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The implementation of the template bubble_sort assumed

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that the call-back comparison function returns a positive
number when arg1 < arg2, and a negative number when arg1 > arg2.
This is not in line with other implementation of sorting
algorithm.
Changed bubble_sort: now a negative result from the comparison
function means that arg1 < arg2, and positive result means
that arg1 > arg2.
Changed accordingly all call-back functions that are used as
parameters in the call of bubble_sort.

Added a test case to check the proper sorting of window functions.
This commit is contained in:
Igor Babaev
2016-04-01 12:00:54 -07:00
parent c9ff5cfbfd
commit 2e4bd4407e
7 changed files with 204 additions and 59 deletions
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75
mysql-test/r/win.result
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@@ -1505,3 +1505,78 @@ EXPLAIN
}
drop table t1;
drop table t0;
#
# Building ordering index for window functions
#
create table t1 (
pk int primary key,
a int,
b int,
c int
);
insert into t1 values
(101 , 0, 10, 1),
(102 , 0, 10, 2),
(103 , 1, 10, 3),
(104 , 1, 10, 4),
(108 , 2, 10, 5),
(105 , 2, 20, 6),
(106 , 2, 20, 7),
(107 , 2, 20, 8),
(109 , 4, 20, 9),
(110 , 4, 20, 10),
(111 , 5, NULL, 11),
(112 , 5, 1, 12),
(113 , 5, NULL, 13),
(114 , 5, NULL, 14),
(115 , 5, NULL, 15),
(116 , 6, 1, NULL),
(117 , 6, 1, 10),
(118 , 6, 1, 1),
(119 , 6, 1, NULL),
(120 , 6, 1, NULL),
(121 , 6, 1, NULL),
(122 , 6, 1, 2),
(123 , 6, 1, 20),
(124 , 6, 1, -10),
(125 , 6, 1, NULL),
(126 , 6, 1, NULL),
(127 , 6, 1, NULL);
select sum(b) over (partition by a order by b,pk
rows between unbounded preceding and current row) as c1,
avg(b) over (w1 rows between 1 preceding and 1 following) as c2,
sum(c) over (w2 rows between 1 preceding and 1 following) as c5,
avg(b) over (w1 rows between 5 preceding and 5 following) as c3,
sum(b) over (w1 rows between 1 preceding and 1 following) as c4
from t1
window w1 as (partition by a order by b,pk),
w2 as (partition by b order by c,pk);
c1 c2 c5 c3 c4
1 1.0000 42 1.0000 1
1 1.0000 NULL 1.0000 2
10 1.0000 NULL 1.0000 3
10 10.0000 3 10.0000 20
10 10.0000 9 10.0000 20
10 15.0000 9 17.5000 30
11 1.0000 NULL 1.0000 3
12 1.0000 -10 1.0000 2
2 1.0000 24 1.0000 3
20 10.0000 12 10.0000 20
20 10.0000 6 10.0000 20
20 20.0000 27 20.0000 40
3 1.0000 -7 1.0000 3
30 16.6667 13 17.5000 50
4 1.0000 NULL 1.0000 3
40 20.0000 19 20.0000 40
5 1.0000 NULL 1.0000 3
50 20.0000 21 17.5000 60
6 1.0000 NULL 1.0000 3
7 1.0000 13 1.0000 3
70 20.0000 24 17.5000 40
8 1.0000 32 1.0000 3
9 1.0000 -9 1.0000 3
NULL 1.0000 29 1.0000 1
NULL NULL 24 1.0000 NULL
NULL NULL 38 1.0000 NULL
NULL NULL 42 1.0000 NULL
drop table t1;