How to get aggregated data from nested schema using Elasticsearch DSL

Environments

curl http://localhost:9200
{
  "name" : "xxxxx",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "xxxxx",
  "version" : {
    "number" : "6.2.4",
    "build_hash" : "xxxxx",
    "build_date" : "2018-04-12T20:37:28.497551Z",
    "build_snapshot" : false,
    "lucene_version" : "7.2.1",
    "minimum_wire_compatibility_version" : "5.6.0",
    "minimum_index_compatibility_version" : "5.0.0"
  },
  "tagline" : "You Know, for Search"
}

$ python -m pip freeze
elasticsearch==6.3.0
elasticsearch-dsl==6.1.0

Introduction

nothing special

Schema

# show schema
$ curl -H "Accept: application/json" -H "Content-type: application/json" -XGET http://localhost:9200/index_name/_all/_mapping?pretty
{
  "index_name" : {
    "mappings" : {
      "index_name" : {
        "dynamic" : "strict",
        "_all" : {
          "enabled" : false
        },
        "properties" : {
          "annotate" : {
            "properties" : {
              "data" : {
                "type" : "nested",
                "properties" : {
                  "people" : {
                    "properties" : {
                      "name" : {
                        "type" : "keyword"
                      }
                    }
                  }
                }
              }
            }
          },
          "created_at" : {
            "type" : "date"
          },
          "id" : {
            "type" : "long"
          }
        }
      }
    }
  }
}

How to get

from elasticsearch_dsl import Search

body = {
    "size": 0,
    "aggs": {
        "group_by_state": {
            "nested": {
                "path": "annotate.data"
            },      
            "aggs":{
                "tagging":{
                    "terms": {
                        "field": "annotate.data.people.name",
                    }       
                }       
            }       
        }       
    }
}

s = Search.from_dict(body)
response = s.execute()

Result

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 3,
    "max_score" : 0.0,
    "hits" : [ ]
  },
  "aggregations" : {
    "group_by_state" : {
      "doc_count" : 15,
      "tagging" : {
        "doc_count_error_upper_bound" : 0,
        "sum_other_doc_count" : 0,
        "buckets" : [
          {
            "key" : "John",
            "doc_count" : 2
          },
          {
            "key" : "Yamada",
            "doc_count" : 9
          },
          {
            "key" : "Lisa",
            "doc_count" : 1
          },
          {
            "key" : "Bob",
            "doc_count" : 3
          }
        ]
      }
    }
  }
}

By the way..

I had faced trouble because of mistake of schema before.
In detail, way of using "nested".
Official document says

Complex datatypesedit

Array datatype

　　Array support does not require a dedicated type

Object datatype

　　object for single JSON objects

Nested datatype

　　nested for arrays of JSON objects

I had used schema like below

{
  "index_name" : {
    "mappings" : {
      "index_name" : {
        "dynamic" : "strict",
        "_all" : {
          "enabled" : false
        },
        "properties" : {
          "annotate" : {
            "type": "nested", # oops
            "properties" : {
              "data" : {
                "type" : "nested",
                "properties" : {
                  "people" : {
                    "type": "nested", # oops
                    "properties" : {
                      "name" : {
                        "type" : "keyword"
                      }
                    }
                  }
                }
              }
            }
          },
          "created_at" : {
            "type" : "date"
          },
          "id" : {
            "type" : "long"
          }
        }
      }
    }
  }
}

Refs

Field datatypes | Elasticsearch Reference [6.3] | Elastic
Search DSL — Elasticsearch DSL 6.2.1 documentation