SQL Query for generating matrix like output querying related table in SQL Server

Question

I have three tables:
Product

ProductID   ProductName  
1           Cycle  
2           Scooter  
3           Car  

<

Answer 1

You can use SQL Server's PIVOT operator

SELECT  *
FROM    (
          SELECT  P.ProductName
                  , C.CustName
                  , T.Amount
          FROM    Transactions AS T  
                  INNER JOIN Product AS P ON  T.ProductID = P.ProductID  
                  INNER JOIN Customer AS C ON  T.CustomerID = C.CustomerID  
          WHERE   T.TranDate BETWEEN '2011-01-01' AND '2011-03-31'   
        ) s
PIVOT   (SUM(Amount) FOR ProductName IN ([Car], [Cycle], [Scooter])) pvt

Test data

;WITH q AS (
  SELECT  [Product] = 'Car', [Customer] = 'Armstrong', [Amount] = 80115.50
  UNION ALL SELECT 'Car', 'Michelle', 36571.85  
  UNION ALL SELECT 'Car', 'Schmidt', 45000.65  
  UNION ALL SELECT 'Cycle', 'Michelle', 15000.00  
  UNION ALL SELECT 'Cycle', 'Ronald', 25000.00  
  UNION ALL SELECT 'Scooter', 'Peterson', 82658.23  
  UNION ALL SELECT 'Scooter', 'Ronald', 98547.52  
  UNION ALL SELECT 'Scooter', 'Schmidt', 54000.25  
)
SELECT  Customer
        , Car = ISNULL(Car, 0)
        , Cycle = ISNULL(Cycle, 0)
        , Scooter = ISNULL(Scooter, 0)
        , Total = ISNULL(Car, 0) + ISNULL(Cycle, 0) + ISNULL(Scooter, 0)
FROM    (
          SELECT  *
          FROM    q
        ) s
PIVOT   (SUM(Amount) FOR Product IN ([Car], [Cycle], [Scooter])) pvt

Output

Customer   Car       Cycle     Scooter   Total
Armstrong  80115.50  0.00      0.00      80115.50
Michelle   36571.85  15000.00  0.00      51571.85
Peterson   0.00      0.00      82658.23  82658.23
Ronald     0.00      25000.00  98547.52  123547.52
Schmidt    45000.65  0.00      54000.25  99000.90

Answer 2

create table #Product (ProductID   int,ProductName  varchar(15))
insert into #Product values (1,'Cycle')
insert into #Product values (2,'Scooter')
insert into #Product values (3,'Car')

create table #Customer (CustomerID   int, CustomerName  varchar(30))
insert into #Customer values (101,'Ronald')
insert into #Customer values (102,'Michelle')
insert into #Customer values (103,'Armstrong')
insert into #Customer values (104,'Schmidt')
insert into #Customer values (105,'Peterson')

create table #Transactions (TID int,ProductID int,CustomerID int, TranDate smalldatetime,Amount decimal(18,2))
insert into #Transactions values (10001,1,101,'01-Jan-11',25000.00)
insert into #Transactions values (10002,2,101,'02-Jan-11',98547.52)
insert into #Transactions values (10003,1,102,'03-Feb-11',15000.00)
insert into #Transactions values (10004,3,102,'07-Jan-11',36571.85)
insert into #Transactions values (10005,2,105,'09-Feb-11',82658.23)
insert into #Transactions values (10006,2,104,'10-Feb-11',54000.25)
insert into #Transactions values (10007,3,103,'20-Feb-11',80115.50)
insert into #Transactions values (10008,3,104,'22-Feb-11',45000.65)

with temp as 
(
select cus.CustomerName,pro.ProductName, sum(trans.Amount) as Amount from #Transactions as trans
inner join #Customer as cus on trans.CustomerID = cus.CustomerID
inner join #Product as pro on trans.ProductID = pro.ProductID
group by cus.CustomerName,pro.ProductName
)

select CustomerName,isnull([Car],0)Car, isnull([Cycle],0)Cycle,isnull([Scooter],0) as Scooter, isnull([Car],0)+isnull([Cycle],0)+isnull([Scooter],0)as Total  from temp
pivot (
sum(Amount) for ProductName in ([Cycle],[Scooter],[Car])
)pot*

Answer 3

We can create matrix using pivot, this can easily done with data frames

product|Key|Value
A      |P  |10|
A      |Q  |40|
B      |R  |50|
B      |S  |50|

val newdf=df.groupBy("product").pivot("key").sum("value")

|product|P   |Q   |R   |S   |
|B      |null|null|  50|  50|
|A      |  10|  40|null|null|

We can replace null and we can do calculations as well