I've got a problem in SQL Server.
"Whate'er is well conceived is clearly said, And the words to say it flow with ease", Nicolas Boileau-Despreaux
Well, I don't think I'll be able to make it clear but I'll try ! And I'd like to apologize for my bad english !
I've got this table :
id ind lvl result date
1 1 a 3 2017-01-31
2 1 a 3 2017-02-28
3 1 a 1 2017-03-31
4 1 a 1 2017-04-30
5 1 a 1 2017-05-31
6 1 b 1 2017-01-31
7 1 b 3 2017-02-28
8 1 b 3 2017-03-31
9 1 b 1 2017-04-30
10 1 b 1 2017-05-31
11 2 a 3 2017-01-31
12 2 a 1 2017-02-28
13 2 a 3 2017-03-31
14 2 a 1 2017-04-30
15 2 a 3 2017-05-31
I'd like to count the number of month the combo {ind, lvl} remain in the result 1 before re-initializing the number of month to 0 if the result is not 1.
Clearly, I need to get something like that :
id ind lvl result date BadResultRemainsFor%Months
1 1 a 3 2017-01-31 0
2 1 a 3 2017-02-28 0
3 1 a 1 2017-03-31 1
4 1 a 1 2017-04-30 2
5 1 a 1 2017-05-31 3
6 1 b 1 2017-01-31 1
7 1 b 3 2017-02-28 0
8 1 b 3 2017-03-31 0
9 1 b 1 2017-04-30 1
10 1 b 1 2017-05-31 2
11 2 a 3 2017-01-31 0
12 2 a 1 2017-02-28 1
13 2 a 3 2017-03-31 0
14 2 a 1 2017-04-30 1
15 2 a 3 2017-05-31 0
So that if I was looking for the number of months the result was 1 for the date 2017-05-31 with the id 1 and the lvl a, I know it's been 3 months.
Assume all the date the the end day of month:
;WITH tb(id,ind,lvl,result,date) AS(
select 1,1,'a',3,'2017-01-31' UNION
select 2,1,'a',3,'2017-02-28' UNION
select 3,1,'a',1,'2017-03-31' UNION
select 4,1,'a',1,'2017-04-30' UNION
select 5,1,'a',1,'2017-05-31' UNION
select 6,1,'b',1,'2017-01-31' UNION
select 7,1,'b',3,'2017-02-28' UNION
select 8,1,'b',3,'2017-03-31' UNION
select 9,1,'b',1,'2017-04-30' UNION
select 10,1,'b',1,'2017-05-31' UNION
select 11,2,'a',3,'2017-01-31' UNION
select 12,2,'a',1,'2017-02-28' UNION
select 13,2,'a',3,'2017-03-31' UNION
select 14,2,'a',1,'2017-04-30' UNION
select 15,2,'a',3,'2017-05-31'
)
SELECT t.id,t.ind,t.lvl,t.result,t.date
,CASE WHEN t.isMatched=1 THEN ROW_NUMBER()OVER(PARTITION BY t.ind,t.lvl,t.id-t.rn ORDER BY t.id) ELSE 0 END
FROM (
SELECT t1.*,c.MonthDiff,CASE WHEN c.MonthDiff=t1.result THEN 1 ELSE 0 END AS isMatched
,CASE WHEN c.MonthDiff=t1.result THEN ROW_NUMBER()OVER(PARTITION BY t1.ind,t1.lvl,CASE WHEN c.MonthDiff=t1.result THEN 1 ELSE 0 END ORDER BY t1.id) ELSE null END AS rn
FROM tb AS t1
LEFT JOIN tb AS t2 ON t1.ind=t2.ind AND t1.lvl=t2.lvl AND t2.id=t1.id-1
CROSS APPLY(VALUES(ISNULL(DATEDIFF(MONTH,t2.date,t1.date),1))) c(MonthDiff)
) AS t
ORDER BY t.id
id ind lvl result date
----------- ----------- ---- ----------- ---------- --------------------
1 1 a 3 2017-01-31 0
2 1 a 3 2017-02-28 0
3 1 a 1 2017-03-31 1
4 1 a 1 2017-04-30 2
5 1 a 1 2017-05-31 3
6 1 b 1 2017-01-31 1
7 1 b 3 2017-02-28 0
8 1 b 3 2017-03-31 0
9 1 b 1 2017-04-30 1
10 1 b 1 2017-05-31 2
11 2 a 3 2017-01-31 0
12 2 a 1 2017-02-28 1
13 2 a 3 2017-03-31 0
14 2 a 1 2017-04-30 1
15 2 a 3 2017-05-31 0
By slightly tweaking your input data and slightly tweaking how we define the requirement, it becomes quite simple to produce the expected results.
First, we tweak your date values so that the only thing that varies is the month and year - the days are all the same. I've chosen to do that my adding 1 day to each value1. The fact that this produces results which are one month advanced doesn't matter here, since all values are similarly transformed, and so the monthly relationships stay the same.
Then, we introduce a numbers table - here, I've assumed a small fixed table is adequate. If it doesn't fit your needs, you can easily locate examples online for creating a large fixed numbers table that you can use for this query.
And, finally, we recast the problem statement. Instead of trying to count months, we instead ask "what's the smallest number of months, greater of equal to zero, that I need to go back from the current row, to locate a row with a non-1 result?". And so, we produce this query:
declare #t table (id int not null,ind int not null,lvl varchar(13) not null,
result int not null,date date not null)
insert into #t(id,ind,lvl,result,date) values
(1 ,1,'a',3,'20170131'), (2 ,1,'a',3,'20170228'), (3 ,1,'a',1,'20170331'),
(4 ,1,'a',1,'20170430'), (5 ,1,'a',1,'20170531'), (6 ,1,'b',1,'20170131'),
(7 ,1,'b',3,'20170228'), (8 ,1,'b',3,'20170331'), (9 ,1,'b',1,'20170430'),
(10,1,'b',1,'20170531'), (11,2,'a',3,'20170131'), (12,2,'a',1,'20170228'),
(13,2,'a',3,'20170331'), (14,2,'a',1,'20170430'), (15,2,'a',3,'20170531')
;With Tweaked as (
select
*,
DATEADD(day,1,date) as dp1d
from
#t
), Numbers(n) as (
select 0 union all select 1 union all select 2 union all select 3 union all select 4
union all
select 5 union all select 6 union all select 7 union all select 8 union all select 9
)
select
id, ind, lvl, result, date,
COALESCE(
(select MIN(n) from Numbers n1
inner join Tweaked t2
on
t2.ind = t1.ind and
t2.lvl = t1.lvl and
t2.dp1d = DATEADD(month,-n,t1.dp1d)
where
t2.result != 1
),
1) as [BadResultRemainsFor%Months]
from
Tweaked t1
The COALESCE is just there to deal with the edge case, such as for your 1,b data, where there is no previous row with a non-1 result.
Results:
id ind lvl result date BadResultRemainsFor%Months
----------- ----------- ------------- ----------- ---------- --------------------------
1 1 a 3 2017-01-31 0
2 1 a 3 2017-02-28 0
3 1 a 1 2017-03-31 1
4 1 a 1 2017-04-30 2
5 1 a 1 2017-05-31 3
6 1 b 1 2017-01-31 1
7 1 b 3 2017-02-28 0
8 1 b 3 2017-03-31 0
9 1 b 1 2017-04-30 1
10 1 b 1 2017-05-31 2
11 2 a 3 2017-01-31 0
12 2 a 1 2017-02-28 1
13 2 a 3 2017-03-31 0
14 2 a 1 2017-04-30 1
15 2 a 3 2017-05-31 0
1An alternative way to perform the adjustment is to use a DATEADD/DATEDIFF pair to perform a "floor" operation against the dates:
DATEADD(month,DATEDIFF(month,0,date),0) as dp1d
Which resets all of the date values to be the first of their own month rather than the following month. This may fell more "natural" to you, or you may already have such values available in your original data.
Assuming the dates are continously increasing in month, you can use window function like so:
select
t.id, ind, lvl, result, dat,
case when result = 1 then row_number() over (partition by grp order by id) else 0 end x
from (
select t.*,
dense_rank() over (order by e, result) grp
from (
select
t.*,
row_number() over (order by id) - row_number() over (partition by ind, lvl, result order by id) e
from your_table t
order by id) t ) t;
When I run a SQL query on a single table and here is the data (this is just a sample, error column might be more than 10)
time total Error
00:16 6 10000(E)
00:20 4 10000(E)
00:46 2 10000(E)
01:01 2 10000(E)
01:40 2 10000(E)
02:07 2 10000(E)
02:52 1 10000(E)
04:27 2 10000(E)
04:29 6 10000(E)
04:32 4 10000(E)
04:49 2 10000(E)
04:50 2 10000(E)
06:18 2 10000(E)
09:04 1 10000(E)
10:57 4 10000(E)
10:58 4 10000(E)
00:36 1 9401(E)
00:37 1 9401(E)
00:57 1 9401(E)
00:58 1 9401(E)
01:32 1 9401(E)
01:33 1 9401(E)
02:36 2 9401(E)
03:05 1 9401(E)
03:06 1 9401(E)
09:53 2 9401(E)
12:11 2 9401(E)
12:12 4 9401(E)
12:41 1 9401(E)
I want to write a SQL query so that I want to get the above data like this
time 10000(E) 9401(E)
---------------------------
00:16 6 0
00:20 4 0
00:36 0 1
00:37 0 1
00:46 2 0
00:57 0 1
00:58 0 1
01:01 2 0
01:32 0 1
01:33 0 1
01:40 2 0
02:07 2 0
02:36 0 2
02:52 1 0
03:05 0 1
03:06 0 1
04:27 2 0
04:29 6 0
04:32 4 0
04:49 2 0
04:50 2 0
06:18 2 0
09:04 1 0
09:53 0 1
10:57 4 0
10:58 4 0
12:11 0 2
12:12 0 4
12:41 0 1
is this possible??
Does this meet your requirement?
select e.time
, e.[10000(E)]
, e.[9401(E)]
from (
select time
, SUM(case when Error LIKE N'10000(E)' then Total else NULL end) as [10000(E)]
, null as [9401(E)]
from MyTable
where Error LIKE N'10000(E)'
group by time
union
select time
, null as [10000(E)]
, SUM(case when Error LIKE N'9401' then Total else NULL end) as [9401(E)]
from MyTable
where Error LIKE N'9401(E)'
group by time
) e
order by e.time
If no, please tell me about the result so that I can bring the righteous corrections.
The SUM function only comes to group the number of occurences of a same error into one given time, which seems to be what you have in your table, actually. So, it shouldn't modify any data. On the other hand, if you had two different records of the same error by the same time, then they should be grouped by this time and the total of occurences of this error will be additioned.
For your given in- and output it could be as simple as this.
SELECT *
FROM (
SELECT time
, [10000(E)] = Total
, [9401(E)] = 0
FROM YourTable
WHERE Error = '10000(E)'
UNION ALL
SELECT time
, [10000(E)] = 0
, [9401(E)] = Total
FROM YourTable
WHERE Error = '9401(E)'
) q
ORDER BY
time