返回带有枢轴数据的多列

Question

I've a requirement where I've to show total sales of a product month-wise and did it perfectly with pivot as follows:

SELECT *
FROM (SELECT m.ProductId [Product],  
       DATENAME(MONTH, m.OrderDate) [Month], 
       SUM(ISNULL(M.Quantity, 0)) [Sales]
      FROM SampleOrders m
      GROUP BY m.ProductId, 
      DATENAME(MONTH, m.OrderDate)) AS MontlySalesData
PIVOT( SUM([Sales])   
    FOR Month IN ([January],[February],[March],[April],[May],
    [June],[July],[August],[September],[October],[November],
    [December])) AS PivotData

Output :

Product January February    March   April   May June    July    August  September   October November    December
1001    NULL    NULL    NULL    NULL    6   30  NULL    NULL    NULL    NULL    NULL    NULL
1002    NULL    NULL    NULL    NULL    14  6   NULL    NULL    NULL    NULL    NULL    NULL

So in May and June, the data are shown as expected using the OrderDate column. But I've another requirement where I've to show the month-wise stock as well with the pivot data from another table. To make it simple, I require something as below output:

Product May May-Stock June June-Stock
1001    6   10        30   20
1002    14   6         6   10

I am not sure how I can achieve this and bit confused if I can use two pivots at a time to get the result. Any ideas would be highly appreciated.

NB : Below are the tables schemas with sample data

CREATE TABLE [dbo].[SampleOrders](
    [Id] [int] IDENTITY(1,1) NOT NULL,
    [ProductId] [int] NULL,
    [OrderDate] [datetime] NULL,
    [CustomerId] [int] NULL,
    [Quantity] [float] NULL,
 CONSTRAINT [PK_SampleOrders] PRIMARY KEY CLUSTERED 
(
    [Id] ASC
)WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
) ON [PRIMARY]

Id  ProductId   OrderDate   CustomerId  Quantity
1   1001    2019-06-10 00:00:00.000 1   10
2   1001    2019-06-01 00:00:00.000 1   20
3   1002    2019-06-02 00:00:00.000 2   2
4   1002    2019-06-20 00:00:00.000 2   4
5   1001    2019-05-20 00:00:00.000 1   6
6   1002    2019-05-22 00:00:00.000 1   14

CREATE TABLE [dbo].[SampleStock](
    [Id] [int] IDENTITY(1,1) NOT NULL,
    [ProductId] [int] NULL,
    [Quantity] [float] NULL,
    [Status] [int] NULL,
    [StockDate] [datetime] NULL,
 CONSTRAINT [PK_SampleStock] PRIMARY KEY CLUSTERED 
(
    [Id] ASC
)WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
) ON [PRIMARY]

Id  ProductId   Quantity    Status  StockDate
1   1001    20  1   2019-06-10 00:00:00.000
2   1002    10  1   2019-06-12 00:00:00.000
3   1001    10  1   2019-05-02 00:00:00.000
4   1002    4   2   2019-05-20 00:00:00.000

Answer 1

This may help

CREATE TABLE [dbo].[SampleOrders](
    [Id] [int] IDENTITY(1,1) NOT NULL,
    [ProductId] [int] NULL,
    [OrderDate] [datetime] NULL,
    [CustomerId] [int] NULL,
    [Quantity] [float] NULL,
 CONSTRAINT [PK_SampleOrders] PRIMARY KEY CLUSTERED 
(
    [Id] ASC
)WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
) ON [PRIMARY]
GO
CREATE TABLE [dbo].[SampleStock](
    [Id] [int] IDENTITY(1,1) NOT NULL,
    [ProductId] [int] NULL,
    [Quantity] [float] NULL,
    [Status] [int] NULL,
    [StockDate] [datetime] NULL,
 CONSTRAINT [PK_SampleStock] PRIMARY KEY CLUSTERED 
(
    [Id] ASC
)WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
) ON [PRIMARY]
GO

INSERT INTO SampleOrders(ProductId,OrderDate,CustomerId,Quantity) VALUES(1001,'2019-06-10 00:00:00.000', 1,   10)
INSERT INTO SampleOrders(ProductId,OrderDate,CustomerId,Quantity) VALUES(1001,'2019-06-01 00:00:00.000', 1,   20)
INSERT INTO SampleOrders(ProductId,OrderDate,CustomerId,Quantity) VALUES(1002,'2019-06-02 00:00:00.000', 2,   2 )
INSERT INTO SampleOrders(ProductId,OrderDate,CustomerId,Quantity) VALUES(1002,'2019-06-20 00:00:00.000', 2,   4 )
INSERT INTO SampleOrders(ProductId,OrderDate,CustomerId,Quantity) VALUES(1001,'2019-05-20 00:00:00.000', 1,   6 )
INSERT INTO SampleOrders(ProductId,OrderDate,CustomerId,Quantity) VALUES(1002,'2019-05-22 00:00:00.000', 1,   14)
GO
INSERT INTO SampleStock(ProductId,Quantity,Status,StockDate) VALUES (1001,20,1,'2019-06-10 00:00:00.000')
INSERT INTO SampleStock(ProductId,Quantity,Status,StockDate) VALUES (1002,10,1,'2019-06-12 00:00:00.000')
INSERT INTO SampleStock(ProductId,Quantity,Status,StockDate) VALUES (1001,10,1,'2019-05-02 00:00:00.000')
INSERT INTO SampleStock(ProductId,Quantity,Status,StockDate) VALUES (1002,6 ,2,'2019-05-20 00:00:00.000')
INSERT INTO SampleStock(ProductId,Quantity,Status,StockDate) VALUES (1003,4 ,2,'2019-05-20 00:00:00.000')
GO
SELECT * FROM SampleOrders
SELECT * FROM SampleStock
GO
-- DROP TABLE #MonthlySales
SELECT Product
      ,January as JanuarySales
      ,February as FebruarySales
      ,March as MarchSales
      ,April as AprilSales
      ,May as MaySales
      ,June as JuneSales
      ,July as JulySales
      ,August as AugustSales
      ,September as SeptemberSales
      ,October as OctoberSales
      ,November as NovemberSales
      ,December as DecemberSales
INTO #MonthlySales
FROM (SELECT m.ProductId [Product],  
       DATENAME(MONTH, m.OrderDate) [Month], 
       SUM(ISNULL(M.Quantity, 0)) [Sales]
      FROM SampleOrders m
      GROUP BY m.ProductId, 
      DATENAME(MONTH, m.OrderDate)) AS MontlySalesData
PIVOT( SUM([Sales])   
    FOR Month IN ([January],[February],[March],[April],[May],
    [June],[July],[August],[September],[October],[November],
    [December])) AS PivotData

GO
-- DROP TABLE #MonthlyStock
SELECT Product
      ,January as JanuaryStock 
      ,February as FebruaryStock
      ,March as MarchStock
      ,April as AprilStock
      ,May as MayStock
      ,June as JuneStock
      ,July as JulyStock
      ,August as AugustStock
      ,September as SeptemberStock
      ,October as OctoberStock
      ,November as NovemberStock
      ,December as DecemberStock
INTO #MonthlyStock
FROM (SELECT m.ProductId [Product],  
       DATENAME(MONTH, m.StockDate) [Month], 
       SUM(ISNULL(M.Quantity, 0)) [Stock] 
      FROM SampleStock m
      GROUP BY m.ProductId, 
      DATENAME(MONTH, m.StockDate)) AS MontlyStock
PIVOT( SUM([Stock])   
    FOR Month IN ([January],[February],[March],[April],[May],
    [June],[July],[August],[September],[October],[November],
    [December])) AS PivotData

GO
SELECT ISNULL(sl.Product,st.Product) as Product
      ,JanuarySales,JanuaryStock
      ,FebruarySales,FebruaryStock
      ,MarchSales,MarchStock
      ,AprilSales,AprilStock
      ,MaySales,MayStock
      ,JuneSales,JuneStock
      ,JulySales,JulyStock
      ,AugustSales,AugustStock
      ,SeptemberSales,SeptemberStock
      ,OctoberSales,OctoberStock
      ,NovemberSales,NovemberStock
      ,DecemberSales,DecemberStock
FROM #MonthlySales sl
FULL JOIN #MonthlyStock st ON sl.Product = st.Product