我有一个数据,数据如下:

我需要使用column id, region, company, dept, subdept and amountsepend更新Matching_id和Matching_Type。逻辑是这样的:
Sum AmountSepend by Region, Company, Dept and SubDept。如果sum为0,则Matching_Type为'Match‘,Matching_id为匹配记录的id的组合,否则为'Not Match’,Matching_id为id。**SUM表示无论AmountSepend为正还是负,相同条件下所有记录的总和。
另一个重要的标准是,如果交易是单记录,意味着按地区、公司、部门和SubDept分组的总计数为1,则匹配类型不匹配,Matching_UID为id,而不管AmountSepend为0或正/负值。示例id 8。
以下是输出:

这里是表和数据脚本
CREATE TABLE [dbo].[StackoverflowQuest](
[id] [int] NOT NULL,
[Region] [varchar](50) NULL,
[Company] [varchar](50) NULL,
[Dept] [varchar](50) NULL,
[SubDept] [varchar](50) NULL,
[AmountSepend] [float] NULL,
[Matching_id] [varchar](100) NULL,
[Matching_Type] [varchar](100) NULL
) ON [PRIMARY]我怎么能达到这样的效果呢?如有任何帮助/提示,我们将不胜感激
发布于 2016-12-02 19:03:08
CREATE TABLE #Table(Id INT,Region VARCHAR(100),Company INT,Dept INT,SubDept
INT,AmtSpend INT,MatchingId VARCHAR(100),MatchingType VARCHAR(100))
INSERT INTO #Table(Id ,Region ,Company , Dept ,SubDept ,AmtSpend )
SELECT 1,'NAM',12378,1,NULL,900 UNION ALL
SELECT 2,'NAM',12378,1,NULL,-900 UNION ALL
SELECT 3,'NAM',12370,1,23,1000 UNION ALL
SELECT 4,'ASA',1234,9,12,5000 UNION ALL
SELECT 5,'NAM',12370,1,23,-1000 UNION ALL
SELECT 6,'ASA',1234,9,12,800 UNION ALL
SELECT 7,'ASA',1234,9,12,-600 UNION ALL
SELECT 8,'ASA',12311,6,NULL,200
UPDATE #Table SET MatchingId = MatchIds,MatchingType = 'Match'
FROM
(
SELECT T2.Company,STUFF( ( SELECT ',' + CAST(T3.Id AS VARCHAR) FROM #Table
T3 WHERE T2.Company = T3.Company FOR XML PATH('')),1,1,'') MatchIds
FROM #Table T2
JOIN
(
SELECT T1.Company Company,SUM(T1.AmtSpend) Total
FROM #Table T1
GROUP BY T1.Company
HAVING SUM(T1.AmtSpend) = 0
)A ON A.Company = T2.Company
GROUP BY T2.Company
) A
WHERE A.Company = #Table.Company
UPDATE #Table SET MatchingId = CAST(Id AS VARCHAR),MatchingType = 'Not
Match' WHERE ISNULL(MatchingId,'') = ''
SELECT * FROM #Tablehttps://stackoverflow.com/questions/40929816
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