I have a big table like below:
id date count
1 201241 1
2 201241 2
3 201241 0
1 201242 5
2 201242 3
4 201242 4
3 201243 8
4 201243 2
...
How can I shift count column based on id and date columns.
id date shifted_count
1 201241 0
2 201241 0
3 201241 0
1 201242 1
2 201242 2
4 201242 0
3 201243 0
4 201243 4
...
I had some tries but they are incorrect:
;WITH CTE AS
(
SELECT count OVER(ORDER BY id , date ASC) shcount
FROM mytable
)
UPDATE mytable SET shifted_count = (SELECT shcount from CTE )
Related
Query: SELECT (row_number() OVER ()) as grp, * from tbl
Edit: the rows below are returned by a pgrouting shortest path function and it does have a sequence.
seq grp id
1 1 8
2 2 3
3 3 2
4 4 null
5 5 324
6 6 82
7 7 89
8 8 null
9 9 1
10 10 2
11 11 90
12 12 null
How do I make it so that the grp column is only incremented after a null value on id - and also keep the same order of rows
seq grp id
1 1 8
2 1 3
3 1 2
4 1 null
5 2 324
6 2 82
7 2 89
8 2 null
9 3 1
10 3 2
11 3 90
12 3 null
demo:db<>fiddle
Using a cumulative SUM aggregation is a possible approach:
SELECT
SUM( -- 2
CASE WHEN id IS NULL THEN 1 ELSE 0 END -- 1
) OVER (ORDER BY seq) as grp,
id
FROM mytable
If the current (ordered!) value is NULL, then make it 1, else 0. Now you got a bunch of zeros, delimited by a 1 at each NULL record. If you'd summerize these values cumulatively, at each NULL record, the sum increased.
Execution of the cumulative SUM() using window functions
This yields:
0 8
0 3
0 2
1 null
1 324
1 82
1 89
2 null
2 1
2 2
2 90
3 null
As you can see, the groups start with the NULL records, but you are expecting to end it.
This can be achieved by adding another window function: LAG(), which moves the records to the next row:
SELECT
SUM(
CASE WHEN next_id IS NULL THEN 1 ELSE 0 END
) OVER (ORDER BY seq) as grp,
id
FROM (
SELECT
LAG(id) OVER (ORDER BY seq) as next_id,
seq,
id
FROM mytable
) s
The result is your expected one:
1 8
1 3
1 2
1 null
2 324
2 82
2 89
2 null
3 1
3 2
3 90
3 null
I have a data (dt) in SQL like the following:
ID time_id act rd
11 1 1 1
11 2 4 1
11 3 7 0
12 1 8 1
12 2 2 0
12 3 4 1
12 4 3 1
12 5 4 1
13 1 4 1
13 2 1 0
15 1 3 1
16 1 8 0
16 2 8 0
16 3 8 0
16 4 8 0
16 5 8 0
and I want to take the subset of this data such that only ids (and their corresponding time_id, act, rd) that has time_id == 5 is retained. The desired output is the following
ID time_id act rd
12 1 8 1
12 2 2 0
12 3 4 1
12 4 3 1
12 5 4 1
16 1 8 0
16 2 8 0
16 3 8 0
16 4 8 0
16 5 8 0
I know I should use having clause somehow but have not been successful so far (returns me empty outputs). below is my attempt:
SELECT * FROM dt
GROUP BY ID
Having min(time_id) == 5;
This query:
select id from tablename where time_id = 5
returns all the ids that you want in the results.
Use it with the operator IN:
select *
from tablename
where id in (select id from tablename where time_id = 5)
You can use a correlated subquery with exists:
select t.*
from t
where exists (select 1 from t t2 where t2.id = t.id and t2.time_id = 5);
WITH temp AS
(
SELECT id FROM tab WHERE time_id = 5
)
SELECT * FROM tab t join temp tp on(t.id=tp.id);
check this query
select * from table t1 join (select distinct ID from table t where time_id = 5) t2 on t1.id =t2.id;
I have a series of Ids, some of them activate a product on certain month and that product remains activated for an X period of time, while others do not activate the product.
I want to create a column which indicates in which month the user activates the product or a NULL if the user doesn't activate it.
I've tried using a partition like the following:
SELECT id, fl_testdrive, month_dt,
CASE WHEN fl_testdrive = 1 then min(month_dt) OVER(PARTITION BY id ORDER BY month_dt ROWS UNBOUNDED PRECEDING) else 0 end as month_testdrive
FROM Table_1
However, when I try this solution, in the column month_testdrive, I do not obtain the first month in which the user appears, indepently of if he/she activated that product in that month or on a later one.
This is what I get with my query
Id flag_testdrive month_dt month_testdrive
1 0 1 1
1 0 2 1
1 1 3 1
1 1 4 1
2 0 2 0
2 0 3 0
3 1 4 4
3 1 5 4
What I'd expect:
Id flag_testdrive month_dt month_testdrive
1 0 1 3
1 0 2 3
1 1 3 3
1 1 4 3
2 0 2 0
2 0 3 0
3 1 4 4
3 1 5 4
This solution is a second best but is also fine:
Id flag_testdrive month_dt month_testdrive
1 0 1 0
1 0 2 0
1 1 3 3
1 1 4 3
2 0 2 0
2 0 3 0
3 1 4 4
3 1 5 4
You want CASE expression inside MIN():
MIN(CASE WHEN fl_testdrive = 1 THEN month_dt ELSE 0 END) OVER(PARTITION BY id, flag_testdrive ORDER BY month_dt ROWS UNBOUNDED PRECEDING)
Here's an option for you:
DECLARE #Testdate TABLE(
id INT
,flag_testdrive INT
,month_dt INT
)
INSERT INTO #Testdate (
[id]
, [flag_testdrive]
, [month_dt]
)
VALUES(1,0,1)
,(1,0,2)
,(1,1,3)
,(1,1,4)
,(2,0,2)
,(2,0,3)
,(3,1,4)
,(3,1,5)
SELECT
*
,COALESCE((SELECT MIN([aa].[month_dt]) FROM #Testdate aa
WHERE aa.[id] = a.id
AND aa.[flag_testdrive] = 1), 0) AS month_testdrive
FROM #Testdate a
Return the minimum month_dt for a given id only if flag_testdrive=1, wrapped in coalesce to return 0 instead of NULL.
We have a table like below in an sql server 2005 db:
event_id staff_id weeks
1 1 NNNYYYYNNYYY
1 2 YYYNNNYYYNNN
2 1 YYYYYYYYNYYY
This is from a piece of timetabling software and is basically saying which staff members are assigned to an event (register) and the set of weeks they are teaching that register. So staff_id 1 isn't teaching the first 3 weeks of event 1 but is teaching the following 4....
Is there an easy way to convert that to an easier form such as:
event_id staff_id week
1 1 4
1 1 5
1 1 6
1 1 7
1 1 10
1 1 11
1 1 12
1 2 1
1 2 2
1 2 3
1 2 7
1 2 8
1 2 9
2 1 1
2 1 2
2 1 3
2 1 4
2 1 5
2 1 6
2 1 7
2 1 8
2 1 10
2 1 11
2 1 12
WITH cte AS
(
SELECT 1 AS [week]
UNION ALL
SELECT [week] + 1
FROM cte
WHERE [week] < 53
)
SELECT t.event_id, t.staff_id, cte.[week]
FROM your_table AS t
INNER JOIN cte
ON LEN(ISNULL(t.weeks, '')) >= cte.[week]
AND SUBSTRING(t.weeks, cte.[week], 1) = 'Y'
ORDER BY t.event_id, t.staff_id, cte.[week]
Table name is Looupvalue
id Ptypefield Value
1 1 D
2 1 E
3 1 F
4 1 G
5 1 H
6 2 FL
7 2 IF
8 2 VVS1
9 2 VVS2
10 2 VS1
11 2 VS2
12 3 0.50
13 3 1.00
14 3 1.50
15 3 2.00
16 4 Marquise
17 4 Round
18 4 Pear
19 4 Radiant
20 4 Princess
Lookupvalue table value convert roow to column depends on ptypefield
Like
id 1 id 2 id 3 id 4
1 D 6 fl 12 0.50 16 Marquise
2 E 7 If 13 1 17 Round....
3 F 8 vvs2 14 1.5
4 G 9 vvs2 15 2
5 H 10 vs1
11 vs2
Thanks
In your sample output, it is not clear why values from columns 1 and 2 would be related to columns 3 and 4. However, here is a possible solution:
;With RowNumbers As
(
Select Id, PTypeField, Value
, Row_Number() Over( Partition By PTypeField Order By Id ) As Rownum
From #Test
)
Select RowNum
, Min( Case When PTypeField = 1 Then Id End ) As Id
, Min( Case When PTypeField = 1 Then Value End ) As [1]
, Min( Case When PTypeField = 2 Then Id End ) As Id
, Min( Case When PTypeField = 2 Then Value End ) As [2]
, Min( Case When PTypeField = 3 Then Id End ) As Id
, Min( Case When PTypeField = 3 Then Value End ) As [3]
, Min( Case When PTypeField = 4 Then Id End ) As Id
, Min( Case When PTypeField = 4 Then Value End ) As [4]
From RowNumbers
Group By RowNum
If you wanted to dynamically generate the columns, the only way to do that in SQL is to use some fugly dynamic SQL. T-SQL was not designed for this sort of output and instead you should use a reporting tool or do the crosstabbing in a middle tier component or class.
This data schema looks like an EAV which would explain why retrieving the data you want is so difficult.