OpenSearch/docs/reference/aggregations/metrics/sum-aggregation.asciidoc

[[search-aggregations-metrics-sum-aggregation]]
=== Sum Aggregation

A `single-value` metrics aggregation that sums up numeric values that are extracted from the aggregated documents.
These values can be extracted either from specific numeric or <<histogram,histogram>> fields in the documents,
or be generated by a provided script.

Assuming the data consists of documents representing sales records we can sum
the sale price of all hats with:

[source,console]
--------------------------------------------------
POST /sales/_search?size=0
{
    "query" : {
        "constant_score" : {
            "filter" : {
                "match" : { "type" : "hat" }
            }
        }
    },
    "aggs" : {
        "hat_prices" : { "sum" : { "field" : "price" } }
    }
}
--------------------------------------------------
// TEST[setup:sales]

Resulting in:

[source,console-result]
--------------------------------------------------
{
    ...
    "aggregations" : {
        "hat_prices" : {
           "value" : 450.0
        }
    }
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]

The name of the aggregation (`hat_prices` above) also serves as the key by which the aggregation result can be retrieved from the returned response.

==== Script

We could also use a script to fetch the sales price:

[source,console]
--------------------------------------------------
POST /sales/_search?size=0
{
    "query" : {
        "constant_score" : {
            "filter" : {
                "match" : { "type" : "hat" }
            }
        }
    },
    "aggs" : {
        "hat_prices" : {
            "sum" : {
                "script" : {
                   "source": "doc.price.value"
                }
            }
        }
    }
}
--------------------------------------------------
// TEST[setup:sales]

This will interpret the `script` parameter as an `inline` script with the `painless` script language and no script parameters. To use a stored script use the following syntax:

[source,console]
--------------------------------------------------
POST /sales/_search?size=0
{
    "query" : {
        "constant_score" : {
            "filter" : {
                "match" : { "type" : "hat" }
            }
        }
    },
    "aggs" : {
        "hat_prices" : {
            "sum" : {
                "script" : {
                    "id": "my_script",
                    "params" : {
                        "field" : "price"
                    }
                }
            }
        }
    }
}
--------------------------------------------------
// TEST[setup:sales,stored_example_script]

===== Value Script

It is also possible to access the field value from the script using `_value`.
For example, this will sum the square of the prices for all hats:

[source,console]
--------------------------------------------------
POST /sales/_search?size=0
{
    "query" : {
        "constant_score" : {
            "filter" : {
                "match" : { "type" : "hat" }
            }
        }
    },
    "aggs" : {
        "square_hats" : {
            "sum" : {
                "field" : "price",
                "script" : {
                    "source": "_value * _value"
                }
            }
        }
    }
}
--------------------------------------------------
// TEST[setup:sales]

==== Missing value

The `missing` parameter defines how documents that are missing a value should
be treated. By default documents missing the value will be ignored but it is
also possible to treat them as if they had a value. For example, this treats
all hat sales without a price as being `100`.

[source,console]
--------------------------------------------------
POST /sales/_search?size=0
{
    "query" : {
        "constant_score" : {
            "filter" : {
                "match" : { "type" : "hat" }
            }
        }
    },
    "aggs" : {
        "hat_prices" : {
            "sum" : {
                "field" : "price",
                "missing": 100 <1>
            }
        }
    }
}
--------------------------------------------------
// TEST[setup:sales]

[[search-aggregations-metrics-sum-aggregation-histogram-fields]]
==== Histogram fields

When the sums are computed on <<histogram,histogram fields>>, the result of the aggregation is the sum of all elements in the `values`
array multiplied by the number in the same position in the `counts` array.

For example, if we have the following index that stores pre-aggregated histograms with latency metrics for different networks:

[source,console]
--------------------------------------------------
PUT metrics_index/_doc/1
{
  "network.name" : "net-1",
  "latency_histo" : {
      "values" : [0.1, 0.2, 0.3, 0.4, 0.5], <1>
      "counts" : [3, 7, 23, 12, 6] <2>
   }
}

PUT metrics_index/_doc/2
{
  "network.name" : "net-2",
  "latency_histo" : {
      "values" :  [0.1, 0.2, 0.3, 0.4, 0.5], <1>
      "counts" : [8, 17, 8, 7, 6] <2>
   }
}

POST /metrics_index/_search?size=0
{
    "aggs" : {
        "total_latency" : { "sum" : { "field" : "latency_histo" } }
    }
}
--------------------------------------------------

For each histogram field the sum aggregation will multiply each number in the `values` array <1> multiplied with its associated count
in the `counts` array <2>. Eventually, it will add all values for all histograms and return the following result:

[source,console-result]
--------------------------------------------------
{
    ...
    "aggregations" : {
        "total_latency" : {
           "value" : 28.8
        }
    }
}
--------------------------------------------------
// TESTRESPONSE[skip:test not setup]