前,纬度在后。这点需要特别注意。

POST geoshape/_doc/1
{
    
    
	"city":"西安-郑州",
	"location":{
    
    
		"type":"linestring",
		"coordinates":[
			[108.953364,34.372762],
			[113.626277,34.76845]
		]
	}
}

查询包含在由银川和南昌组成的矩形的地理形状内的数据,由于西安和郑州组成的直线落在该矩形区域内,因此可以被查询到。

{
    
    
	"query":{
    
    
		"bool":{
    
    
			"must":{
    
    
				"match_all":{
    
    }
			},
			"filter":{
    
    
				"geo_shape":{
    
    
					"location":{
    
    
						"shape":{
    
    
							"type":"envelope",
							"coordinates":[
								[106.230564,38.50359],
								[115.870747,28.704175]
							]
						},
						"relation":"within"
					}
				}
			}
		}
	}
}

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转载自blog.csdn.net/dwjf321/article/details/103960280