具有独立 where 子句的多列 - SQL Pivot? [英] Mutiple columns with independent where clause - SQL Pivot?

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本文介绍了具有独立 where 子句的多列 - SQL Pivot?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

是否可以采用以下结构的表格:

Is it possible to take a table that is structured in the following fashion:

ID    Month     Info1 Info2
1      1          A     B
1      2          C     D
1      3          E     F
2      3          G     H
2      4          I     J

最终变成这样的表格:

ID    JanInfo1 JanInfo2 FebInfo1 FebInfo2 MarInfo1 MarInfo2 AprInfo1 AprInfo2
1        A        B        C        D        E        F        NULL    NULL
2       NULL      NULL    NULL     NULL      G        H         I       J

我研究过使用枢轴,但无法让它们工作.

I've looked into using pivots and couldn't get them to work.

我目前每个月都使用 CROSS APPLY 表值函数.

I currently use CROSS APPLY table valued functions for each each month.

有没有更好的方法来做到这一点?

Is there a better way to do this?

添加现有查询 - 尝试简化显示:

Added existing query - tried to simplify for display:

-- Get the unique IDs
DECLARE @PersonIds TABLE
(
    UploadID UNIQUEIDENTIFIER,
    PersonId VARCHAR(200),
    RecordYear INT
)
INSERT INTO @PersonIds
    SELECT DISTINCT UploadID, PersonId, RecordYear
    FROM [VERTICALTABLE] 
    WHERE UploadID = @PTPUploadID
            AND RecordYear = @RecordYear
        GROUP BY  UploadID, PersonId, RecordYear

-- Flatten via functions
INSERT INTO [FLATTABLE](PersonID, JanuaryCoverage, FebruaryCoverage, MarchCoverage, AprilCoverage, MayCoverage, JuneCoverage, 
        JulyCoverage, AugustCoverage, SeptemberCoverage, OctoberCoverage, NovemberCoverage, DecemberCoverage)

    SELECT PID.PersonID, M1.Covered, M2.Covered, M3.Covered, M4.Covered, M5.Covered, M6.Covered,
        M7.Covered, M8.Covered, M9.Covered, M10.Covered, M11.Covered, M12.Covered
    FROM @PersonIds AS PID
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 1, PID.PersonId) AS M1
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 2, PID.PersonId) AS M2
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 3, PID.PersonId) AS M3
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 4, PID.PersonId) AS M4
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 5, PID.PersonId) AS M5
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 6, PID.PersonId) AS M6
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 7, PID.PersonId) AS M7
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 8, PID.PersonId) AS M8
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 9, PID.PersonId) AS M9
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 10, PID.PersonId) AS M10
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 11, PID.PersonId) AS M11
    OUTER APPLY GetMonthInfpo(@PTPUploadID, @RecordYear, 12, PID.PersonId) AS M12
    WHERE UploadID = @PTPUploadID 
        AND RecordYear = @RecordYear

函数看起来像

ALTER FUNCTION GetMonthInfpo( 
(   
    @UploadID UNIQUEIDENTIFIER,
    @Year INT,
    @Month INT,
    @PersonID VARCHAR(200)
)
RETURNS TABLE 
AS
RETURN 
(
    SELECT COUNT(*) AS 'Covered'
    FROM [VERTICALTABLE] 
    WHERE UploadID = @UploadID
        AND RecordYear = @Year
        AND RecordMonth = @Month
        AND PersonId = @PersonID
)

推荐答案

你不需要多个 subqry.答案很简单——使用集合论.从你的第一个表 ID/Month/Info1/Info2 做 ID/Month + (1+2)/Info with easy union - 例如:

You don't need multiple subqry. Answer is very easy - use set theory. From your first table ID/Month/Info1/Info2 do ID/Month + (1+2) /Info with easy union - for example:

select ID, cast(Month as varchar(10)) + cast('_1' as varchar(10)) ComposedMonth, Info1 Info 
from tbl
union all
select ID, cast(Month as varchar(10)) + cast('_2' as varchar(10)), Info2 
from tbl

然后在这个数据集上使用(呈现为视图或临时表)pivot子句.

Then use on this dataset (presented as view or temp table) pivot clause.

select * 
from vw_tbl t
pivot (max(Info) for ComposedMonth in ([1_1], [1_2]...)) p
-- or if you will cast month to text
-- pivot (max(Info) for ComposedMonth in ([Jan_1], [Jan_2]...)) p

组合字符串是轻松旋转的关键.

Composing strings is the key for easy pivoting.

这篇关于具有独立 where 子句的多列 - SQL Pivot?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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