I have a table like:
user_id operation amount
1 purchase 10
1 sale 40
2 purchase 100
2 sale 20
2 conversion 15
3 sale 70
4 conversion 40
given by the SQL query:
SELECT
user_id,
operation,
COUNT(item_num) AS amount
FROM MyTable
GROUP BY user_id, operation
I want to calculate, for each user, the percentage of the total amount for each operation and it would be nice to place them in the columns(actually dividing numbers):
user_id purchase sale conversion
1 10 /50 40 /50 0 /50
2 100 /135 20 /135 15 /135
3 0 /70 70 /70 0 /70
4 0 /40 0 /40 40 /40
EDIT:
Thanks to the intuition given in the responses, I was able to find the solution that suits me best
WITH result
AS
(
SELECT
[user_id],
[operation],
CAST(COUNT([item_num]) AS float) AS amount,
SUM(COUNT([item_num])) over(partition by [user_id]) AS total_amount
FROM Mytable
GROUP BY user_id, operation
)
SELECT
[user_id],
ROUND(ISNULL([purchase], 0) / total_amount, 2) AS purchase,
ROUND(ISNULL([sale], 0) / total_amount, 2) AS sale,
ROUND(ISNULL([conversion], 0) / total_amount, 2) AS conversion
FROM result
PIVOT
(
MAX(amount)
FOR operation IN ([purchase], [sale], [conversion])
) x
ORDER BY user_id
This code will work for you. You will need to use a CTE with the columns and a sum() over() calculating the total sum per user_id.
With that information, all you need to do is pivot the result and give the formatting desired. If you need the division and not just showing what its dividing, remove the formating and concatenation.
WITH Sum_Over AS
(
select user_id,operation, amount,sum(amount) over(partition by user_id) AS Total_Sum
from #test
)
SELECT user_id
,CAST(ISNULL([purchase],0) AS VARCHAR(5))+'/'+CAST(Total_Sum AS VARCHAR(5)) AS [purchase]
,CAST(ISNULL([sale],0) AS VARCHAR(5))+'/'+CAST(Total_Sum AS VARCHAR(5)) AS [sale]
,CAST(ISNULL([conversion],0) AS VARCHAR(5))+'/'+CAST(Total_Sum AS VARCHAR(5)) AS [conversion]
FROM Sum_Over
PIVOT (
max(amount)
FOR operation IN ([purchase],[sale],[conversion])
)x
ORDER BY user_id
The answer from Jader is cleaner. This one uses Group By:
With result As
(
SELECT
user_id,
Sum(amount) as tot,
Case When operation = 'purchase' Then
convert(nvarchar(5),sum(amount)) + '/' + convert(nVarChar(50),(Select sum(amount) From MyTable t Where t.user_id = x.user_id))
End As [purchase],
Case When operation = 'sale' Then
convert(nvarchar(5),sum(amount)) + '/' + convert(nVarChar(50),(Select sum(amount) From MyTable t Where t.user_id = x.user_id))
End As [sale],
Case When operation = 'conversion' Then
convert(nvarchar(5),sum(amount)) + '/' + convert(nVarChar(50),(Select sum(amount) From MyTable t Where t.user_id = x.user_id))
End As [conversion]
FROM MyTable x
GROUP BY user_id, operation
)
Select user_id,
isnull(Max(purchase),'0/' + convert(nVarChar(50),sum(tot))) As purchase,
isnull(Max(sale),'0/' + convert(nVarChar(50),sum(tot))) As sale,
isnull(Max(conversion),'0/' + convert(nVarChar(50),sum(tot))) As conversion
From result
Group By user_id
Related
Is it possible to use the DATEADD function but exclude dates from a table?
We already have a table with all dates we need to exclude. Basically, I need to add number of days to a date but exclude dates within a table.
Example: Add 5 days to 01/08/2021. Dates 03/08/2021 and 04/08/2021 exist in the exclusion table. So, resultant date should be: 08/08/2021.
Thank you
A bit of a "wonky" solution, but it works. Firstly we use a tally to create a Calendar table of dates, that exclude your dates in the table, then we get the nth row, where n is the number of days to add:
DECLARE #DaysToAdd int = 5,
#StartDate date = '20210801';
WITH N AS(
SELECT N
FROM (VALUES(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL))N(N)),
Tally AS(
SELECT 0 AS I
UNION ALL
SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS I
FROM N N1, N N2, N N3), --Up to 1,000
Calendar AS(
SELECT DATEADD(DAY,T.I, #StartDate) AS D,
ROW_NUMBER() OVER (ORDER BY T.I) AS I
FROM Tally T
WHERE NOT EXISTS (SELECT 1
FROM dbo.DatesTable DT
WHERE DT.YourDate = DATEADD(DAY,T.I, #StartDate)))
SELECT D
FROM Calendar
WHERE I = #DaysToAdd+1;
A best solution is probably a calendar table.
But if you're willing to traverse through every date, then a recursive CTE can work. It would require tracking the total iterations and another column to substract if any traversed date was in the table. The exit condition uses the total difference.
An example dataset would be:
CREATE TABLE mytable(mydate date); INSERT INTO mytable VALUES ('20210803'), ('20210804');
And an example function run in it's own batch:
ALTER FUNCTION dbo.fn_getDays (#mydate date, #daysadd int)
RETURNS date
AS
BEGIN
DECLARE #newdate date;
WITH CTE(num, diff, mydate) AS (
SELECT 0 AS [num]
,0 AS [diff]
,DATEADD(DAY, 0, #mydate) [mydate]
UNION ALL
SELECT num + 1 AS [num]
,CTE.diff +
CASE WHEN DATEADD(DAY, num+1, #mydate) IN (SELECT mydate FROM mytable)
THEN 0 ELSE 1 END
AS [diff]
,DATEADD(DAY, num+1, #mydate) [mydate]
FROM CTE
WHERE (CTE.diff +
CASE WHEN DATEADD(DAY, num+1, #mydate) IN (SELECT mydate FROM mytable)
THEN 0 ELSE 1 END) <= #daysadd
)
SELECT #newdate = (SELECT MAX(mydate) AS [mydate] FROM CTE);
RETURN #newdate;
END
Running the function:
SELECT dbo.fn_getDays('20210801', 5)
Produces output, which is the MAX(mydate) from the function:
----------
2021-08-08
For reference the MAX(mydate) is taken from this dataset:
n diff mydate
----------- ----------- ----------
0 0 2021-08-01
1 1 2021-08-02
2 1 2021-08-03
3 1 2021-08-04
4 2 2021-08-05
5 3 2021-08-06
6 4 2021-08-07
7 5 2021-08-08
You can use the IN clause.
To perform the test, I used a W3Schools Test DB
SELECT DATE_ADD(BirthDate, INTERVAL 10 DAY) FROM Employees WHERE FirstName NOT IN (Select FirstName FROM Employees WHERE FirstName LIKE 'N%')
This query shows all the birth dates + 10 days except for the only employee with name starting with N (Nancy)
I'm trying to sum totals together that goes beyond a basic "group by" or "case" statement.
Here's an example datasets:
Amt Cust_id Ranking PlanType
10 1 1 Term
6 1 2 Variable
8 1 3 Variable
7 1 4 Variable
12 1 5 Term
6 1 6 Variable
10 1 7 Variable
The objective is to return the max sum where the plan type is 'Variable' and
the Ranking numbers are adjacent to each other.
So the answer to the example would be the sum of rows 2-4 which returns 21.
The answer is not the sum of all variable plan types, because row 5 is a 'Term' which breaks it apart.
So I'd like to end with a dataset like below to handle multiple groups of customers:
Amt Cust_ID
21 1
30 2
45 3
Here's where I'm stuck which returns wrong answer:
Create Table #tb (Amt INT, Cust_id TINYINT, Ranking INT, PlanType
VARCHAR(10))
INSERT INTO #tb
VALUES (10,1,1,'Term'),
(6,1,2,'Variable'),
(8,1,3,'Variable'),
(7,1,4,'Variable'),
(12,1,5,'Term'),
(6,1,6,'Variable'),
(10,1,7,'Variable'),
(10,2,1,'Term'),
(6,2,2,'Variable'),
(7,2,4,'Variable'),
(12,2,5,'Term'),
(6,2,6,'Variable'),
(50,2,7,'Variable')
select
( SELECT SUM(Amt) FROM #tb as t2
WHERE t2.Cust_ID=t1.Cust_ID AND t2.Ranking<=t1.Ranking AND
t2.PlanType='Variable') RollingAmt
,Cust_ID, Ranking, Amt, PlanType
from #tb as t1
order by Cust_ID, Ranking
The query runs a rolling sum ordered by "Ranking" where PlanType = 'Variable'. Unfortunately it runs a rolling sum of all "Variable"'s together. I need it to not do that.
If it runs into a PlanType "Term" it needs to start over its sum within each group.
In order to do this you need to use a gaps-and-islands technique to generate a "group id" based on consecutive runs of the same PlanType, then you can sum and sort based on that new group id.
Try this:
DECLARE #data TABLE (Amt INT, Cust_id TINYINT, Ranking INT, PlanType VARCHAR(10))
INSERT INTO #data
VALUES (10,1,1,'Term'),
(6,1,2,'Variable'),
(8,1,3,'Variable'),
(7,1,4,'Variable'),
(12,1,5,'Term'),
(6,1,6,'Variable'),
(10,1,7,'Variable'),
(10,2,1,'Term'),
(6,2,2,'Variable'),
(7,2,4,'Variable'),
(12,2,5,'Term'),
(6,2,6,'Variable'),
(50,2,7,'Variable')
;WITH X AS
(
SELECT *,
ROW_NUMBER() OVER(PARTITION BY Cust_id,PlanType ORDER BY Ranking)
- ROW_NUMBER() OVER(PARTITION BY Cust_id ORDER BY Ranking) groupID /* Assign a groupID to consecutive runs of PlanTypes by Cust_id */
FROM #data
), Y AS
(
SELECT *, SUM(Amt) OVER(PARTITION BY Cust_id,groupID) AS AmtSum /* Sum Amt by Cust/groupID */
FROM X
WHERE PlanType='Variable'
), Z AS
(
SELECT *, ROW_NUMBER() OVER(PARTITION BY Cust_id ORDER BY AmtSum DESC) AS RN /* Assign a row number (1) to highest AmtSum by Cust */
FROM Y
)
SELECT AmtSum, Cust_id
FROM Z
WHERE RN=1 /* Only select RN=1 to get highest value by cust_id/groupId */
If you are curious about how this all works, you can comment the last SELECT and do SELECT * FROM X then SELECT * FROM Y etc, to see what each step does along the way; but only one SELECT can follow the entire CTE structure.
Based on the following example : (it is a "QueryLog" table, this table store interactions between a user and two different products N and R):
Id Date UserID Product
--------------------------------------------------
0 2013-06-09 14:50:24.000 100 N
1 2013-06-09 15:27:23.000 100 N
2 2013-06-09 15:29:23.000 100 N
3 2013-06-17 15:31:23.000 100 N
4 2013-06-17 15:32:23.000 100 N
5 2014-05-19 15:30:23.000 250 N
6 2014-07-19 15:27:23.000 250 N
7 2014-07-19 15:27:23.000 333 R
8 2014-08-19 15:27:23.000 333 R
Expected results :
Count
-----
1
(Only UserID 250 is inside my criteria)
If one user interacts 10 times with the product in only one month, he's not in my criteria.
To resume, I am looking for :
The Number of distinct users that had interactions with product N on at least more than one month (what ever the number of interactions this user may have had during a single month)
This is the code I've tried:
select distinct v.UserID, v.mois , v.annee
from
(select c.UserID , c. mois, c.annee, COUNT(c.UserID) as frequence
from
(
SELECT
datepart(month,[DATE]) as mois,
datepart(YEAR,[DATE]) as annee ,
Username,
UserID,
Product
FROM QueryLog
where Product = 'N'
) c
group by c.UserID, c.annee, c.mois
) v
group by v.UserID, v.mois, v.annee
try this:
DECLARE #YourTable table (Id int, [Date] datetime, UserID int, Product char(1))
INSERT INTO #YourTable VALUES (0,'2013-06-09 14:50:24',100 ,'N')
,(1,'2013-06-09 15:27:23',100 ,'N')
,(2,'2013-06-09 15:29:23',100 ,'N')
,(3,'2013-06-17 15:31:23',100 ,'N')
,(4,'2013-06-17 15:32:23',100 ,'N')
,(5,'2014-05-19 15:30:23',250 ,'N')
,(6,'2014-07-19 15:27:23',250 ,'N')
,(7,'2014-07-19 15:27:23',333 ,'R')
,(8,'2014-08-19 15:27:23',333 ,'R')
;WITH MultiMonthUsers AS
(
select
UserID
FROM (select
UserID
FROM #YourTable
WHERE product='N'
GROUP BY UserID, YEAR([Date]),MONTH([Date])
)dt2
GROUP BY UserID
HAVING COUNT(*)>1
)
SELECT COUNT(*) FROM MultiMonthUsers
Depending on number of rows and indexes, this will run slow. Using YEAR([Date]),MONTH([Date]) will prevent any index usage.
I think this will do it, but I need a better dataset to test with:
SELECT COUNT(*)
FROM (
--roll all month/user records into single row
SELECT UserID, datediff(month 0, [date]) As MonthGroup
FROM QueryLog
WHERE Product='N'
GROUP BY datediff(month 0, [date]), UserId
) t
-- look for users with multiple rows
GROUP BY UserID
HAVING COUNT(UserID) > 1
Seems like there should be a way to roll this up further, to avoid the need for the nested select.
I'm new to T-SQL and need help converting an excel report to a run on SQL. I have a SQL table that records all the daily inventory transactions (in/out) from each stockroom. I need to create a report that list the current inventory levels for each product in each location and the qty in each place as follows. In other words, the current inventory levels of each place.
I also need help on how to insert the Preferred Out Report (below) into SQL Server as a view so I can run this each month over and over again.
Thanks in Advance!
Inventory Log table:
PubID QTY LocationID Transaction
1 10 1 Add
1 20 2 Add
1 30 3 Add
1 5 1 Sold
1 10 2 Sold
1 5 3 Sold
2 10 1 Add
2 10 2 Add
2 5 2 Sold
2 8 2 Sold
1 20 1 Add
1 20 2 Add
2 2 2 Sold
Preferred Output Table:
PubID Local_1 Local_2 Local_3 Total
1 25 30 25 80
2 5 0 0 5
Total 30 30 25 85
I see a lot of close examples here but most just add the value while I need to subtract the Sold inventory from the Added stock to get my totals in each column.
The row totals and column totals on the right and bottom are pluses but not needed if it's easier without.
THANKS!
If this was about aggregation without pivoting, you could use a CASE expression, like this:
SELECT
...
Local_1 = SUM(CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END),
...
FROM ...
GROUP BY ...
However, in the PIVOT clause, the argument of the aggregate function must be just a column reference, not an expression. You can work around that by transforming the original dataset so that QTY is either positive or negative, depending on Transaction:
SELECT
PubID,
QTY = CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END,
LocationID
FROM dbo.InventoryLog
The above query will give you a result set like this:
PubID QTY LocationID
----- --- ----------
1 10 1
1 20 2
1 30 3
1 -5 1
1 -10 2
1 -5 3
2 10 1
2 10 2
2 -5 2
2 -8 2
1 20 1
1 20 2
2 -2 2
which is now easy to pivot:
WITH prepared AS (
SELECT
PubID,
QTY = CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END,
LocationID
FROM dbo.InventoryLog
)
SELECT
PubID,
Local_1 = [1],
Local_2 = [2],
Local_3 = [3]
FROM prepared
PIVOT
(
SUM(QTY)
FOR LocationID IN ([1], [2], [3])
) AS p
;
Note that you could actually prepare the names Local_1, Local_2, Local_3 beforehand and avoid renaming them in the main SELECT. Assuming they are formed by appending the LocationID value to the string Local_, here's an example of what I mean:
WITH prepared AS (
SELECT
PubID,
QTY = CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END,
Name = 'Local_' + CAST(LocationID AS varchar(10))
FROM dbo.InventoryLog
)
SELECT
PubID,
Local_1,
Local_2,
Local_3
FROM prepared
PIVOT
(
SUM(QTY)
FOR Name IN (Local_1, Local_2, Local_3)
) AS p
;
You will see, however, that in this solution renaming will be needed at some point anyway, so I'll use the previous version in my further explanation.
Now, adding the totals to the pivot results as in your desired output may seem a little tricky. Obviously, the column could be calculated simply as the sum of all the Local_* columns, which might actually not be too bad with a small number of locations:
WITH prepared AS (
SELECT
PubID,
QTY = CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END,
LocationID
FROM dbo.InventoryLog
)
SELECT
PubID,
Local_1 = [1],
Local_2 = [2],
Local_3 = [3]
Total = COALESCE([1], 0)
+ COALESCE([2], 0)
+ COALESCE([3], 0)
FROM prepared
PIVOT
(
SUM(QTY)
FOR LocationID IN ([1], [2], [3])
) AS p
;
(COALESCE is needed because some results may be NULL.)
But there's an alternative to that, where you don't have to list all the locations explicitly one extra time. You could return the totals per PubID alongside the details in the prepared dataset using SUM() OVER (...), like this:
WITH prepared AS (
SELECT
PubID,
QTY = CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END,
LocationID,
Total = SUM(CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END)
OVER (PARTITION BY PubID)
FROM dbo.InventoryLog
)
…
or like this, if you wish to avoid repetition of the CASE expression:
WITH prepared AS (
SELECT
t.PubID,
QTY = x.AdjustedQTY,
t.LocationID,
Total = SUM(x.AdjustedQTY) OVER (PARTITION BY t.PubID)
FROM dbo.InventoryLog AS t
CROSS APPLY (
SELECT CASE t.[Transaction] WHEN 'Add' THEN t.QTY ELSE -t.QTY END
) AS x (AdjustedQTY)
)
…
Then you would just include the Total column into the main SELECT clause along with the pivoted results and PubID:
…
SELECT
PubID,
Local_1,
Local_2,
Local_3,
Total
FROM prepared
PIVOT
(
SUM(QTY)
FOR LocationID IN ([1], [2], [3])
) AS p
;
That would be the total column for you. As for the row, it is actually easy to add it when you are acquainted with the ROLLUP() grouping function:
…
SELECT
PubID,
Local_1 = SUM([1]),
Local_2 = SUM([2]),
Local_3 = SUM([3]),
Total = SUM(Total)
FROM prepared
PIVOT
(
SUM(QTY)
FOR LocationID IN ([1], [2], [3])
) AS p
GROUP BY ROLLUP(PubID)
;
The total row will have NULL in the PubID column, so you'll again need COALESCE to put the word Total instead (only if you want to return it in SQL; alternatively you could substitute it in the calling application):
…
PubID = COALESCE(CAST(PubID AS varchar(10)), 'Total'),
…
And that would be all. To sum it up, here is a complete query:
WITH prepared AS (
SELECT
PubID,
QTY = x.AdjustedQTY,
t.LocationID,
Total = SUM(x.AdjustedQTY) OVER (PARTITION BY t.PubID)
FROM dbo.InventoryLog AS t
CROSS APPLY (
SELECT CASE t.[Transaction] WHEN 'Add' THEN t.QTY ELSE -t.QTY END
) AS x (AdjustedQTY)
)
SELECT
PubID = COALESCE(CAST(PubID AS varchar(10)), 'Total'),
Local_1 = SUM([1]),
Local_2 = SUM([2]),
Local_3 = SUM([3]),
Total = SUM(Total)
FROM prepared
PIVOT
(
SUM(QTY)
FOR LocationID IN ([1], [2], [3])
) AS p
GROUP BY ROLLUP(PubID)
;
As a final touch to it, you may want to apply COALESCE to the SUMs as well, to avoid returning NULLs in your data (if that is necessary).
The query below does what you need. I might have had one extra group by that could be combined into 1 but you get the idea.
DECLARE #InventoryLog TABLE
(
PubId INT,
Qty INT,
LocationId INT,
[Transaction] Varchar(4)
)
DECLARE #LocationTable TABLE
(
Id INT,
Name VarChar(10)
)
INSERT INTO #LocationTable
VALUES
(1, 'LOC_1'),
(2, 'LOC_2'),
(3, 'LOC_3')
INSERT INTO #InventoryLog
VALUES
(1 , 10, 1 , 'Add'),
(1 , 20, 2 , 'Add'),
(1 , 30, 3 , 'Add'),
(1 , 5 , 1 , 'Sold'),
(1 , 10, 2 , 'Sold'),
(1 , 5 , 3 , 'Sold'),
(2 , 10, 1 , 'Add'),
(2 , 10, 2 , 'Add'),
(2 , 5 , 2 , 'Sold'),
(2 , 8 , 2 , 'Sold'),
(1 , 20, 1 , 'Add'),
(1 , 20, 2 , 'Add'),
(2 , 2 , 2 , 'Sold')
SELECT PubId,
lT.Name LocationName,
CASE
WHEN [Transaction] ='Add' Then Qty
WHEN [Transaction] ='Sold' Then -Qty
END as Quantity
INTO #TempInventoryTable
FROM #InventoryLog iL
INNER JOIN #LocationTable lT on iL.LocationId = lT.Id
SELECT * INTO #AlmostThere
FROM
(
SELECT PubId,
ISNULL(LOC_1,0) LOC_1,
ISNULL(LOC_2,0) LOC_2,
ISNULL(LOC_3,0) LOC_3,
SUM(ISNULL(LOC_1,0) + ISNULL(LOC_2,0) + ISNULL(LOC_3,0)) AS TOTAL
FROM #TempInventoryTable s
PIVOT
(
SUM(Quantity)
FOR LocationName in (LOC_1,LOC_2,LOC_3)
) as b
GROUP BY PubId, LOC_1, LOC_2, LOC_3
) b
SELECT CAST(PubId as VARCHAR(10))PubId,
LOC_1,
LOC_2,
LOC_3,
TOTAL
FROM #AlmostThere
UNION
SELECT ISNULL(CAST(PubId AS VARCHAR(10)),'TOTAL') PubId,
[LOC_1]= SUM(LOC_1),
[LOC_2]= SUM(LOC_2),
[LOC_3]= SUM(LOC_3),
[TOTAL]= SUM(TOTAL)
FROM #AlmostThere
GROUP BY ROLLUP(PubId)
DROP TABLE #TempInventoryTable
DROP TABLE #AlmostThere
PubId LOC_1 LOC_2 LOC_3 TOTAL
1 25 30 25 80
2 10 -5 0 5
TOTAL 35 25 25 85
Sql Fiddle
Here is another approach: aggregate the data before pivoting, then pivot the aggregated results.
Compared to my other suggestion, this method is much simpler syntactically, which may also make it easier to understand and maintain.
All the aggregation is done with the help of the CUBE() grouping function. The basic query would be this:
SELECT
PubID,
LocationID,
QTY = SUM(CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END)
FROM dbo.InventoryLog
GROUP BY CUBE(PubID, LocationID)
You can see the same CASE expression as in my other answer, only this time it can be directly used as the argument of SUM.
Using aggregation by CUBE gives us not only the totals by (PubID, LocationID), but also by PubID and LocationID separately, as well as the grand total. This is the result of the query for the example in your question:
PubID LocationID QTY
----- ---------- ---
1 1 35
2 1 10
NULL 1 45
1 2 50
2 2 25
NULL 2 75
1 3 35
NULL 3 35
NULL NULL 155
1 NULL 120
2 NULL 35
Rows with NULLs in LocationID are row totals in the final result set, and those with NULLs in PubID are column totals. The row with NULLs in both columns is the grand total.
Before we can proceed with the pivoting, we need to prepare column names for the pivoted results. If the names are supposed to be derived from the values of LocationID, the following declaration will replace LocationID in the original query's SELECT clause:
Location = COALESCE('Local_' + CAST(LocationID AS varchar(10)), 'Total')
We can also substitute 'Total' for the NULLs in PubID at this same stage, so this will replace PubID in the SELECT clause:
PubID = COALESCE(CAST(PubID AS varchar(10)), 'Total')
Now the results will look like this:
PubID LocationID QTY
----- ---------- ---
1 Local_1 35
2 Local_1 10
Total Local_1 45
1 Local_2 50
2 Local_2 25
Total Local_2 75
1 Local_3 35
Total Local_3 35
Total Total 155
1 Total 120
2 Total 35
and at this point everything is ready to apply PIVOT. This query transforms the above result set according to the desired format:
WITH aggregated AS (
SELECT
PubID = COALESCE(CAST(PubID AS varchar(10)), 'Total'),
Location = COALESCE('Local_' + CAST(LocationID AS varchar(10)), 'Total'),
QTY = SUM(CASE [Transaction] WHEN 'Add' THEN QTY ELSE -QTY END)
FROM dbo.InventoryLog
GROUP BY CUBE(PubID, LocationID)
)
SELECT
PubID,
Local_1,
Local_2,
Local_3,
Total
FROM aggregated
PIVOT (
MAX(QTY)
FOR Location IN (Local_1, Local_2, Local_3, Total)
) AS p
;
This query will return NULLs for missing combinations of (PubID, LocationID). If you want to return 0 instead, apply COALESCE to the result of SUM in the definition of aggregated.
There's one table named StudentScore which has fields of: Score, CourseID, StudentID and Semester. The later three ones are the primary keys.
I want to write a stored procedure to get the average score of each student. But the rule is quite complex and I don't know how to express it in one query. Nested query should be avoided if is possible.
Here is the rule:
If one student take a course for more than once, only the last score should be calculated.
For example, there're following data:
StudentID | CourseID | Semester | Score
1 1 1 80
1 2 1 40
1 3 1 60
1 2 2 50
1 3 2 20
2 1 1 90
The stored procedure should return:
StudentID | AvgScore
1 50 // which is avg(80, 50, 20)
2 90
Please suggest stored procedure as efficient as possible. Thanks!
;WITH x AS
(
SELECT StudentID, Score, rn = ROW_NUMBER() OVER
(PARTITION BY StudentID, CourseID
ORDER BY Semester DESC)
FROM dbo.StudentScore
)
SELECT StudentID, AvgScore = AVG(Score)
FROM x
WHERE rn = 1
GROUP BY StudentID;
If you want something rounded to certain decimal places, maybe:
;WITH x AS
(
SELECT StudentID, Score = 1.0*Score, rn = ROW_NUMBER() OVER
(PARTITION BY StudentID, CourseID
ORDER BY Semester DESC)
FROM dbo.StudentScore
)
SELECT StudentID, AvgScore = CONVERT(DECIMAL(10,2), AVG(Score))
FROM x
WHERE rn = 1
GROUP BY StudentID;