Group Aggregation

DISTINCT Aggregation

Distinct aggregates remove duplicate values before applying an aggregation function. The following example counts the number of distinct order_ids instead of the total number of rows in the Orders table.

SELECT COUNT(DISTINCT order_id) FROM Orders

GROUPING SETS

Grouping sets allow for more complex grouping operations than those describable by a standard GROUP BY. Rows are grouped separately by each specified grouping set and aggregates are computed for each group just as for simple GROUP BY clauses.

Each sublist of GROUPING SETS may specify zero or more columns or expressions and is interpreted the same way as though used directly in the GROUP BY clause. An empty grouping set means that all rows are aggregated down to a single group, which is output even if no input rows were present.

References to the grouping columns or expressions are replaced by null values in result rows for grouping sets in which those columns do not appear.

SELECT supplier_id, rating, COUNT(*) AS total
FROM (VALUES
    ('supplier1', 'product1', 4),
    ('supplier1', 'product2', 3),
    ('supplier2', 'product3', 3),
    ('supplier2', 'product4', 4))
AS Products(supplier_id, product_id, rating)
GROUP BY GROUPING SETS ((supplier_id, rating), (supplier_id), ())

ROLLUP

ROLLUP is a shorthand notation for specifying a common type of grouping set. It represents the given list of expressions and all prefixes of the list, including the empty list.

SELECT supplier_id, rating, COUNT(*)
FROM (VALUES
    ('supplier1', 'product1', 4),
    ('supplier1', 'product2', 3),
    ('supplier2', 'product3', 3),
    ('supplier2', 'product4', 4))
AS Products(supplier_id, product_id, rating)
GROUP BY ROLLUP (supplier_id, rating)

CUBE

CUBE is a shorthand notation for specifying a common type of grouping set. It represents the given list and all of its possible subsets - the power set.

For example, the following two queries are equivalent.

SELECT supplier_id, rating, product_id, COUNT(*)
FROM (VALUES
    ('supplier1', 'product1', 4),
    ('supplier1', 'product2', 3),
    ('supplier2', 'product3', 3),
    ('supplier2', 'product4', 4))
AS Products(supplier_id, product_id, rating)
GROUP BY CUBE (supplier_id, rating, product_id)

SELECT supplier_id, rating, product_id, COUNT(*)
FROM (VALUES
    ('supplier1', 'product1', 4),
    ('supplier1', 'product2', 3),
    ('supplier2', 'product3', 3),
    ('supplier2', 'product4', 4))
AS Products(supplier_id, product_id, rating)
GROUP BY GROUPING SET (
    ( supplier_id, product_id, rating ),
    ( supplier_id, product_id         ),
    ( supplier_id,             rating ),
    ( supplier_id                     ),
    (              product_id, rating ),
    (              product_id         ),
    (                          rating ),
    (                                 )
)

HAVING

HAVING eliminates group rows that do not satisfy the condition. HAVING is different from WHERE: WHERE filters individual rows before the GROUP BY while HAVING filters group rows created by GROUP BY. Each column referenced in condition must unambiguously reference a grouping column unless it appears within an aggregate function.

The presence of HAVING turns a query into a grouped query even if there is no GROUP BY clause. It is the same as what happens when the query contains aggregate functions but no GROUP BY clause. The query considers all selected rows to form a single group, and the SELECT list and HAVING clause can only reference table columns from within aggregate functions. Such a query will emit a single row if the HAVING condition is true, zero rows if it is not true.

SELECT SUM(amount)
FROM Orders
GROUP BY users
HAVING SUM(amount) > 50