在数组中具有多个位置的 ElasticSearch 地理距离过滤器 - 可能吗？

Question

假设我们在 ElasticSearch 索引中有一堆文档。每个文档都有多个位置在一个数组中，像这样:

{
  "name": "foobar",
  "locations": [
    {
      "lat": 40.708519,
      "lon": -74.003212
    },
    {
      "lat": 39.752609,
      "lon": -104.998100
    },
    {
      "lat": 51.506321,
      "lon": -0.127140
    }
  ]
}

根据ElasticSearch reference guide

the geo_distance filter can work with multiple locations / points per document. Once a single location / point matches the filter, the document will be included in the filter.

那么，是否可以创建一个地理距离过滤器来检查数组中的所有位置？

不幸的是，这似乎不起作用:

{
  "filter": {
    "geo_distance": {
      "distance": "100 km",
      "locations": "40, -105"
    }
  }
}

抛出“QueryParsingException[[myIndex] 未能找到 geo_point 字段 [locations]”，因为 locations 不是单个 geo_point 而是一个数组geo_point 的。

Answer 1

您是否指定了 geo_point mapping为您的文档？

curl -XDELETE 'http://localhost:9200/twitter/'
curl -XPUT 'http://localhost:9200/twitter/'

curl -XPUT 'http://localhost:9200/twitter/tweet/_mapping' -d '
{
    "tweet" : {
        "properties" : {
            "locations" : {"type" : "geo_point"}
        }
    }
}'

curl -XPUT 'http://localhost:9200/twitter/tweet/1' -d '
{ 
    "user": "kimchy", 
    "postDate": "2009-11-15T13:12:00", 
    "message": "Trying out Elastic Search, so far so good?",
    "locations" : [{
        "lat" : 50.00,
        "lon" : 10.00
    },
    {
        "lat" : 40.00,
        "lon" : 9.00
    }]
}'

curl -XPUT 'http://localhost:9200/twitter/tweet/2' -d '
{ 
    "user": "kimchy", 
    "postDate": "2009-11-15T13:12:00", 
    "message": "Trying out Elastic Search, so far so good?",
    "locations" : [{
        "lat" : 30.00,
        "lon" : 8.00
    },
    {
        "lat" : 20.00,
        "lon" : 7.00
    }]
}'

curl -XGET 'http://localhost:9200/twitter/tweet/_search' -d '{
    "query": {
        "filtered" : {
            "query" : {
                "match_all" : {}
            },
            "filter" : {
                "geo_distance" : {
                    "distance" : "20km",
                    "tweet.locations" : {
                        "lat" : 40.00,
                        "lon" : 9.00
                    }
                }
            }
        }
    }
}'