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measure aggregate function

Applies to: check marked yes Databricks SQL check marked yes Databricks Runtime 16.4 and above

Returns the measure_column aggregated from the values of a group.

Unlike a regular aggregate function like SUM, AVG, or COUNT, the MEASURE function does not specify the aggregation. It inherits the definition of the aggregation from the metric view definition.

Using a metric view with measures is superior to regular views because it abstracts the complexity of the underlying aggregations while giving the invoker the freedom to choose the grouping columns.

Syntax

measure ( measure_column )

This function cannot be invoked as a window function using the OVER clause.

Arguments

Returns

A value of the type of measure_column.

Examples

-- A metric view with a measure column 4 metric columns
CREATE OR REPLACE VIEW region_sales_metrics
  (month COMMENT 'Month order was made',
   status,
   order_priority,
   count_orders COMMENT 'Count of orders',
   total_Revenue,
   total_Revenue_p_Customer,
   total_revenue_for_open_orders)
  WITH METRICS
  LANGUAGE YAML
  COMMENT 'A metric view for regional sales metrics.'
  AS $$
   version: 0.1
   source: samples.tpch.orders
   filter: o_orderdate > '1990-01-01'
   dimensions:
   - name: month
     expr: date_trunc('MONTH', o_orderdate)
   - name: status
     expr: case
       when o_orderstatus = 'O' then 'Open'
       when o_orderstatus = 'P' then 'Processing'
       when o_orderstatus = 'F' then 'Fulfilled'
       end
   - name: order_priority
     expr: split(o_orderpriority, '-')[1]
   measures:
   - name: count_orders
     expr: count(1)
   - name: total_revenue
     expr: SUM(o_totalprice)
   - name: total_revenue_per_customer
     expr: SUM(o_totalprice) / count(distinct o_custkey)
   - name: total_revenue_for_open_orders
     expr: SUM(o_totalprice) filter (where o_orderstatus='O')
  $$;

-- Tracking total_revenue_per_customer by month in 1995
> SELECT extract(month from month) as month,
    measure(total_revenue_per_customer)::bigint AS total_revenue_per_customer
  FROM region_sales_metrics
  WHERE extract(year FROM month) = 1995
  GROUP BY ALL
  ORDER BY ALL;
  month	 total_revenue_per_customer
  -----  --------------------------
   1     167727
   2     166237
   3     167349
   4     167604
   5     166483
   6     167402
   7     167272
   8     167435
   9     166633
  10     167441
  11     167286
  12     167542

-- Tracking total_revenue_per_customer by month and status in 1995
> SELECT extract(month from month) as month,
    status,
    measure(total_revenue_per_customer)::bigint AS total_revenue_per_customer
  FROM region_sales_metrics
  WHERE extract(year FROM month) = 1995
  GROUP BY ALL
  ORDER BY ALL;
  month  status      total_revenue_per_customer
  -----  ---------   --------------------------
   1     Fulfilled   167727
   2     Fulfilled   161720
   2    Open          40203
   2    Processing   193412
   3    Fulfilled    121816
   3    Open          52424
   3    Processing   196304
   4    Fulfilled     80405
   4    Open          75630
   4    Processing   196136
   5    Fulfilled     53460
   5    Open         115344
   5    Processing   196147
   6    Fulfilled     42479
   6    Open         160390
   6    Processing   193461
   7    Open         167272
   8    Open         167435
   9    Open         166633
   10   Open         167441
   11   Open         167286
   12   Open         167542