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SQL window functions for MySQL
- 1. Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SQL window functions for MySQL
Dag H. Wanvik
Senior database engineer,
Oracle
- 2. 2Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not
a commitment to deliver any material, code, or functionality, and should not be
relied upon in making purchasing decisions. The development, release, and
timing of any features or functionality described for Oracle’s products remains at
the sole discretion of Oracle.
- 3. 3Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Agenda
Quick intro to window functions
Types of window functions
The window specification
Evaluation and optimizations
More on non-aggregate wfs
Implicit and explicit windows
Q & A
1
2
3
4
5
6
7
- 4. 4Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Window functions: what are they?
●
A window function performs a calculation across a set of rows that are
related to the current row, similar to what can be done with an aggregate
function.
●
But unlike traditional aggregate functions, a window function does not
cause rows to become grouped into a single output row.
●
So, similar to normal function, but can access values of other rows “in
the vicinity” of the current row
- 5. 5Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id, salary,
SUM(salary) OVER (PARTITION BY department_id)
AS department_total
FROM employee
ORDER BY department_id, name;
Window function example, no frame
The OVER keyword
signals a window function
- 6. 6Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Partitions: 10, 20, 30
+---------+---------------+--------+------------------+
| name | department_id | salary | department_total |
+---------+---------------+--------+------------------+
| Newt | NULL | 75000 | 75000 |
| Dag | 10 | NULL | 370000 |
| Ed | 10 | 100000 | 370000 |
| Fred | 10 | 60000 | 370000 |
| Jon | 10 | 60000 | 370000 |
| Michael | 10 | 70000 | 370000 |
| Newt | 10 | 80000 | 370000 |
| Lebedev | 20 | 65000 | 130000 |
| Pete | 20 | 65000 | 130000 |
| Jeff | 30 | 300000 | 370000 |
| Will | 30 | 70000 | 370000 |
+---------+---------------+--------+------------------+
Partition == disjoint
set of rows in result set
Here: all rows in partition
are peers
- 7. 7Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id, salary,
SUM(salary) AS department_total
FROM employee GROUP BY department_id
ORDER BY department_id, name;
ERROR 1055 (42000): Expression #1 of SELECT list is not in GROUP BY clause and
contains nonaggregated column 'mysql.employee.name' which is not functionally dependent
on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_by
With GROUP BY
- 8. 8Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT /* name, */ department_id, /* salary,*/
SUM(salary) AS department_total
FROM employee GROUP BY department_id
ORDER BY department_id /*, name */;
+---------------+------------------+
| department_id | department_total |
+---------------+------------------+
| NULL | 75000 |
| 10 | 370000 |
| 20 | 130000 |
| 30 | 370000 |
+---------------+------------------+
With GROUP BY
- 9. 9Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id, salary,
SUM (salary) OVER (PARTITION BY department_id
ORDER BY name
ROWS 2 PRECEDING) total
FROM employee
ORDER BY department_id, name;
Window function example, frame
- 10. 10Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Partitions: 10, 20, 30
ORDER BY name
within each
partition
+---------+---------------+--------+--------+
| name | department_id | salary | total |
+---------+---------------+--------+--------+
| Newt | NULL | 75000 | 75000 |
| Dag | 10 | NULL | NULL |
| Ed | 10 | 100000 | 100000 |
| Fred | 10 | 60000 | 160000 |
| Jon | 10 | 60000 | 220000 |
| Michael | 10 | 70000 | 190000 |
| Newt | 10 | 80000 | 210000 |
| Lebedev | 20 | 65000 | 65000 |
| Pete | 20 | 65000 | 130000 |
| Jeff | 30 | 300000 | 300000 |
| Will | 30 | 70000 | 370000 |
+---------+---------------+--------+--------+
moving window frame:
SUM (salary)
...
ROWS 2 PRECEDING
a frame is a subset of a
partition
- 11. 11Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id, salary,
AVG(salary) OVER w AS `avg`,
salary - AVG(salary) OVER w AS diff FROM employee
WINDOW w as (PARTITION BY department_id)
ORDER BY diff DESC;
Window function example
i.e. find the employees with the largest difference between their wage
and that of the department average
Note: explicit window definition of “w”
- 12. 12Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Partitions: 10, 20, 30
+---------+---------------+--------+-----------+------------+
| name | department_id | salary | avg | diff |
+---------+---------------+--------+-----------+------------+
| Jeff | 30 | 300000 | 185000.00 | 115000.00 |
| Ed | 10 | 100000 | 74000.00 | 26000.00 |
| Newt | 10 | 80000 | 74000.00 | 6000.00 |
| Newt | NULL | 75000 | 75000.00 | 0.00 |
| Pete | 20 | 65000 | 65000.00 | 0.00 |
| Lebedev | 20 | 65000 | 65000.00 | 0.00 |
| Michael | 10 | 70000 | 74000.00 | -4000.00 |
| Jon | 10 | 60000 | 74000.00 | -14000.00 |
| Fred | 10 | 60000 | 74000.00 | -14000.00 |
| Will | 30 | 70000 | 185000.00 | -115000.00 |
| Dag | 10 | NULL | 74000.00 | NULL |
+---------+---------------+--------+-----------+------------+
- 13. 13Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Types of window functions
●
Aggregates
●
Ranking
●
Analytical
COUNT, SUM, AVG + more to come
RANK, DENSE_RANK, PERCENT_RANK,
CUME_DIST, ROW_NUMBER
NTILE, LEAD, LAG, NTH, FIRST_VALUE,
LAST_VALUE
Blue ones use frames, all obey partitions
- 14. 14Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Anatomy of a window specification
window specification ::=
[ existing window name ]
[PARTITION BY expr-1, ... ]
[ORDER BY expr-1, ... [DESC] ]
[ frame clause ]
–
- 15. 15Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
frame clause bound
partition
CURRENT ROW
UNBOUNDED
PRECEDING
UNBOUNDED
FOLLOWING
n PRECEDING
m PRECEDING
- 16. 16Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
frame clause
frame clause ::= { ROWS | RANGE } { start | between }
start ::= { CURRENT ROW | UNBOUNDED PRECEDING | n PRECEDING}
between ::= BETWEEN bound-1 AND bound-2
bound ::= start | UNBOUNDED FOLLOWING | n FOLLOWING
●
“start” form implies upper is CURRENT ROW (or its peer iff RANGE)
●
An empty OVER () specification, says that all rows in the partition are
peers and included in frame.
●
An ORDER BY without frame implies frame:
RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
●
Limitation: frame exclusion not supported
- 17. 17Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
frame clause
●
ROWS or RANGE (GROUPS unit not supported)
●
ROWS: bounds are physical row offsets
●
RANGE: logical offset based on current row's value
Ex: RANGE BETWEEN INTERVAL 1 WEEK PRECEDING AND CURRENT ROW
●
RANGE requires ORDER BY on one numeric expression
●
Limitation: bounds must be static
- 18. 18Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT dat, amount, SUM(amount) OVER w FROM payments
WINDOW w AS (ORDER BY dat RANGE
BETWEEN INTERVAL 1 WEEK PRECEDING AND
CURRENT ROW)
ORDER BY dat;
RANGE frame example
i.e. find the sum of payments within the last 7 days
- 19. 19Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
RANGE frame example
+------------+--------+--------+
| dat | amount | sum |
+------------+--------+--------+
| 2017-01-01 | 100.50 | 300.50 |
| 2017-01-01 | 200.00 | 300.50 |
| 2017-01-02 | 200.00 | 500.50 |
| 2017-01-03 | 200.00 | 700.50 |
| 2017-01-05 | 200.00 | 900.50 |
| 2017-01-10 | 200.00 | 700.00 |
| 2017-01-10 | 100.00 | 700.00 |
| 2017-01-11 | 200.00 | 700.00 |
+------------+--------+--------+
SELECT dat, amount,
SUM(amount) OVER w AS `sum` FROM payments
WINDOW w AS
(ORDER BY dat
RANGE BETWEEN INTERVAL 1 WEEK PRECEDING AND
CURRENT ROW)
ORDER BY dat;
Current row's date is the 10th
, so first row in range is the 3rd
.
Frame cardinality is 4 due to peer in next row.
For Jan 5, the frame cardinality is 5, and sum is 900.50.
- 20. 20Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
When are they evaluated?
●
after GROUP BY/ HAVING
●
before final ORDER BY, DISTINCT, LIMIT
●
you can have several window functions and several different
windows
●
To filter on wf's value, use a subquery, e.g.
SELECT * FROM (SELECT SUM(salary) OVER (PARTITION BY department_id) `sum`
FROM employee) AS s
WHERE `sum` < 100000;
+-------+
| sum |
+-------+
| 75000 |
+-------+
- 21. 21Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Logical flow
JOIN
GROUP
BY
WINDOW
1
WINDOW
n
ORDER BY/
DISTINCT/
LIMIT
Sort for
PARTITION BY
and
ORDER BY
● Tmp file between each windowing step
(in-mem if result set can fit †)
● Streamable wfs vs buffered
● Depends on wf and frame
● Buffered: re-read rows
● O(rows * frame size) optimize
● Move frame for SUM 1 row: invert by
subtraction, add new row.
† cf. variables tmp_table_size, max_heap_table_size
- 22. 22Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Streamable evaluation
SELECT name, department_id, salary,
SUM(salary) OVER (PARTITION BY department_id ORDER BY name
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS `sum`
FROM employee;
+---------+---------------+--------+--------+
| name | department_id | salary | sum |
+---------+---------------+--------+--------+
| Newt | NULL | 75000 | 75000 |
| Dag | 10 | NULL | NULL |
| Ed | 10 | 100000 | 100000 | Just accumulate as we see rows
| Fred | 10 | 60000 | 160000 |
| Jon | 10 | 60000 | 220000 |
| Michael | 10 | 70000 | 290000 |
| Newt | 10 | 80000 | 370000 |
| Lebedev | 20 | 65000 | 65000 |
| Pete | 20 | 65000 | 130000 |
| Jeff | 30 | 300000 | 300000 |
| Will | 30 | 70000 | 370000 |
+---------+---------------+--------+--------+
- 23. 23Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Logical flow
JOIN
GROUP
BY
WINDOW
1
WINDOW
n
ORDER BY/
DISTINCT/
LIMIT
Row
addressable
buffer
in-mem:
overflows to disk
Permits re-reading
rows when frame
moves
- 24. 24Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Non-streamable evaluation
SELECT name, department_id, salary,
SUM(salary) OVER (PARTITION BY department_id ORDER BY name
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS `sum`
FROM employee;
+---------+---------------+--------+--------+
| name | department_id | salary | sum |
+---------+---------------+--------+--------+
| Newt | NULL | 75000 | 75000 |
| Dag | 10 | NULL | NULL |
| Ed | 10 | 100000 | 100000 |
| Fred | 10 | 60000 | 160000 |
| Jon | 10 | 60000 | 220000 |
| Michael | 10 | 70000 | 190000 |
| Newt | 10 | 80000 | 210000 |
| Lebedev | 20 | 65000 | 65000 |
| Pete | 20 | 65000 | 130000 |
| Jeff | 30 | 300000 | 300000 |
| Will | 30 | 70000 | 370000 |
+---------+---------------+--------+--------+
When eval'ing Michael, subtract Ed's
contribution, add Michael
or just evaluate entire frame over again
(non-optimized). In both cases we need
re-visit rows.
- 25. 25Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Optimizations
●
Accumulate frames by inversion (discussed; done) ¹
●
Avoid materializing each step in temporary file if possible (done)
●
Sort only once for windows with the same PARTITION/ORDER BY
requirements (done)
●
Sort only once for windows with subset relation on above (not yet)
●
Eliminate sorts by using indexes (not yet)
¹not done by default for floats due to possible under/-overflow errors, but can be enabled using a variable.
Enabling it is crucial for performance for large frames due to the combinatorial hardness.
- 26. 26Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Explain, last query
EXPLAIN FORMAT=JSON SELECT name, department_id, salary,
SUM(salary) OVER (PARTITION BY department_id ORDER BY name
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS `sum`
FROM employee;
... "windows": [
{"name": "<unnamed window>",
"evalated as #": 1,
"using sorting": true,
"using temporary file": false,
"uses frame buffer": true,
"optimized frame evaluation": true,
"functions used": [
"sum" ]}
],
"buffer_result": {
:
- 27. 27Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
More on non-aggregate wfs
●
RANK, DENSE_RANK, PERCENT_RANK, CUME_DIST, ROW_NUMBER
●
LEAD, LAG, FIRST_VALUE, LAST_VALUE, NTH_VALUE
- 28. 28Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
RANK
SELECT name, department_id AS dept, salary,
RANK() OVER w AS `rank`
FROM employee
WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
+---------+------+--------+------+
| name | dept | salary | rank |
+---------+------+--------+------+
| Newt | NULL | 75000 | 1 |
| Ed | 10 | 100000 | 1 |
| Newt | 10 | 80000 | 2 |
| Fred | 10 | 70000 | 3 |
| Michael | 10 | 70000 | 3 |
| Jon | 10 | 60000 | 5 |
| Dag | 10 | NULL | 6 |
| Pete | 20 | 65000 | 1 |
| Lebedev | 20 | 65000 | 1 |
| Jeff | 30 | 300000 | 1 |
| Will | 30 | 70000 | 2 |
+---------+------+--------+------+
- 29. 29Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
DENSE_RANK
SELECT name, department_id AS dept, salary,
RANK() OVER w AS `rank`, DENSE_RANK() OVER w AS dense
FROM employee
WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
+---------+------+--------+------+-------+
| name | dept | salary | rank | dense |
+---------+------+--------+------+-------+
| Newt | NULL | 75000 | 1 | 1 |
| Ed | 10 | 100000 | 1 | 1 |
| Newt | 10 | 80000 | 2 | 2 |
| Fred | 10 | 70000 | 3 | 3 |
| Michael | 10 | 70000 | 3 | 3 |
| Jon | 10 | 60000 | 5 | 4 |
| Dag | 10 | NULL | 6 | 5 |
| Pete | 20 | 65000 | 1 | 1 |
| Lebedev | 20 | 65000 | 1 | 1 |
| Jeff | 30 | 300000 | 1 | 1 |
| Will | 30 | 70000 | 2 | 2 |
+---------+------+--------+------+-------+
DENSE_RANK doesn't skip
- 30. 30Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
ROW_NUMBER
SELECT name, department_id AS dept, salary,
RANK() OVER w AS `rank`, DENSE_RANK() OVER w AS dense,
ROW_NUMBER() OVER w AS `#`
FROM employee
WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
+---------+------+--------+------+-------+---+
| name | dept | salary | rank | dense | # |
+---------+------+--------+------+-------+---+
| Newt | NULL | 75000 | 1 | 1 | 1 |
| Ed | 10 | 100000 | 1 | 1 | 1 |
| Newt | 10 | 80000 | 2 | 2 | 2 |
| Fred | 10 | 70000 | 3 | 3 | 3 |
| Michael | 10 | 70000 | 3 | 3 | 4 |
| Jon | 10 | 60000 | 5 | 4 | 5 |
| Dag | 10 | NULL | 6 | 5 | 6 |
| Pete | 20 | 65000 | 1 | 1 | 1 |
| Lebedev | 20 | 65000 | 1 | 1 | 2 |
| Jeff | 30 | 300000 | 1 | 1 | 1 |
| Will | 30 | 70000 | 2 | 2 | 2 |
+---------+------+--------+------+-------+---+
- 31. 31Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
CUME_DIST
SELECT name, department_id AS dept, salary,
RANK() OVER w AS `rank`, DENSE_RANK() OVER w AS dense,
ROW_NUMBER() OVER w AS `#`, CUME_DIST() OVER w AS cume
FROM employee
WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
+---------+------+--------+------+-------+---+---------------------+
| name | dept | salary | rank | dense | # | cume |
+---------+------+--------+------+-------+---+---------------------+
| Newt | NULL | 75000 | 1 | 2 | 1 | 1 |
| Ed | 10 | 100000 | 1 | 2 | 1 | 0.16666666666666666 |
| Newt | 10 | 80000 | 2 | 3 | 2 | 0.3333333333333333 |
| Fred | 10 | 70000 | 3 | 4 | 3 | 0.6666666666666666 |
| Michael | 10 | 70000 | 3 | 4 | 4 | 0.6666666666666666 |
| Jon | 10 | 60000 | 5 | 5 | 5 | 0.8333333333333334 |
| Dag | 10 | NULL | 6 | 6 | 6 | 1 |
| Pete | 20 | 65000 | 1 | 2 | 1 | 1 |
| Lebedev | 20 | 65000 | 1 | 2 | 2 | 1 |
| Jeff | 30 | 300000 | 1 | 2 | 1 | 0.5 |
| Will | 30 | 70000 | 2 | 3 | 2 | 1 |
+---------+------+--------+------+-------+---+---------------------+
Cumulative distribution
“For a row R, if we assume ascending
ordering, CUME_DIST of R is the
number of rows with values <= the value
of R, divided by the number of rows
evaluated in the partition. “
- 32. 32Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
PERCENT_RANK
SELECT name, department_id AS dept, salary,
RANK() OVER w AS `rank`, DENSE_RANK() OVER w AS dense,
ROW_NUMBER() OVER w AS `#`, CUME_DIST() OVER w AS cume,
PERCENT_RANK() OVER w AS p_r
FROM employee WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
+---------+------+--------+------+-------+---+---------------------+-----+
| name | dept | salary | rank | dense | # | cume | p_r |
+---------+------+--------+------+-------+---+---------------------+-----+
| Newt | NULL | 75000 | 1 | 2 | 1 | 1 | 0 |
| Ed | 10 | 100000 | 1 | 2 | 1 | 0.16666666666666666 | 0 |
| Newt | 10 | 80000 | 2 | 3 | 2 | 0.3333333333333333 | 0.2 |
| Fred | 10 | 70000 | 3 | 4 | 3 | 0.6666666666666666 | 0.4 |
| Michael | 10 | 70000 | 3 | 4 | 4 | 0.6666666666666666 | 0.4 |
| Jon | 10 | 60000 | 5 | 5 | 5 | 0.8333333333333334 | 0.8 |
| Dag | 10 | NULL | 6 | 6 | 6 | 1 | 1 |
| Pete | 20 | 65000 | 1 | 2 | 1 | 1 | 0 |
| Lebedev | 20 | 65000 | 1 | 2 | 2 | 1 | 0 |
| Jeff | 30 | 300000 | 1 | 2 | 1 | 0.5 | 0 |
| Will | 30 | 70000 | 2 | 3 | 2 | 1 | 1 |
+---------+------+--------+------+-------+---+---------------------+-----+
(rank - 1) / (total rows - 1)
- 33. 33Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
NTILE
SELECT name, department_id AS dept, salary,
...
PERCENT_RANK() OVER w AS p_r, NTILE(3) OVER w AS `ntile`
FROM employee WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
+---------+------+--------+------+-------+---+---------------------+-----+-------+
| name | dept | salary | rank | dense | # | cume | p_r | ntile |
+---------+------+--------+------+-------+---+---------------------+-----+-------+
| Newt | NULL | 75000 | 1 | 2 | 1 | 1 | 0 | 1 |
| Ed | 10 | 100000 | 1 | 2 | 1 | 0.16666666666666666 | 0 | 1 |
| Newt | 10 | 80000 | 2 | 3 | 2 | 0.3333333333333333 | 0.2 | 1 |
| Fred | 10 | 70000 | 3 | 4 | 3 | 0.6666666666666666 | 0.4 | 2 |
| Michael | 10 | 70000 | 3 | 4 | 4 | 0.6666666666666666 | 0.4 | 2 |
| Jon | 10 | 60000 | 5 | 5 | 5 | 0.8333333333333334 | 0.8 | 3 |
| Dag | 10 | NULL | 6 | 6 | 6 | 1 | 1 | 3 |
| Pete | 20 | 65000 | 1 | 2 | 1 | 1 | 0 | 1 |
| Lebedev | 20 | 65000 | 1 | 2 | 2 | 1 | 0 | 2 |
| Jeff | 30 | 300000 | 1 | 2 | 1 | 0.5 | 0 | 1 |
| Will | 30 | 70000 | 2 | 3 | 2 | 1 | 1 | 2 |
+---------+------+--------+------+-------+---+---------------------+-----+-------+
Divides an ordered
partition into a
specified number of
groups aka buckets
and assigns a bucket
number to each row in
the partition.
- 34. 34Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
LEAD, LAG
Returns value evaluated at the row that is offset rows after/before the current row within the
partition; if there is no such row, instead return default (which must be of the same type as
value).
Both offset and default are evaluated with respect to the current row. If omitted, offset
defaults to 1 and default to null
lead or lag function ::= { LEAD | LAG } ( expr [ , offset [ , default expression>] ] )
[ RESPECT NULLS ]
Note: “IGNORE NULLS” not supported, RESPECT NULLS is default but can be specified.
- 35. 35Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
+---------+------+--------+-------+
| name | dept | salary | lead |
+---------+------+--------+-------+
| Newt | NULL | 75000 | NULL |
| Ed | 10 | 100000 | 80000 |
| Newt | 10 | 80000 | 70000 |
| Fred | 10 | 70000 | 70000 |
| Michael | 10 | 70000 | 60000 |
| Jon | 10 | 60000 | NULL |
| Dag | 10 | NULL | NULL |
| Pete | 20 | 65000 | 65000 |
| Lebedev | 20 | 65000 | NULL |
| Jeff | 30 | 300000 | 70000 |
| Will | 30 | 70000 | NULL |
+---------+------+--------+-------+
LEAD
SELECT name, department_id AS dept, salary,
LEAD(salary, 1) OVER w AS `lead`
FROM employee
WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
- 36. 36Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
+---------+------+--------+--------+-------+
| name | dept | salary | lag | lead |
+---------+------+--------+--------+-------+
| Newt | NULL | 75000 | NULL | NULL |
| Ed | 10 | 100000 | NULL | 80000 |
| Newt | 10 | 80000 | 100000 | 70000 |
| Fred | 10 | 70000 | 80000 | 70000 |
| Michael | 10 | 70000 | 70000 | 60000 |
| Jon | 10 | 60000 | 70000 | NULL |
| Dag | 10 | NULL | 60000 | NULL |
| Pete | 20 | 65000 | NULL | 65000 |
| Lebedev | 20 | 65000 | 65000 | NULL |
| Jeff | 30 | 300000 | NULL | 70000 |
| Will | 30 | 70000 | 300000 | NULL |
+---------+------+--------+--------+-------+
LAG
SELECT name, department_id AS dept, salary,
LAG(salary, 1) OVER w AS `lag`,
LEAD(salary, 1) OVER w AS `lead`
FROM employee
WINDOW w AS (PARTITION BY department_id
ORDER BY salary DESC);
- 37. 37Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
FIRST_VALUE, LAST_VALUE, NTH_VALUE
Returns value evaluated at the first, last, nth in the frame of the current row
within the partition; if there is no nth row (frame is too small), the NTH_VALUE
returns NULL.
first or last value ::= { FIRST_VALUE | LAST_VALUE } ( expr )
[ RESPECT NULLS ]
nth_value ::= NTH_VALUE ( expr, nth-row ) [FROM FIRST]
[ RESPECT NULLS ]
Note: “IGNORE NULLS” is not supported, RESPECT NULLS is used but can
be specified.
Note: For NTH_VALUE, “FROM LAST” is not supported, FROM FIRST is used
but can be specified
- 38. 38Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id AS dept, salary,
SUM(salary) OVER w AS `sum`,
FIRST_VALUE(salary) OVER w AS `first`
FROM employee WINDOW w AS (PARTITION BY department_id
ORDER BY name
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
+---------+------+--------+--------+--------+
| name | dept | salary | sum | first |
+---------+------+--------+--------+--------+
| Newt | NULL | 75000 | 75000 | 75000 |
| Dag | 10 | NULL | NULL | NULL |
| Ed | 10 | 100000 | 100000 | NULL |
| Fred | 10 | 60000 | 160000 | NULL |
| Jon | 10 | 60000 | 220000 | 100000 |
| Michael | 10 | 70000 | 190000 | 60000 |
| Newt | 10 | 80000 | 210000 | 60000 |
| Lebedev | 20 | 65000 | 65000 | 65000 |
| Pete | 20 | 65000 | 130000 | 65000 |
| Jeff | 30 | 300000 | 300000 | 300000 |
| Will | 30 | 70000 | 370000 | 300000 |
+---------+------+--------+--------+--------+
FIRST_VALUE “in frame”
Current row: Jon
FIRST_VALUE in frame is: Ed
- 39. 39Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id AS dept, salary,
SUM(salary) OVER w AS `sum`,
FIRST_VALUE(salary) OVER w AS `first`, LAST_VALUE(salary) OVER w AS `last`
FROM employee WINDOW w AS (PARTITION BY department_id
ORDER BY name
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
+---------+------+--------+--------+--------+--------+
| name | dept | salary | sum | first | last |
+---------+------+--------+--------+--------+--------+
| Newt | NULL | 75000 | 75000 | 75000 | 75000 |
| Dag | 10 | NULL | NULL | NULL | NULL |
| Ed | 10 | 100000 | 100000 | NULL | 100000 |
| Fred | 10 | 60000 | 160000 | NULL | 60000 |
| Jon | 10 | 60000 | 220000 | 100000 | 60000 |
| Michael | 10 | 70000 | 190000 | 60000 | 70000 |
| Newt | 10 | 80000 | 210000 | 60000 | 80000 |
| Lebedev | 20 | 65000 | 65000 | 65000 | 65000 |
| Pete | 20 | 65000 | 130000 | 65000 | 65000 |
| Jeff | 30 | 300000 | 300000 | 300000 | 300000 |
| Will | 30 | 70000 | 370000 | 300000 | 70000 |
+---------+------+--------+--------+--------+--------+
LAST_VALUE “in frame”
Current row: Jon
LAST_VALUE in frame is: Jon
- 40. 40Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
SELECT name, department_id AS dept, salary,
SUM(salary) OVER w AS `sum`,
NTH_VALUE(salary, 2) OVER w AS nth
FROM employee WINDOW w AS (PARTITION BY department_id
ORDER BY name
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
+---------+------+--------+--------+--------+
| name | dept | salary | sum | nth |
+---------+------+--------+--------+--------+
| Newt | NULL | 75000 | 75000 | NULL |
| Dag | 10 | NULL | NULL | NULL |
| Ed | 10 | 100000 | 100000 | 100000 |
| Fred | 10 | 60000 | 160000 | 100000 |
| Jon | 10 | 60000 | 220000 | 60000 |
| Michael | 10 | 70000 | 190000 | 60000 |
| Newt | 10 | 80000 | 210000 | 70000 |
| Lebedev | 20 | 65000 | 65000 | NULL |
| Pete | 20 | 65000 | 130000 | 65000 |
| Jeff | 30 | 300000 | 300000 | NULL |
| Will | 30 | 70000 | 370000 | 70000 |
+---------+------+--------+--------+--------+
NTH_VALUE “in frame”
Current row: Jon
NTH_VALUE(.., 2) in frame is: Fred
- 41. 41Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Implicit and explicit windows
●
Windows can be implicit and unnamed:
COUNT(*) OVER (PARTITION BY DEPARTMENT_ID)
●
Windows can be defined and named via the windows clause clause:
SELECT COUNT(*) OVER w FROM t
WINDOW w as (PARTITION BY department_id)
●
This allows easy sharing of windows between several window functions
and also avoids redundant windowing steps since more functions can be
evaluated in the same step.
●
Limitation: equivalent windows are not yet merged
- 42. 42Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Implicit and explicit windows
●
A window definition can inherit from another window definition in its
specification, adding detail (no override)
SELECT name, department_id,
COUNT(*) OVER w1 AS cnt1,
COUNT(*) over w2 AS cnt2 FROM employee
WINDOW w1 AS (PARTITION BY department_id),
w2 AS (w1 ORDER BY name)
ORDER BY department_id, name;
+---------+---------------+------+------+
| name | department_id | cnt1 | cnt2 |
+---------+---------------+------+------+
| Newt | NULL | 1 | 1 |
| Dag | 10 | 6 | 1 |
| Ed | 10 | 6 | 2 |
| Fred | 10 | 6 | 3 |
| Jon | 10 | 6 | 4 |
| Michael | 10 | 6 | 5 |
| Newt | 10 | 6 | 6 |
| Lebedev | 20 | 2 | 1 |
| Pete | 20 | 2 | 2 |
| Jeff | 30 | 2 | 1 |
| Will | 30 | 2 | 2 |
+---------+---------------+------+------+
- 43. 43Copyright © 2017 Oracle and/or its affiliates. All rights reserved.
Time-line
●
Work in progress, no due date yet