Elasticsearch: Geo_spacial search in a list of nested objects

Elastic Stack Elasticsearch
1

I'm using Elasticsearch 6.3 and spring-data-elasticsearch, I have the index restaurant having the mapping below :

{
 "mapping": {
   "restaurant": {
     "properties": {
       "id": {
         "type": "keyword"
       },
       "name": {
         "type": "text",
         "store": true,
         "analyzer": "custom_analyzer",
         "search_analyzer": "custom_search_analyzer"
       },
       "locations": {
         "type": "nested",
         "include_in_parent": true,
         "properties": {
           "id": {
             "type": "long"
           },
           "fullAddress": {
             "type": "text"
           },
           "geo": {
             "type": "geo_point"
           },
           "phone": {
             "type": "keyword"
           }
         }
       },
       "menus": {
         "type": "nested",
         "properties": {
           "id": {
             "type": "long"
           },
           "name": {
             "type": "text",
             "store": true,
             "analyzer": "custom_analyzer",
             "search_analyzer": "custom_search_analyzer"
           }
         }
       }
     }
   }
 }
}

This is an example of a document of this mapping :

{
 "took": 1,
 "timed_out": false,
 "_shards": {
   "total": 5,
   "successful": 5,
   "skipped": 0,
   "failed": 0
 },
 "hits": {
   "total": 1,
   "max_score": 1,
   "hits": [
     {
       "_index": "restaurants",
       "_type": "restaurants",
       "_id": "1",
       "_score": 1,
       "_source": {
         "id": 1,
         "name": "Mc Donald",
         "menus": [
           {
             "id": 7097,
             "name": "Big Fish"
           },
           {
             "id": 13899,
             "name": "Big Mac"
           }
         ],
         "locations": [
           {
             "id": 1,
             "fullAddress": "7 Bd Solférino, 59000 Lille",
             "geo": { "lat": 50.6423461,"lon": 3.1390441},
             "phone": "0305060804"
           },
           {
             "id": 2,
             "fullAddress": "7 Rue Nationale, 75000 Paris",
             "geo": { "lat": 40.6423461,"lon": -7.1390441},
             "phone": "0305060804"
           }
         ]
       }
     }
   ]
 }
}

I try to search all the restaurants around me, for example, I search the nearest Mc Donald.

I tryed the 2 queries below but they return emty list :

  • Query 1: (Using post filtering)
GET restaurants/_search
{
  "query": {
    "match": {
      "name": "donald"
    }
  },
  "post_filter": {
    "nested": {
      "path": "locations",
      "query": {
        "geo_distance": {
          "distance": "10km",
          "locations.geo": [50.6423461, 3.1390441]
        }
      }
    }
  }
}
  • Query 2: (Using filtering inside query)
GET restaurants/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "name": "donald"
          }
        }
      ],
      "filter": {
        "nested": {
          "path": "locations",
          "query": {
            "geo_distance": {
              "distance": "10km",
              "locations.geo": [50.6423461,3.1390441]
            }
          },
          "inner_hits": {}
        }
      }
    }
  }
}

PLEASE, could someone tell me what I do wrong in my mapping or queries.
Thx in advance

2

The order of the geo points in the query is incorrect. Note that in that cases (array format) the position must be [lon, lat], as defined here:

https://www.elastic.co/guide/en/elasticsearch/reference/current/geo-point.html

Therefore this query should give you the expected answer:

GET restaurants/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "name": "donald"
          }
        }
      ],
      "filter": {
        "nested": {
          "path": "locations",
          "query": {
            "geo_distance": {
              "distance": "10km",
              "locations.geo": [3.1390441, 50.6423461]
            }
          },
          "inner_hits": {}
        }
      }
    }
  }
}
3

OK it's so simple, but I had to see it :sweat_smile:
It works like a charm :wink:

Thank you very much.

4

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