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[[search-aggregations-metrics-sum-aggregation]]
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=== Sum Aggregation
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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.
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Assuming the data consists of documents representing sales records we can sum
the sale price of all hats with:
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[source,console]
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--------------------------------------------------
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POST /sales/_search?size=0
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{
"query" : {
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"constant_score" : {
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"filter" : {
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"match" : { "type" : "hat" }
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}
}
},
"aggs" : {
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"hat_prices" : { "sum" : { "field" : "price" } }
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}
}
--------------------------------------------------
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// TEST[setup:sales]
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Resulting in:
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[source,console-result]
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--------------------------------------------------
{
...
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"aggregations" : {
"hat_prices" : {
"value" : 450.0
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}
}
}
--------------------------------------------------
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// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
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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.
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==== Script
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We could also use a script to fetch the sales price:
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[source,console]
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--------------------------------------------------
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POST /sales/_search?size=0
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{
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"query" : {
"constant_score" : {
"filter" : {
"match" : { "type" : "hat" }
}
}
},
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"aggs" : {
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"hat_prices" : {
"sum" : {
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"script" : {
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"source": "doc.price.value"
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}
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}
}
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}
}
--------------------------------------------------
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// TEST[setup:sales]
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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:
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[source,console]
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--------------------------------------------------
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POST /sales/_search?size=0
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{
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"query" : {
"constant_score" : {
"filter" : {
"match" : { "type" : "hat" }
}
}
},
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"aggs" : {
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"hat_prices" : {
"sum" : {
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"script" : {
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"id": "my_script",
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"params" : {
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"field" : "price"
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}
}
}
}
}
}
--------------------------------------------------
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// TEST[setup:sales,stored_example_script]
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===== Value Script
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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:
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[source,console]
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--------------------------------------------------
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POST /sales/_search?size=0
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{
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"query" : {
"constant_score" : {
"filter" : {
"match" : { "type" : "hat" }
}
}
},
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"aggs" : {
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"square_hats" : {
"sum" : {
"field" : "price",
"script" : {
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"source": "_value * _value"
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}
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}
}
}
}
--------------------------------------------------
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// TEST[setup:sales]
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==== Missing value
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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`.
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[source,console]
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--------------------------------------------------
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POST /sales/_search?size=0
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{
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"query" : {
"constant_score" : {
"filter" : {
"match" : { "type" : "hat" }
}
}
},
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"aggs" : {
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"hat_prices" : {
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"sum" : {
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"field" : "price",
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"missing": 100 <1>
}
}
}
}
--------------------------------------------------
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// TEST[setup:sales]
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[[search-aggregations-metrics-sum-aggregation-histogram-fields]]
==== Histogram fields
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When sum is computed on <<histogram,histogram fields>>, the result of the aggregation is the sum of all elements in the `values`
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array multiplied by the number in the same position in the `counts` array.
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For example, for the following index that stores pre-aggregated histograms with latency metrics for different networks:
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[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" } }
}
}
--------------------------------------------------
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For each histogram field the `sum` aggregation will multiply each number in the `values` array <1> multiplied by its associated count
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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]