我有2张桌子 以下是我需要遵循以获得所需输出的步骤。我可以跟进第3步。请帮助我，因为它有点复杂，我无法理解如何继续前进。
表1
Site Code FailFlag Comments ModifiedDate ModifiedBy
ABT A01 F Dfasdf 10/11/2011 Anna
ABT A01 F dsfsdf 15/12/2012 Mand
ABT A01 Rds 30/03/2011 Tim
ABT A01 GHDs 02/12/2012 Andy
ABT A02 F dfd 09/05/2012 Anna
ABT A02 sdada 11/02/2013 Kathy
ABT A02 Dfg 15/05/2011 Rob
AFL A02 F asda 13/02/2011 Dan
AFL A02 dsaa 24/12/2010 Ryan
TRG A01 sdasd 16/04/2010 Richard
TRG K05 jksdh 23/04/2012 Mark
KLD K05 F sd 18/05/2013 Jim
KLD K05 dsfsd 10/03/2012 James
KLD K05 sdsd 12/05/2011 Luther
KTY K05 F saq 09/09/2012 Ryan
KTY K05 asd 04/04/2010 Kathy
KMD C02 F nas 29/02/2012 Rob
KMD C02 asda 11/11/2011 Andy
表2：
Site Code Freq StartDate EndDate
ABT A01 43 01/01/2011 01/02/2012
ABT A02 254 01/01/2011 19/02/2011
ABT A02 109 20/02/2011 01/01/2012
ABT A02 12 02/01/2012 01/01/2013
AFL A02 13 01/01/2011 01/02/2012
TRG A01 122 01/01/2011 01/02/2012
TRG K05 61 01/01/2011 01/02/2012
KLD KO5 33 01/01/2011 15/05/2012
KLD K05 79 16/05/2012 01/01/2013
KTY K05 52 01/01/2011 01/02/2012
KMD C02 78 01/01/2011 01/02/2012
ZYT G01 11 01/01/2011 01/02/2012
PYN A01 15 01/01/2011 01/02/2012
DYN F08 122 01/01/2011 01/02/2012
步骤：
表1中两列“网站”和“代码”的组合将在Tabel2中查看“网站”和“代码”列的组合。
在“失败”列中过滤相同的内容并找出失败次数
以下是查询和输出：
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN F = 'F' THEN 1 ELSE 0 END) FROM Table1
GROUP BY Site,Det
Site Code Count FailFlagCount
ABT A01 4 2
ABT A02 3 1
AFL A02 2 1
TRG A01 1 0
TRG K05 1 0
KLD KO5 3 1
KTY K05 2 1
KMD C02 2 1
我们检查表2中的相同组合。即，步骤2输出的站点和代码在表2中查看以获得其频率
计算：
一个。 CC％= [1-（失败数/计数）] * 100 = [1-（2/4）] * 100
湾B.P.O％= [1-（FailCount / Freq）] * 100 = [1-（2/43）] * 100
c.Forecast％=
让我们假设当前月份是3月。
计算过去3年的失败次数并找出平均值，假设为“X”。
计算剩余月份的失败，'Y'=（X *剩余月数/ 12）
超过12个月的总失败=当前失败+ Y
因此预测％= [1-（超过12个月/频率的总故障）] * 100。
对于我们的例子，让我们假设X = 2的值 因此Y =（2 * 9/12）
预测％= [1-（1 + 1.5）] * 100
上述计算将针对网站和代码的所有可能组合进行。
Site Code CC B.P.O Forecast StartDate EndDate
ABT A01 01/01/2011 01/02/2012
ABT A02 01/01/2011 19/02/2011
ABT A02 20/02/2011 01/01/2012
ABT A02 02/01/2012 01/01/2013
AFL A02 01/01/2011 01/02/2012
TRG A01 01/01/2011 01/02/2012
TRG K05 01/01/2011 01/02/2012
KLD K05 01/01/2011 15/05/2012
KLD K05 16/05/2012 01/01/2013
KTY K05 01/01/2011 01/02/2012
KMD C02 01/01/2011 01/02/2012
上表的分组是在网站类型上完成的，即网站的首字母。
然后在分组后完成所有计算（cc，BPO，预测）的平均值
例如： - 'A'代表'ABT'，'T'代表'TRG'。
（我假设我们要么为多种类型创建多个表，然后进行联合以获得以下查询）
示例： -
Site Code CC B.P.O Forecast
A A01
A A02
[i.e.,Avg value of (ABT and A02)
and (AFL and A02)]
T A01
T K05 avg
[i.e., Avg value of (KLD and K05)
and (KTY and K05)]
K K05
K C02
这应该是我的最终输出。请帮助。
添加表格的脚本以便于提供帮助：
表1脚本：
CREATE TABLE Table1
(
ID INT IDENTITY(1,1) PRIMARY KEY CLUSTERED,
Site VARCHAR(5),
Code VARCHAR(5),
FailFlag CHAR(1),
Comments VARCHAR(100),
ModifiedDate DATETIME,
ModifiedBy VARCHAR(50)
);
INSERT INTO Table1
(Site, Code, FailFlag, Comments, ModifiedDate, ModifiedBy)
SELECT 'ABT', 'A01', 'F', 'Dfasdf', '10/11/2011', 'Anna' UNION ALL
SELECT 'ABT', 'A01', 'F', 'dsfsdf', '15/12/2012', 'Mand' UNION ALL
SELECT 'ABT', 'A01', NULL, 'Rds', '30/03/2011', 'Tim' UNION ALL
SELECT 'ABT', 'A01', NULL, 'GHDs', '02/12/2012', 'Andy' UNION ALL
SELECT 'ABT', 'A02', 'F', 'dfd', '09/05/2012', 'Anna' UNION ALL
SELECT 'ABT', 'A02', NULL, 'sdada', '11/02/2013', 'Kathy' UNION ALL
SELECT 'ABT', 'A02', NULL, 'Dfg', '15/05/2011', 'Rob' UNION ALL
SELECT 'AFL', 'A02', 'F', 'asda', '13/02/2011', 'Dan' UNION ALL
SELECT 'AFL', 'A02', NULL, 'dsaa', '24/12/2010', 'Ryan' UNION ALL
SELECT 'TRG', 'A01', NULL, 'sdasd', '16/04/2010', 'Richard' UNION ALL
SELECT 'TRG', 'K05', NULL, 'jksdh', '23/04/2012', 'Mark' UNION ALL
SELECT 'KLD', 'K05', 'F', 'sd', '18/05/2013', 'Jim' UNION ALL
SELECT 'KLD', 'K05', NULL, 'dsfsd', '10/03/2012', 'James' UNION ALL
SELECT 'KLD', 'K05', NULL, 'sdsd', '12/05/2011', 'Luther' UNION ALL
SELECT 'KTY', 'K05', 'F', 'saq', '09/09/2012', 'Ryan' UNION ALL
SELECT 'KTY', 'K05', NULL, 'asd', '04/04/2010', 'Kathy' UNION ALL
SELECT 'KMD', 'C02', 'F', 'nas', '29/02/2012', 'Rob' UNION ALL
SELECT 'KMD', 'C02', NULL, 'asda', '11/11/2011', 'Andy';
表2脚本：
CREATE TABLE Table2
(
ID INT IDENTITY(1,1) PRIMARY KEY CLUSTERED,
Site VARCHAR(5),
Code VARCHAR(5),
Freq int,
StartDate DATETIME,
EndDate DATETIME
);
INSERT INTO Table2 (Site, Code, Freq, StartDate, EndDate)
SELECT 'ABT', 'A01', 43, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'ABT', 'A02', 254, '01/01/2011', '19/02/2011' UNION ALL
SELECT 'ABT', 'A02', 109, '20/02/2011', '01/01/2012' UNION ALL
SELECT 'ABT', 'A02', 12, '02/01/2012', '01/01/2013' UNION ALL
SELECT 'AFL', 'A02', 13, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'TRG', 'A01', 122, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'TRG', 'K05', 61, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'KLD', 'KO5', 33, '01/01/2011', '15/05/2012' UNION ALL
SELECT 'KLD', 'K05', 79, '16/05/2012', '01/01/2013' UNION ALL
SELECT 'KTY', 'K05', 52, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'KMD', 'C02', 78, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'ZYT', 'G01', 11, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'PYN', 'A01', 15, '01/01/2011', '01/02/2012' UNION ALL
SELECT 'DYN', 'F08', 122, '01/01/2011', '01/02/2012';
答案 0 :(得分：1)
“有点复杂。”是。
从顶部开始，这是你的第2步。 这可能有一个关键的缺陷，因为它不会限制任何过去3年或过去12个月。从你的问题中不清楚这是意图，所以我们将使用它。
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site,Code;
需要将其与Table2连接以获取频率字段。我已经将它包装在子选择中并调用该子查询S2，因为它是第2步。
SELECT s2.Site, s2.Code,s2.[Count], S2.FailFlagCount, Table2.Freq
FROM
(
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site,Code
) S2
LEFT JOIN Table2 on S2.Site = table2.Site and S2.Code = table2.Code
;
然后计算CC和BPO相对容易。以上是一个名为S3的子查询。
请注意，我在这里阻止了零除错。
SELECT Site, Code, [Count], FailFlagCount, Freq,
CASE WHEN [Count]=0 THEN 0 ELSE ( 1-(FailFlagCount / [Count]))*100 END CC,
CASE WHEN Freq = 0 THEN 0 ELSE ( 1-(FailFlagCount / Freq))*100 END BPO
FROM
(
SELECT s2.Site, s2.Code,s2.[Count], S2.FailFlagCount, ISNULL(Table2.Freq, 1) AS Freq
FROM
(
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site,Code
) S2
LEFT JOIN Table2 on S2.Site = table2.Site and S2.Code = table2.Code
) s3
;
好的，这里有一些实验，围绕SQL月份函数，如何计算剩下几个月，以及今年1月。
select GETDATE(), month(GETDATE()), 12-MONTH(GETDATE()),
DATEADD(YEAR, -3, GETDATE()),
DATEFROMPARTS (YEAR(GETDATE()),1,1)
;
所以现在我们可以计算Y数 - 这是表1的整体，但过滤了过去36个月，然后计算月平均值。当你在月中运行时，隐含的错误可能会在这里蔓延 - 它不会在月份边界上破坏，它将在过去的3年内完成，而不是在本月之外的最后36个完成月份。
请注意，我必须将count（*）转换为浮点数，否则它是一个整数，在除法中将其舍入为0。
SELECT SITE, CODE, count(*) tot, cast(count(*) as float)/36 avg, (cast(count(*) as float)/36) * ((12-MONTH(GETDATE()))/12) Y
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEADD(YEAR, -3, GETDATE())
GROUP BY SITE, CODE;
我们今年以同样的方式计算失败。
SELECT SITE, CODE, COUNT(*) currFails
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEFROMPARTS (YEAR(GETDATE()),1,1)
GROUP BY SITE, CODE;
所以现在我们可以结合以上3个步骤来获得一个Y表，当前年份失败。注意那里的ISNULL有LEFT JOIN来补偿今年没有失败的网站。
SELECT s3.Site, s3.Code, [Count], FailFlagCount, Freq,
CASE WHEN [Count]=0 THEN 0 ELSE ( 1-(FailFlagCount / [Count]))*100 END CC,
CASE WHEN Freq = 0 THEN 0 ELSE ( 1-(FailFlagCount / Freq))*100 END BPO,
ISNULL(YBIt.Y, 0) Y,
isnull(currBit.currFails, 0) as currFails
FROM
(
SELECT s2.Site, s2.Code,s2.[Count], S2.FailFlagCount, ISNULL(Table2.Freq, 1) AS Freq
FROM
(
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site,Code
) S2
LEFT JOIN Table2 on S2.Site = table2.Site and S2.Code = table2.Code
) s3
LEFT JOIN
(
SELECT SITE, CODE, count(*) tot, cast(count(*) as float)/36 avg, (cast(count(*) as float)/36) * ((12-MONTH(GETDATE()))/12) Y
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEADD(YEAR, -3, GETDATE())
GROUP BY SITE, CODE
) YBit on S3.Site = Ybit.site AND S3.code = YBit.code
LEFT JOIN
(
SELECT SITE, CODE, COUNT(*) currFails
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEFROMPARTS (YEAR(GETDATE()),1,1)
GROUP BY SITE, CODE
) currBit ON s3.site = currBit.site and s3.code = currBit.code;
;
所以我们最终可以计算预测。
SELECT Site, code, [Count], FAilFlagCount, Freq,
CC, BPO, Y, currFails, Y+currFails totF12,
CASE WHEN Freq = 0 then 0 else (1-(( Y+currFails)/ Freq))*100 END Forecast
FROM
(
SELECT s3.Site, s3.Code, [Count], FailFlagCount, Freq,
CASE WHEN [Count]=0 THEN 0 ELSE ( 1-(FailFlagCount / [Count]))*100 END CC,
CASE WHEN Freq = 0 THEN 0 ELSE ( 1-(FailFlagCount / Freq))*100 END BPO,
ISNULL(YBIt.Y, 0) Y,
isnull(currBit.currFails, 0) as currFails
FROM
(
SELECT s2.Site, s2.Code,s2.[Count], S2.FailFlagCount, ISNULL(Table2.Freq, 1) AS Freq
FROM
(
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site, Code
) S2
LEFT JOIN Table2 on S2.Site = table2.Site and S2.Code = table2.Code
) s3
LEFT JOIN
(
SELECT SITE, CODE, count(*) tot, cast(count(*) as float)/36 avg, (cast(count(*) as float)/36) * ((12-MONTH(GETDATE()))/12) Y
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEADD(YEAR, -3, GETDATE())
GROUP BY SITE, CODE
) YBit on S3.Site = Ybit.site AND S3.code = YBit.code
LEFT JOIN
(
SELECT SITE, CODE, COUNT(*) currFails
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEFROMPARTS (YEAR(GETDATE()),1,1)
GROUP BY SITE, CODE
) currBit ON s3.site = currBit.site and s3.code = currBit.code
) S4A
;
好的，我们突然又需要开始日期和结束日期。它们位于表2中，它似乎也可能是Site + Code的主列表。因此，让我们使用左连接进行初始化并将计算加入到计算中。我们还将计算网站类型。
这是您对每个网站+代码的详细计算。
select left (t2.site, 1) siteType, t2.site, t2.code,
[Count], FAilFlagCount, s4.Freq,
CC, BPO, Forecast,
T2.StartDate, T2.EndDAte
FROM
Table2 T2
LEFT JOIN
(
SELECT Site, code, [Count], FAilFlagCount, Freq,
CC, BPO, Y, currFails, Y+currFails totF12,
CASE WHEN Freq = 0 then 0 else (1-(( Y+currFails)/ Freq))*100 END Forecast
FROM
(
SELECT s3.Site, s3.Code, [Count], FailFlagCount, Freq,
CASE WHEN [Count]=0 THEN 0 ELSE ( 1-(FailFlagCount / [Count]))*100 END CC,
CASE WHEN Freq = 0 THEN 0 ELSE ( 1-(FailFlagCount / Freq))*100 END BPO,
ISNULL(YBIt.Y, 0) Y,
isnull(currBit.currFails, 0) as currFails
FROM
(
SELECT s2.Site, s2.Code,s2.[Count], S2.FailFlagCount, ISNULL(Table2.Freq, 1) AS Freq
FROM
(
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site, Code
) S2
LEFT JOIN Table2 on S2.Site = table2.Site and S2.Code = table2.Code
) s3
LEFT JOIN
(
SELECT SITE, CODE, count(*) tot, cast(count(*) as float)/36 avg, (cast(count(*) as float)/36) * ((12-MONTH(GETDATE()))/12) Y
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEADD(YEAR, -3, GETDATE())
GROUP BY SITE, CODE
) YBit on S3.Site = Ybit.site AND S3.code = YBit.code
LEFT JOIN
(
SELECT SITE, CODE, COUNT(*) currFails
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEFROMPARTS (YEAR(GETDATE()),1,1)
GROUP BY SITE, CODE
) currBit ON s3.site = currBit.site and s3.code = currBit.code
) S4A
) S4
on t2.site = s4.site and t2.code = s4.code
;
从那里，我们可以轻松创建平均值。
SELECT siteType, '' as site, '' as code, avg([count]) [count], avg(FailFlagCount) FailFlagCount, avg(Freq) Freq,
avg (CC) CC, avg(BPO) BPO, avg(Forecast) Forecast, '' StartDAte, '' EndDate
FROM
(
select left (t2.site, 1) siteType, t2.site, t2.code,
[Count], FAilFlagCount, s4.Freq,
CC, BPO, Forecast,
T2.StartDate, T2.EndDAte
FROM
Table2 T2
LEFT JOIN
(
SELECT Site, code, [Count], FAilFlagCount, Freq,
CC, BPO, Y, currFails, Y+currFails totF12,
CASE WHEN Freq = 0 then 0 else (1-(( Y+currFails)/ Freq))*100 END Forecast
FROM
(
SELECT s3.Site, s3.Code, [Count], FailFlagCount, Freq,
CASE WHEN [Count]=0 THEN 0 ELSE ( 1-(FailFlagCount / [Count]))*100 END CC,
CASE WHEN Freq = 0 THEN 0 ELSE ( 1-(FailFlagCount / Freq))*100 END BPO,
ISNULL(YBIt.Y, 0) Y,
isnull(currBit.currFails, 0) as currFails
FROM
(
SELECT s2.Site, s2.Code,s2.[Count], S2.FailFlagCount, ISNULL(Table2.Freq, 1) AS Freq
FROM
(
SELECT Site,Code,COUNT(*) as [Count],
FailFlagCount= SUM(CASE WHEN FailFlag = 'F' THEN 1 ELSE 0 END)
FROM Table1
GROUP BY Site, Code
) S2
LEFT JOIN Table2 on S2.Site = table2.Site and S2.Code = table2.Code
) s3
LEFT JOIN
(
SELECT SITE, CODE, count(*) tot, cast(count(*) as float)/36 avg, (cast(count(*) as float)/36) * ((12-MONTH(GETDATE()))/12) Y
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEADD(YEAR, -3, GETDATE())
GROUP BY SITE, CODE
) YBit on S3.Site = Ybit.site AND S3.code = YBit.code
LEFT JOIN
(
SELECT SITE, CODE, COUNT(*) currFails
FROM Table1
WHERE FailFlag = 'F'
AND ModifiedDate >= DATEFROMPARTS (YEAR(GETDATE()),1,1)
GROUP BY SITE, CODE
) currBit ON s3.site = currBit.site and s3.code = currBit.code
) S4A
) S4
on t2.site = s4.site and t2.code = s4.code
) S5
GROUP BY siteType
;
或者您可以使用详细计算填充表格，然后计算平均值，而不是使用我的最终计算。
我会把最后的工会留给你。