Ratio metrics

Ratio allows you to create a ratio between two metrics. You simply specify a numerator and a denominator metric. Additionally, you can apply a dimensional filter to both the numerator and denominator using a constraint string when computing the metric.

The parameters, description, and type for ratio metrics are:

Parameter	Description	Required	Type
name	The name of the metric.	Required	String
description	The description of the metric.	Optional	String
type	The type of the metric (cumulative, derived, ratio, or simple).	Required	String
label	Defines the display value in downstream tools. Accepts plain text, spaces, and quotes (such as orders_total or "orders_total").	Required	String
type_params	The type parameters of the metric.	Required	Dict
numerator	The name of the metric used for the numerator, or structure of properties.	Required	String or dict
denominator	The name of the metric used for the denominator, or structure of properties.	Required	String or dict
filter	Optional filter for the numerator or denominator.	Optional	String
alias	Optional alias for the numerator or denominator.	Optional	String

The following displays the complete specification for ratio metrics, along with an example.

models/metrics/file_name.yml

metrics:
  - name: The metric name # Required
    description: the metric description # Optional
    type: ratio # Required
    label: String that defines the display value in downstream tools. (such as orders_total or "orders_total") #Required
    type_params: # Required
      numerator: The name of the metric used for the numerator, or structure of properties # Required
        name: Name of metric used for the numerator # Required
        filter: Filter for the numerator # Optional
        alias: Alias for the numerator # Optional
      denominator: The name of the metric used for the denominator, or structure of properties # Required
        name: Name of metric used for the denominator # Required
        filter: Filter for the denominator # Optional
        alias: Alias for the denominator # Optional

For advanced data modeling, you can use fill_nulls_with and join_to_timespine to set null metric values to zero, ensuring numeric values for every data row.

Ratio metrics example

These examples demonstrate how to create ratio metrics in your model. They cover basic and advanced use cases, including applying filters to the numerator and denominator metrics.

Example 1

This example is a basic ratio metric that calculates the ratio of food orders to total orders:

models/metrics/file_name.yml

metrics:
  - name: food_order_pct
    description: "The food order count as a ratio of the total order count"
    label: Food order ratio
    type: ratio
    type_params: 
      numerator: food_orders
      denominator: orders

Example 2

This example is a ratio metric that calculates the ratio of food orders to total orders, with a filter and alias applied to the numerator. Note that in order to add these attributes, you'll need to use an explicit key for the name attribute too.

models/metrics/file_name.yml

metrics:
  - name: food_order_pct
    description: "The food order count as a ratio of the total order count, filtered by location"
    label: Food order ratio by location
    type: ratio
    type_params:
      numerator:
        name: food_orders
        filter: location = 'New York'
        alias: ny_food_orders
      denominator:
        name: orders
        filter: location = 'New York'
        alias: ny_orders

Ratio metrics using different semantic models

The system will simplify and turn the numerator and denominator into a ratio metric from different semantic models by computing their values in sub-queries. It will then join the result set based on common dimensions to calculate the final ratio. Here's an example of the SQL generated for such a ratio metric.

select
  subq_15577.metric_time as metric_time,
  cast(subq_15577.mql_queries_created_test as double) / cast(nullif(subq_15582.distinct_query_users, 0) as double) as mql_queries_per_active_user
from (
  select
    metric_time,
    sum(mql_queries_created_test) as mql_queries_created_test
  from (
    select
      cast(query_created_at as date) as metric_time,
      case when query_status in ('PENDING','MODE') then 1 else 0 end as mql_queries_created_test
    from prod_dbt.mql_query_base mql_queries_test_src_2552 
  ) subq_15576
  group by
    metric_time
) subq_15577
inner join (
  select
    metric_time,
    count(distinct distinct_query_users) as distinct_query_users
  from (
    select
      cast(query_created_at as date) as metric_time,
      case when query_status in ('MODE','PENDING') then email else null end as distinct_query_users
    from prod_dbt.mql_query_base mql_queries_src_2585 
  ) subq_15581
  group by
    metric_time
) subq_15582
on
  (
    (
      subq_15577.metric_time = subq_15582.metric_time
    ) or (
      (
        subq_15577.metric_time is null
      ) and (
        subq_15582.metric_time is null
      )
    )
  )

Add filter

Users can define constraints on input metrics for a ratio metric by applying a filter directly to the input metric, like so:

models/metrics/file_name.yml

metrics:
  - name: frequent_purchaser_ratio
    description: Fraction of active users who qualify as frequent purchasers
    type: ratio
    type_params:
      numerator:
        name: distinct_purchasers
        filter: |
          {{Dimension('customer__is_frequent_purchaser')}}
        alias: frequent_purchasers
      denominator:
        name: distinct_purchasers

Note the filter and alias parameters for the metric referenced in the numerator.

• Use the filter parameter to apply a filter to the metric it's attached to.
• The alias parameter is used to avoid naming conflicts in the rendered SQL queries when the same metric is used with different filters.
• If there are no naming conflicts, the alias parameter can be left out.

Related docs

• Fill null values for simple, derived, or ratio metrics