gistfile1.txt

###Changes:
-Added "include_in_root" for each nested object.  
-Removed the "nested" params from the last facet

This basically copies the nested doc into the root doc.  You then reference the root "inner object" rather than the "nested object" to get the data.  Be careful though, this breaks down if you have multiple nested docs that share the same name (e.g. array of nested), since the facet will operate on the entire array instead of individual ones.

See this thread for more info:  https://groups.google.com/d/topic/elasticsearch/pjoNmosdCPs/discussion




##### Delete past attempts

curl -X DELETE localhost:9200/example

##### Create mapping with two nested documents (a 'thing' has 'foo' and 'bar')

curl -XPUT 'http://127.0.0.1:9200/example/?pretty=1' -d '
{
   "mappings" : {
      "thing" : {
         "properties" : {
            "name": {
               "type": "string"
            },
            "foo" : {
               "type" : "nested",
               "include_in_root": true,
               "properties" : { "name": { "type": "string" }}
            },
            "bar" : {
               "type" : "nested",
               "include_in_root": true,
               "properties" : { "name": { "type": "string" }}
            }
         }
      }
   }
}
'

##### Add some data

curl -XPOST 'http://127.0.0.1:9200/example/thing?pretty=1'  -d '
{
   "name" : "My Thing",
   "foo": {"name": "Foo"},
   "bar": {"name": "MyBar"}
}
'
curl -XPOST 'http://127.0.0.1:9200/example/thing?pretty=1'  -d '
{
   "name" : "Your Thing",
   "foo": {"name": "Foo"},
   "bar": {"name": "YourBar"}
}
'

##### Query data

curl -XGET 'http://127.0.0.1:9200/example/thing/_search?pretty=1'  -d '
{
   "query" : {
      "match" : {
         "name": "Thing"
      }
   },
   "facets" : {
      "foo_facet" : {
        "terms" : { "field" : "foo.name" },
        "nested": "foo"
      },
      "bar_facet" : {
        "terms" : { "field" : "bar.name" },
        "nested": "bar"
      },
      "bar_facet_where_bar_other" : {
        "facet_filter": { "terms": { "bar.name": ["mybar"] } },
        "terms" : { "field" : "bar.name" }
         "nested" : "bar"
      },
      "foo_facet_where_bar_other" : {
        "facet_filter": { "terms": { "bar.name": ["mybar"] } },
        "terms" : { "field" : "foo.name" }
      }
   }
}
'

#### Search results

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 0.8784157,
    "hits" : [ {
      "_index" : "example",
      "_type" : "thing",
      "_id" : "_ty1yk_gQ0eAyZl7mqxP-w",
      "_score" : 0.8784157, "_source" :
{
"name" : "My Thing",
"foo": {"name": "Foo"},
"bar": {"name": "MyBar"}
}

    }, {
      "_index" : "example",
      "_type" : "thing",
      "_id" : "i1AokusmRdWyeaVQpOL9KQ",
      "_score" : 0.8784157, "_source" :
{
"name" : "Your Thing",
"foo": {"name": "Foo"},
"bar": {"name": "YourBar"}
}

    } ]
  },
  "facets" : {
    "foo_facet" : {
      "_type" : "terms",
      "missing" : 0,
      "total" : 2,
      "other" : 0,
      "terms" : [ {
        "term" : "foo",
        "count" : 2
      } ]
    },
    "bar_facet" : {
      "_type" : "terms",
      "missing" : 0,
      "total" : 2,
      "other" : 0,
      "terms" : [ {
        "term" : "yourbar",
        "count" : 1
      }, {
        "term" : "mybar",
        "count" : 1
      } ]
    },
    "bar_facet_where_bar_other" : {
      "_type" : "terms",
      "missing" : 0,
      "total" : 1,
      "other" : 0,
      "terms" : [ {
        "term" : "mybar",
        "count" : 1
      } ]
    },
    "foo_facet_where_bar_other" : {
      "_type" : "terms",
      "missing" : 0,
      "total" : 1,
      "other" : 0,
      "terms" : [ {
        "term" : "foo",
        "count" : 1
      } ]
    }
  }
}