elasticsearch/docs/reference/aggregations/search-aggregations-metrics-sum-aggregation.md
Colleen McGinnis 9bcd59596d
[docs] Prepare for docs-assembler (#125118)
* reorg files for docs-assembler and create toc.yml files

* fix build error, add redirects

* only toc

* move images
2025-03-20 12:09:12 -05:00

164 lines
3.7 KiB
Markdown

---
navigation_title: "Sum"
mapped_pages:
- https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-sum-aggregation.html
---
# Sum aggregation [search-aggregations-metrics-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](/reference/elasticsearch/mapping-reference/histogram.md) fields.
Assuming the data consists of documents representing sales records we can sum the sale price of all hats with:
```console
POST /sales/_search?size=0
{
"query": {
"constant_score": {
"filter": {
"match": { "type": "hat" }
}
}
},
"aggs": {
"hat_prices": { "sum": { "field": "price" } }
}
}
```
Resulting in:
```console-result
{
...
"aggregations": {
"hat_prices": {
"value": 450.0
}
}
}
```
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 [_script_14]
If you need to get the `sum` for something more complex than a single field, run the aggregation on a [runtime field](docs-content://manage-data/data-store/mapping/runtime-fields.md).
```console
POST /sales/_search?size=0
{
"runtime_mappings": {
"price.weighted": {
"type": "double",
"script": """
double price = doc['price'].value;
if (doc['promoted'].value) {
price *= 0.8;
}
emit(price);
"""
}
},
"query": {
"constant_score": {
"filter": {
"match": { "type": "hat" }
}
}
},
"aggs": {
"hat_prices": {
"sum": {
"field": "price.weighted"
}
}
}
}
```
## Missing value [_missing_value_17]
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`.
```console
POST /sales/_search?size=0
{
"query": {
"constant_score": {
"filter": {
"match": { "type": "hat" }
}
}
},
"aggs": {
"hat_prices": {
"sum": {
"field": "price",
"missing": 100
}
}
}
}
```
## Histogram fields [search-aggregations-metrics-sum-aggregation-histogram-fields]
When sum is computed on [histogram fields](/reference/elasticsearch/mapping-reference/histogram.md), 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, for the following index that stores pre-aggregated histograms with latency metrics for different networks:
```console
PUT metrics_index
{
"mappings": {
"properties": {
"latency_histo": { "type": "histogram" }
}
}
}
PUT metrics_index/_doc/1?refresh
{
"network.name" : "net-1",
"latency_histo" : {
"values" : [0.1, 0.2, 0.3, 0.4, 0.5],
"counts" : [3, 7, 23, 12, 6]
}
}
PUT metrics_index/_doc/2?refresh
{
"network.name" : "net-2",
"latency_histo" : {
"values" : [0.1, 0.2, 0.3, 0.4, 0.5],
"counts" : [8, 17, 8, 7, 6]
}
}
POST /metrics_index/_search?size=0&filter_path=aggregations
{
"aggs" : {
"total_latency" : { "sum" : { "field" : "latency_histo" } }
}
}
```
For each histogram field, the `sum` aggregation will add each number in the `values` array, multiplied by its associated count in the `counts` array.
Eventually, it will add all values for all histograms and return the following result:
```console-result
{
"aggregations": {
"total_latency": {
"value": 28.8
}
}
}
```