Window Aggregation

Window aggregations also support GROUPING SETS syntax. 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.

Window aggregations with GROUPING SETS require both the window_start and window_end columns have to be in the GROUP BY clause, but not in the GROUPING SETS clause.

Flink SQL> SELECT window_start, window_end, supplier_id, SUM(price) as price
  FROM TABLE(
    TUMBLE(TABLE Bid, DESCRIPTOR(bidtime), INTERVAL '10' MINUTES))
  GROUP BY window_start, window_end, GROUPING SETS ((supplier_id), ());
+------------------+------------------+-------------+-------+
|     window_start |       window_end | supplier_id | price |
+------------------+------------------+-------------+-------+
| 2020-04-15 08:00 | 2020-04-15 08:10 |      (NULL) | 11.00 |
| 2020-04-15 08:00 | 2020-04-15 08:10 |   supplier2 |  5.00 |
| 2020-04-15 08:00 | 2020-04-15 08:10 |   supplier1 |  6.00 |
| 2020-04-15 08:10 | 2020-04-15 08:20 |      (NULL) | 10.00 |
| 2020-04-15 08:10 | 2020-04-15 08:20 |   supplier2 |  9.00 |
| 2020-04-15 08:10 | 2020-04-15 08:20 |   supplier1 |  1.00 |
+------------------+------------------+-------------+-------+

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. For example, () in GROUPING SETS ((supplier_id), ()) in the preceding example is an empty sublist, and the supplier_id column in the corresponding result data is filled with NULL.

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.

For example, ROLLUP (one,two) is equivalent to GROUPING SET((one,two),(one),()).

Window aggregations with ROLLUP requires both the window_start and window_end columns have to be in the GROUP BY clause, but not in the ROLLUP clause.

For example, the following query is equivalent to the one above.

SELECT window_start, window_end, supplier_id, SUM(price) as price
FROM TABLE(
    TUMBLE(TABLE Bid, DESCRIPTOR(bidtime), INTERVAL '10' MINUTES))
GROUP BY window_start, window_end, ROLLUP (supplier_id);

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.

Window aggregations with CUBE requires both the window_start and window_end columns have to be in the GROUP BY clause, but not in the CUBE clause.

For example, the following two queries are equivalent.

SELECT window_start, window_end, item, supplier_id, SUM(price) as price
  FROM TABLE(
    TUMBLE(TABLE Bid, DESCRIPTOR(bidtime), INTERVAL '10' MINUTES))
  GROUP BY window_start, window_end, CUBE (supplier_id, item);

SELECT window_start, window_end, item, supplier_id, SUM(price) as price
  FROM TABLE(
    TUMBLE(TABLE Bid, DESCRIPTOR(bidtime), INTERVAL '10' MINUTES))
  GROUP BY window_start, window_end, GROUPING SETS (
      (supplier_id, item),
      (supplier_id      ),
      (             item),
      (                 )
)

The window_start and window_end columns are regular timestamp columns, not time attributes. Thus they can not be used as time attributes in subsequent time-based operations.

To propagate time attributes, you need to additionally add window_time column into GROUP BY clause. The window_time is the third column produced by Windowing Table-Valued Functions (Windowing TVFs) which is a time attribute of the assigned window. Adding window_time into GROUP BY clause makes window_time also to be group key that can be selected. Then following queries can use this column for subsequent time-based operations, such as cascading window aggregations and Window TopN.

The following shows a cascading window aggregation where the first window aggregation propagates the time attribute for the second window aggregation.

-- tumbling 5 minutes for each supplier_id
CREATE VIEW window1 AS
-- Note: The window start and window end fields of inner Window TVF are optional in the select clause. However, if they appear in the clause, they need to be aliased to prevent name conflicting with the window start and window end of the outer Window TVF.
SELECT window_start as window_5mintumble_start, window_end as window_5mintumble_end, window_time as rowtime, SUM(price) as partial_price
  FROM TABLE(
    TUMBLE(TABLE Bid, DESCRIPTOR(bidtime), INTERVAL '5' MINUTES))
  GROUP BY supplier_id, window_start, window_end, window_time;

-- tumbling 10 minutes on the first window
SELECT window_start, window_end, SUM(partial_price) as total_price
  FROM TABLE(
      TUMBLE(TABLE window1, DESCRIPTOR(rowtime), INTERVAL '10' MINUTES))
  GROUP BY window_start, window_end;