按日期透视预订状态

Question

一个包裹可以在 2 个日期之间预订，预订状态由 2 个用户更新（0 为未确认，1 为待确认，2 为已确认）。 我正在尝试显示某个包在一段时间内的状态。

我们有下表：

CREATE TABLE [dbo].[Packages](
    [ID] [int] IDENTITY(1,1) NOT NULL,
    [Name] [varchar](50) NULL,
 CONSTRAINT [PK_Packages] 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].[Users](
    [ID] [int] IDENTITY(1,1) NOT NULL,
    [name] [varchar](50) NULL
) ON [PRIMARY]
GO

CREATE TABLE [dbo].[Bookings](
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [PackageID] [int] NULL,
    [fromDate] [datetime] NULL,
    [toDate] [datetime] NULL,
    [status] [int] NULL,
    [user1] [int] NULL,
    [user2] [int] NULL,
 CONSTRAINT [PK_Bookings] 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

一些测试数据：

insert into Packages(Name) values ('pack1')
insert into Packages(Name) values ('pack2')
insert into Packages(Name) values ('pack3')
insert into Packages(Name) values ('pack4')
insert into Packages(Name) values ('pack5')

insert into users(name) values('operator1')
insert into users(name) values('operator2')
insert into users(name) values('admin1')
insert into users(name) values('admin2')

insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (1,'7/1/2020','7/11/2020',0,1,null)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (1,'7/15/2000','7/18/2020',1,2,3)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (2,'7/6/2020','7/10/2020',1,1,4)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (2,'7/20/2000','7/25/2020',0,2,null)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (3,'7/13/2020','7/13/2020',2,1,3)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (3,'7/24/2020','7/30/2020',2,2,3)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (4,'7/5/2020','7/16/2020',2,1,4)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (5,'7/2/2020','7/8/2020',1,1,3)
insert into bookings(PackageID, fromDate, toDate, status, user1, user2) values (5,'7/22/2020','7/30/2020',1,2,4)

我正在尝试实现这样的目标：显示 2020 年 7 月的预订状态

Packages - 7/1/2020 - 7/2/2020 - 7/3/2020 - 7/4/2020 - 7/5/2020 - 7/6/2020 - 7/7/2020 - 7/8/2020 ... 
1        - 0        - 0        - 0        - 0        - 0        - 0        - 0        - 0        ... 
2        -          -          -          -          -          - 1        - 1        - 1        ... 
3        -          -          -          -          -          -          -          -          ... 
4        -          -          -          -          - 2        - 2        - 2        - 2        ... 
5        -          - 1        - 1        - 1        - 1        - 1        - 1        - 1        ... 

Answer 1

我可能会更简单地将日期放在行中而不是列中。如果这对您来说是一个可接受的解决方案，这是一种使用递归查询生成日期然后连接的方法。这假设给定包裹没有重叠预订：

with dates as (
    select '20207101' dt
    union all
    select dateadd(day, 1, dt) from dates where dateadd(day, 1, dt) < '20200801'
)
select p.id, d.dt, b.status
from dates d
cross join packages p 
left join bookings b 
    on  b.packageID = p.id 
    and b.fromDate >= d.dt
    and b.toDate   <  d.dt

您可能希望根据 fromDate 和 toDate 的确切含义调整日期的不等式（我假设一个半开区间）。

如果您确实想要一个透视结果集，那么动态 SQL 之外的一种方法是在每个月的每一天使用条件聚合，如下所示：

with dates as (
    select '20207101' dt
    union all
    select dateadd(day, 1, dt) from dates where dateadd(day, 1, dt) < '20200801'
)
select 
    p.id, 
    max(case when day(d.dt) =  1 then b.status end) [2020701],
    max(case when day(d.dt) =  2 then b.status end) [2020702],
    max(case when day(d.dt) =  3 then b.status end) [2020703],
    ...
    max(case when day(d.dt) = 31 then b.status end) [2020731]
from dates d
cross join packages p 
left join bookings b 
    on  b.packageID = p.id 
    and b.fromDate >= d.dt
    and b.toDate   <  d.dt
group by p.id