Simple metrics
Simple metrics are metrics that directly reference a single measure, without any additional measures involved. They are aggregations over a column in your data platform and can be filtered by one or multiple dimensions.
The parameters, description, and type for simple metrics are:
tip
Note that we use the double colon (::) to indicate whether a parameter is nested within another parameter. So for example, query_params::metrics
means the metrics
parameter is nested under query_params
.
Parameter | Description | Type |
---|---|---|
name | The name of the metric. | Required |
description | The description of the metric. | Optional |
type | The type of the metric (cumulative, derived, ratio, or simple). | Required |
label | Required string that defines the display value in downstream tools. Accepts plain text, spaces, and quotes (such as orders_total or "orders_total" ). | Required |
type_params | The type parameters of the metric. | Required |
measure | A list of measure inputs | Required |
measure:name | The measure you're referencing. | Required |
measure:fill_nulls_with | Set the value in your metric definition instead of null (such as zero). | Optional |
measure:join_to_timespine | Boolean that indicates if the aggregated measure should be joined to the time spine table to fill in missing dates. Default false . | Optional |
The following displays the complete specification for simple metrics, along with an example.
metrics:
- name: The metric name # Required
description: the metric description # Optional
type: simple # Required
label: The value that will be displayed in downstream tools # Required
type_params: # Required
measure:
name: The name of your measure # Required
fill_nulls_with: Set value instead of null (such as zero) # Optional
join_to_timespine: true/false # Boolean that indicates if the aggregated measure should be joined to the time spine table to fill in missing dates. # 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.
Simple metrics example
metrics:
- name: customers
description: Count of customers
type: simple # Pointers to a measure you created in a semantic model
label: Count of customers
type_params:
measure:
name: customers # The measure you are creating a proxy of.
fill_nulls_with: 0
join_to_timespine: true
- name: large_orders
description: "Order with order values over 20."
type: SIMPLE
label: Large orders
type_params:
measure:
name: orders
filter: | # For any metric you can optionally include a filter on dimension values
{{Dimension('customer__order_total_dim')}} >= 20
Related docs
0