Elasticsearch API 06 - Executing Aggregations

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Executing Aggregations

The aggregations framework helps provide aggregated data based on a search query. It is based on simple building blocks called aggregations, that can be composed in order to build complex summaries of the data.

Structuring Aggregations

The following snippet captures the basic structure of aggregations:

"aggregations" : {
    "<aggregation_name>" : {
        "<aggregation_type>" : {
            <aggregation_body>
        }
        [,"meta" : {  [<meta_data_body>] } ]?
        [,"aggregations" : { [<sub_aggregation>]+ } ]?
    }
    [,"<aggregation_name_2>" : { ... } ]*
}

This example groups all the accounts by state, and then returns the top 10 (default) states sorted by count descending (also default):

POST localhost:9200/bank/_search?pretty
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state"
      }
    }
  }
}

In SQL, the above aggregation is similar in concept to:

SELECT state, COUNT(*) FROM bank GROUP BY state ORDER BY COUNT(*) DESC

Response:

"hits" : {
    "total" : 1000,
    "max_score" : 0.0,
    "hits" : [ ]
  },
  "aggregations" : {
    "group_by_state" : {
      "buckets" : [ {
        "key" : "al",
        "doc_count" : 21
      }, {
        "key" : "tx",
        "doc_count" : 17
      }, {
        "key" : "id",
        "doc_count" : 15
      }, {
        "key" : "ma",
        "doc_count" : 15
      }, {
        "key" : "md",
        "doc_count" : 15
      }, {
        "key" : "pa",
        "doc_count" : 15
      }, {
        "key" : "dc",
        "doc_count" : 14
      }, {
        "key" : "me",
        "doc_count" : 14
      }, {
        "key" : "mo",
        "doc_count" : 14
      }, {
        "key" : "nd",
        "doc_count" : 14
      } ]
    }
  }
}

Building on the previous aggregation, this example calculates the average account balance by state (again only for the top 10 states sorted by count in descending order):

POST localhost:9200/bank/_search?pretty
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state"
      },
      "aggs": {
        "average_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}

Building on the previous aggregation, let’s now sort on the average balance in descending order:

POST localhost:9200/bank/_search?pretty
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state",
        "order": {
          "average_balance": "desc"
        }
      },
      "aggs": {
        "average_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}

This example demonstrates how we can group by age brackets (ages 20-29, 30-39, and 40-49), then by gender, and then finally get the average account balance, per age bracket, per gender:

POST localhost:9200/bank/_search?pretty
{
  "size": 0,
  "aggs": {
    "group_by_age": {
      "range": {
        "field": "age",
        "ranges": [
          {
            "from": 20,
            "to": 30
          },
          {
            "from": 30,
            "to": 40
          },
          {
            "from": 40,
            "to": 50
          }
        ]
      },
      "aggs": {
        "group_by_gender": {
          "terms": {
            "field": "gender"
          },
          "aggs": {
            "average_balance": {
              "avg": {
                "field": "balance"
              }
            }
          }
        }
      }
    }
  }
}