Measure properties

Measures are the business metrics that calculate a value for a model. Here are a few examples of measures:

• total_rows compiles to count(*),
• unique_users compiles count(distinct user_id) in SQL.

Measure Fields

dimension: | column: | sql:

One of dimension, column, and sql should be set in order to define the measures under model.meta.rakam.measures. If it's not set, the measure simply counts the all rows (i.e. count(*)). Here are a few examples:

models:
   - name: events
     meta:
        rakam:
          measures:
				total_rows:
				   aggregation: count
				unique_users:
				   aggregation: count_unique
				   dimension: user_id
				unique_users_total_rows_ratio:
				   sql: {{measure.total_rows}}/{{measure.unique_users}}

Please note that these fields are not required under column.meta as they point to the relevant column.

column: references the column in the model target.

dimension: references the dimensions within the same model.

sql: lets you define complex expression, where column type measure is not capable of.
For referencing other entities inside a measure checkout the SQL Context.

aggregation:

The aggregation function that will be applied to to the measure value dimension | column | sql.

Here are the valid values:

count, count_unique, sum, minimum, maximum, average, approximate_unique

total_users:
  dimension: 'user_id'
  aggregation: approximate_unique

aggregation is not required if the sql is defined. Here is an example:

total_events_user_ratio:
	sql: {{measure.total_rows}} / {{measure.total_users}} 

filters:

You can restrict a measure to aggregate only certain dimension values, without applying a filter to an entire query. Here is an example:

event_last_week:
   aggregation: count
   filters: [{dimension: occurred_at, value: 1 week, operator: between}]

The measure above compiles to the following SQL expression:

COUNT(CASE WHEN WEEK(now(), occurred_at) < 1 THEN NULL ELSE 1)