measure aggregate function
Applies to: 
Databricks SQL 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
- measure_column: A reference to a measure column in a metric view.
Returns
A value of the type of measure_column.
Examples
SQL
-- 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