Window Functions
The CData Virtuality Server supports ANSI SQL 2003 window functions. A window function allows an aggregate function to be applied to a subset of the result set without the need for a GROUP BY
clause. A window function is similar to an aggregate function, but requires the use of an OVER
clause or window specification.
Usage
aggregate|ranking OVER ([PARTITION BY ...] [ORDER BY ...] [<FRAME-CLAUSE>])
aggregate can be any aggregate function. Ranking can be one of
ROW_NUMBER()
, RANK()
, DENSE_RANK()
.
Syntax Rules
- Window functions can only appear in the
SELECT
andORDER BY
clauses of a query expression; - Window functions cannot be nested in one another;
- Partitioning and order by expressions cannot contain subqueries or outer references;
- The ranking (
ROW_NUMBER
,RANK
,DENSE_RANK
) functions require the use of the window specificationORDER BY
clause; - An
XMLAGG ORDER BY
clause cannot be used when windowed; - The window specification
ORDER BY
clause cannot reference alias names or use positional ordering; - Windowed aggregates may not use
DISTINCT
if the window specification is ordered; - The Frame Clause can only be used in combination with the Partition Clause (at least one of
PARTITION BY
orORDER BY
should be present).
Frame Clause
The frame clause allows the user to specify a dynamic group of rows, or a range, inside the partition (analogous to a sliding frame in a window). It can be used in two ways:
[ RANGE | ROWS ] frame_start
[ RANGE | ROWS ] BETWEEN frame_start AND frame_end
Where frame_start and frame_end can be one of:
UNBOUNDED PRECEDING
value PRECEDING (ROWS only)
CURRENT ROW
value FOLLOWING (ROWS only)
UNBOUNDED FOLLOWING
Restrictions are that frame_start cannot be UNBOUNDED FOLLOWING
, frame_end cannot be UNBOUNDED PRECEDING
, and the frame_end choice cannot appear earlier in the above list than the frame_start choice. For example, RANGE BETWEEN CURRENT ROW AND
value PRECEDING
is not allowed.
Examples of Usage
Let us assume we have the following table called my_table
:
x | y |
---|---|
1 | 1 |
2 | 1 |
3 | 1 |
4 | 2 |
5 | 3 |
SELECT x, SUM(y) OVER (PARTITION BY y ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS window_column
FROM data_source.my_table;
-- Result:
-- |-----------|---------------|
-- | x | window_column |
-- |-----------|---------------|
-- | 1 | 1 |
-- | 2 | 2 |
-- | 3 | 3 |
-- | 4 | 2 |
-- | 5 | 3 |
-- |-----------|---------------|
SELECT x, COUNT(y) OVER (PARTITION BY y RANGE BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS window_column
FROM data_source.my_table;
-- Result:
-- |-----------|---------------|
-- | x | window_column |
-- |-----------|---------------|
-- | 1 | 3 |
-- | 2 | 3 |
-- | 3 | 3 |
-- | 4 | 1 |
-- | 5 | 1 |
-- |-----------|---------------|
SELECT x, y*100/SUM(y) OVER (PARTITION BY y RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS window_column
FROM data_source.my_table;
-- Result:
-- |-----------|---------------|
-- | x | window_column |
-- |-----------|---------------|
-- | 1 | 33 |
-- | 2 | 33 |
-- | 3 | 33 |
-- | 4 | 100 |
-- | 5 | 100 |
-- |-----------|---------------|
Function Definitions
Function | Description |
---|---|
ROW_NUMBER() | Functionally same as COUNT(*) with the same window specification. Assigns a number to each row in a partition starting at 1 |
RANK() | Assigns a number to each unique ordering value within each partition starting at 1, such that the next rank is equal to the count of prior rows |
DENSE_RANK() | Assigns a number to each unique ordering value within each partition starting at 1, such that the next rank is sequential |
LEAD(scalar_expression [, offset [, default]]) | Returns scalar_expression evaluated at the row that is offset rows before the current row within the partition; if there is no such row, instead returns default (which must be of the same type as scalar_expression ). Both offset and default are evaluated for the current row. If omitted, offset defaults to 1 and default to null |
LAG(scalar_expression [, offset [, default]]) | Returns scalar_expression evaluated at the row that is offset rows after the current row within the partition; if there is no such row, instead returns default (which must be of the same type as scalar_expression ). Both offset and default are evaluated for the current row. If omitted, offset defaults to 1 and default to null |
FIRST_VALUE(scalar_expression) | Returns scalar_expression evaluated at the row that is the first row of the window frame |
LAST_VALUE(scalar_expression) | Returns scalar_expression evaluated at the row that is the last row of the window frame |
Processing
Window functions are logically processed just before creating the output from the SELECT
clause. Window functions can use nested aggregates if a GROUP BY
clause is present. The is no guaranteed effect on the output ordering from the presence of window functions. The SELECT
statement must have an ORDER BY
clause to have a predictable ordering.
The CData Virtuality Server will process all window functions with the same window specification together. Generally, a full pass over the row values coming into the SELECT
clause will be required for each unique window specification. For each window specification, the values will be grouped according to the PARTITION BY
clause. If no PARTITION BY
clause is specified, the entire input is treated as a single partition. The output value is determined based upon the current row value, its peers (that is, rows that are the same with respect to their ordering), and all prior row values based upon ordering in the partition. The ROW_NUMBER
function will assign a unique value to every row regardless of the number of peers.
Example Windowed Results
SELECT name, salary, max(salary) over (partition by name) as max_sal,
rank() over (order by salary) as rank, dense_rank() over (order by salary) as dense_rank,
row_number() over (order by salary) as row_num
FROM data_source.employees
name | salary | max_sal | rank | dense_rank | row_num |
---|---|---|---|---|---|
John | 100000 | 100000 | 2 | 2 | 2 |
Henry | 50000 | 50000 | 5 | 4 | 5 |
John | 60000 | 100000 | 3 | 3 | 3 |
Suzie | 60000 | 150000 | 3 | 3 | 4 |
Suzie | 150000 | 150000 | 1 | 1 | 1 |
See Also
Duplicate Removal with ROW_NUMBER() and PARTITION to see how window functions can be used for removing duplicates