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161 changes: 145 additions & 16 deletions _aggregations/metric/stats.md
Original file line number Diff line number Diff line change
Expand Up @@ -9,37 +9,166 @@ redirect_from:

# Stats aggregations

The `stats` metric is a multi-value metric aggregation that returns all basic metrics such as `min`, `max`, `sum`, `avg`, and `value_count` in one aggregation query.
The `stats` aggregation is a multi-value metric aggregation that computes a summary of numeric data. This aggregation is useful for quick understanding of the distribution of a numeric fields. It can operate [directly on a field](#computing-stats-on-electricity-usage), apply a [script to derive the values](#using-a-script-to-compute-derived-values), or [handle documents with missing fields](#handling-documents-with-missing-fields). The `stats` aggregation returns five values:

The following example returns the basic stats for the `taxful_total_price` field:
* `count`: The number of values collected
* `min`: The lowest value
* `max`: The highest value
* `sum`: The total of all values
* `avg`: The average of the values (sum divided by count)


## Example

The following example computes `stats` aggregation on electricity usage.

### Computing stats on electricity usage

Create an index named `power_usage` and add documents where each document contains the number of kilowatt-hours (kWh) consumed during a given hour using the following request:

```json
PUT /power_usage/_bulk?refresh=true
{"index": {}}
{"device_id": "A1", "kwh": 1.2}
{"index": {}}
{"device_id": "A2", "kwh": 0.7}
{"index": {}}
{"device_id": "A3", "kwh": 1.5}
```
{% include copy-curl.html %}

To compute statistics on the `kwh` field across all documents, use the following aggregation request which suppresses document hits by setting `size` to `0`, and defines a `stats` aggregation named `consumption_stats` over the `kwh` field:
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I'm guessing setting to size to 0 isn't a hard requirement?

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@rishabhmaurya no, its just these docs are regarding aggregations, therefore its focusing on the aggs part


```json
GET /power_usage/_search
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it would be nice to also add an example to nested term aggregation having stats for each bucket.

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@rishabhmaurya thats added now

{
"size": 0,
"aggs": {
"consumption_stats": {
"stats": {
"field": "kwh"
}
}
}
}
```
{% include copy-curl.html %}

The response includes `count`, `min`, `max`, `avg`, and `sum` for the three values ingested:

```json
{
...
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"consumption_stats": {
"count": 3,
"min": 0.699999988079071,
"max": 1.5,
"avg": 1.1333333452542622,
"sum": 3.400000035762787
}
}
}
```

### Using a script to compute derived values

You can also use a script to compute the values used in the `stats` aggregation. This is useful when the metric is derived from document fields or requires transformation.

For example, if you want to convert kilowatt-hours to watt-hours before computing `stats` aggregation. Since `1 kWh` = `1000 Wh`, the can use the following request which utilizes a script to multiply the values by 1000. This aggregation uses the result of `doc['kwh'].value * 1000` as the input value for each document:

```json
GET opensearch_dashboards_sample_data_ecommerce/_search
GET /power_usage/_search
{
"size": 0,
"aggs": {
"stats_taxful_total_price": {
"usage_wh_stats": {
"stats": {
"field": "taxful_total_price"
"script": {
"source": "doc['kwh'].value * 1000"
}
}
}
}
}
```
{% include copy-curl.html %}

#### Example response
The `stats` aggregation returned in the response reflect values of `1200`, `700`, and `1500` watt-hours:

```json
...
"aggregations" : {
"stats_taxful_total_price" : {
"count" : 4675,
"min" : 6.98828125,
"max" : 2250.0,
"avg" : 75.05542864304813,
"sum" : 350884.12890625
{
...
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"usage_wh_stats": {
"count": 3,
"min": 699.999988079071,
"max": 1500,
"avg": 1133.3333452542622,
"sum": 3400.000035762787
}
}
}
}
```
```

### Using a value script with a field

When combining a field with a transformation, you can specify both `field` and `script`. This allows using the `_value` variable to reference the field’s value within the script.

The following example increases each energy reading by 5% before computing `stats` aggregation:

```json
GET /power_usage/_search
{
"size": 0,
"aggs": {
"adjusted_usage": {
"stats": {
"field": "kwh",
"script": {
"source": "_value * 1.05"
}
}
}
}
}
```
{% include copy-curl.html %}

### Handling documents with missing fields

If some documents do not contain the target field, they are excluded by default from the aggregation. To include them using a default value, you can specify the `missing` parameter.

The following request treats missing `kwh` values as `0.0`:

```json
GET /power_usage/_search
{
"size": 0,
"aggs": {
"consumption_with_default": {
"stats": {
"field": "kwh",
"missing": 0.0
}
}
}
}
```
{% include copy-curl.html %}