Create Pricing Metric

post/pricing-metrics

Body ParametersExpand Collapse

aggregation: object { aggregation_type, value_field } or object { aggregation_type } or object { aggregation_type, value_field } or 2 more

The aggregation function used to compute the value of the pricing metric.

Accepts one of the following:

Sum = object { aggregation_type, value_field }

Computes the sum of the value_field over all usage events with the specified event_name.

aggregation_type: "sum"

Accepts one of the following:

"sum"

value_field: string

Field to sum over.

Count = object { aggregation_type }

Computes the number of usage events with the specified event_name.

aggregation_type: "count"

Accepts one of the following:

"count"

Max = object { aggregation_type, value_field }

Computes the max value of the value_field over all usage events with the specified event_name.

aggregation_type: "max"

Accepts one of the following:

"max"

value_field: string

Field to get the max value of.

Last = object { aggregation_type, value_field }

Computes the last value of the value_field over all usage events with the specified event_name.

aggregation_type: "last"

Accepts one of the following:

"last"

value_field: string

Field to get the last value of.

Custom = object { aggregation_type, custom_expression }

Custom aggregation for use cases not supported by the other aggregation types. Please email team@uselark.ai to enable this feature.

aggregation_type: "custom"

Accepts one of the following:

"custom"

custom_expression: string

Custom expression to compute the pricing metric. Please email team@uselark.ai to enable this feature.

event_name: string

The name of the event that the pricing metric is computed on.

name: string

The name of the pricing metric.

unit: string

Unit of measurement for the pricing metric.

dimensions: optional array of string

The dimensions by which the events are grouped to compute the pricing metric.

ReturnsExpand Collapse

PricingMetricResource = object { id, aggregation, event_name, 3 more }

id: string

The ID of the pricing metric.

aggregation: object { aggregation_type, value_field } or object { aggregation_type } or object { aggregation_type, value_field } or object { aggregation_type, value_field }

The aggregation function used to compute the value of the pricing metric.

Accepts one of the following:

Sum = object { aggregation_type, value_field }

aggregation_type: "sum"

Accepts one of the following:

"sum"

value_field: string

The field to sum over.

Count = object { aggregation_type }

aggregation_type: "count"

Accepts one of the following:

"count"

Max = object { aggregation_type, value_field }

aggregation_type: "max"

Accepts one of the following:

"max"

value_field: string

The field to get the max value of.

Last = object { aggregation_type, value_field }

aggregation_type: "last"

Accepts one of the following:

"last"

value_field: string

The field to get the last value of.

event_name: string

The event name that the pricing metric is computed on.

name: string

The name of the pricing metric.

unit: string

The unit of the value computed by the pricing metric.

dimensions: optional array of string

The dimensions by which the events are grouped to compute the pricing metric.

Create Pricing Metric

curl https://api.uselark.ai/pricing-metrics \
    -H 'Content-Type: application/json' \
    -H "X-API-Key: $LARK_API_KEY" \
    -d '{
          "aggregation": {
            "aggregation_type": "sum",
            "value_field": "compute_hours"
          },
          "event_name": "job_completed",
          "name": "Compute Hours",
          "unit": "hours"
        }'

{
  "id": "pmtr_GlX5Tcm2HOn00CoRTFxw2Amw",
  "aggregation": {
    "aggregation_type": "sum",
    "value_field": "compute_hours"
  },
  "event_name": "job_completed",
  "name": "Compute Hours",
  "unit": "hours",
  "dimensions": [
    "string"
  ]
}

Returns Examples

{
  "id": "pmtr_GlX5Tcm2HOn00CoRTFxw2Amw",
  "aggregation": {
    "aggregation_type": "sum",
    "value_field": "compute_hours"
  },
  "event_name": "job_completed",
  "name": "Compute Hours",
  "unit": "hours",
  "dimensions": [
    "string"
  ]
}