通过过滤查看一个特定列的数据到几列答案

【问题标题】：view one particular column data in to several columns by filtering通过过滤查看一个特定列的数据到几列
【发布时间】：2014-03-07 11:34:49
【问题描述】：

我有一个表格，其中有一列包含Leave 类型（Annual、Casual、Medical 等）。

现在我需要根据休假类型Annual Leave、Casual Leave、Medical Leave 等将其拆分为多个列。

表LeaveAccount

LeaveAccountID, 
LeaveTypeID, 
EmployeeID, 
AccountingYearID, 
TotalLeaves, 
LeavesTaken

表LeaveType

LeaveTypeID,
LeaveTypeName

我的查询 [给出一个无限循环] 是：

[FullName, EmplyeeID, AnnualLeave, ShortLeave, Medical Leave]

SELECT
    e.FullName
  , e.EmployeeId
  , a.TotalLeaves as AnnualLeave
  , b.TotalLeaves as shortleave
  , c.TotalLeaves as MedicalLeave
FROM
    LeaveAccount a
  , Employee e
  , LeaveAccount b
  , LeaveAccount c
WHERE
      (a.EmployeeId = b.EmployeeId) 
  and (
            (a.LeaveTypeId = 0) 
        and (b.LeaveTypeId = 20)
        and (c.LeaveTypeId = 1)
      )

我需要使用动态 SQL 吗？我怎么可以这样分裂？

【问题讨论】：

标签： sql sql-server ssis group-by

【解决方案1】：

为什么需要拆分表？

当您可以创建表的视图时，每个视图将包含一列：

CREATE VIEW 
   Annual_Leave
AS 
SELECT 
   Annual
FROM 
   Leave types;

您对其余列执行相同操作。

【讨论】：

【解决方案2】：

尝试使用子选择：

SELECT
    e.FullName
  , e.EmployeeId
  , (SELECT SUM(a.TotalLeaves) FROM LeaveAccount a WHERE a.EmployeeId = e.EmployeeId AND a.LeaveTypeId = 0) AS "AnnualLeave"
  , (SELECT SUM(b.TotalLeaves) FROM LeaveAccount b WHERE b.EmployeeId = e.EmployeeId AND b.LeaveTypeId = 20) AS "ShortLeave"
  , (SELECT SUM(c.TotalLeaves) FROM LeaveAccount c WHERE c.EmployeeId = e.EmployeeId AND c.LeaveTypeId = 1) AS "MedicalLeave"
FROM
  Employee e

另一种解决方案是分组：

SELECT
    e.FullName
  , e.EmployeeId
  , SUM(a.TotalLeaves) AS "AnnualLeave"
  , SUM(b.TotalLeaves) AS "ShortLeave"
  , SUM(c.TotalLeaves) AS "MedicalLeave"
FROM
  Employee e
INNER JOIN
  LeaveAccount a
ON
      a.EmployeeId  = e.EmployeeId
  AND a.LeaveTypeId = 0
INNER JOIN
  LeaveAccount b
ON
      b.EmployeeId  = e.EmployeeId
  AND b.LeaveTypeId = 20
INNER JOIN
  LeaveAccount c
ON
      c.EmployeeId  = e.EmployeeId
  AND c.LeaveTypeId = 1
GROUP BY
    e.FullName
  , e.EmployeeId

编辑：您可能必须在此处使用LEFT OUTER JOIN 而不是INNER JOIN，具体取决于您的数据。

【讨论】：