基于今天,本周,本月,今年第四季度的最快销售总结方式？

Question

以下查询返回正确的结果,但如何更快地获得相同的结果？

目标是通过总结今天,本周,月和季度的销售情况来输出跟踪卖家进度的表格.

SellerID    Today                 ThisWeek              ThisMonth             ThisQuarter
----------- --------------------- --------------------- --------------------- ---------------------
1           400,00                700,00                900,00                900,00
2           950,00                1850,00               2650,00               2650,00

我的查询:

CREATE TABLE #sales(
    [Price] MONEY,
    [Date] DATE,
    [SellerID] INT
)

INSERT INTO #sales VALUES 
(100, '2012-01-01', 1),
(200, '2012-04-01',1),
(300, '2012-04-23',1),
(400, '2012-04-27',1),
(700, '2012-01-01', 2),
(700, '2012-01-02', 2),
(800, '2012-04-01',2),
(900, '2012-04-23',2),
(950, '2012-04-27',2)


SELECT 
SellerID AS SellerID,

SUM(CASE WHEN [Date] >= DATEADD(DAY, DATEDIFF(DAY, 0, GETDATE()),0) THEN [Price] END) AS Today,
SUM(CASE WHEN [Date] >= DATEADD(WEEK, DATEDIFF(WEEK, 0, GETDATE()), 0) THEN [Price] END) AS ThisWeek,
SUM(CASE WHEN [Date] >= DATEADD(MONTH, DATEDIFF(MONTH, 0, GETDATE()), 0) THEN [Price] END) AS ThisMonth,
SUM(CASE WHEN [Date] >= DATEADD(QUARTER, DATEDIFF(QUARTER, 0, GETDATE()), 0) THEN [Price] END) AS ThisQuarter

FROM #sales
WHERE DATEPART(YEAR, [Date]) = DATEPART(YEAR, GETDATE()) 
GROUP BY SellerID

在较大的表上执行相同的查询时,这会变得非常慢.只需删除CASE语句,可将执行时间缩短近50%.

如何以更快,更有效的方式实现相同的结果？

Answer 1

由于是星期五下午,我想我会扩展我对仓储的评论.即使您无法使用SSAS或任何其他OLAP完全探索多维数据集,您仍然可以执行自己的报表特定仓库.在你的情况下,我会建立一个新的数据库(我总是称我的DW,但世界是你的牡蛎),并创建2个模式Fact和Dim(代表事实和维度).在您的情况下,它需要2个表,但您可能需要为"SellerID"添加另一个维度,具体取决于是否需要进一步报告.

CREATE TABLE Dim.Date
(       DateKey     DATE NOT NULL,
        DayOfWeek   VARCHAR(20) NOT NULL,
        Day         TINYINT NOT NULL,
        Week        TINYINT NOT NULL,
        Quarter     TINYINT NOT NULL,
        Month       TINYINT NOT NULL,
        Year        SMALLINT NOT NULL
    CONSTRAINT PK_Dim_Date_DateKey PRIMARY KEY (DateKey)
)
CREATE TABLE Fact.Sales
(       DateKey     DATE NOT NULL,
        SellerID    INT NOT NULL,
        Sales       INT NOT NULL,
        Amount      MONEY NOT NULL,
    CONSTRAINT PK_Fact_Sales PRIMARY KEY (DateKey, SellerID),
    CONSTRAINT FK_Fact_Sales_DateKey FOREIGN KEY (DateKey) REFERENCES Dim.Date
)

假设数据不会过期,您可以使用这样的过程在预定作业中填充仓库:

DECLARE @MaxDate DATE
SELECT  @MaxDate = DATEADD(DAY, 1, MAX(DateKey))
FROM    Fact.Sales

INSERT INTO Dim.Date
SELECT  DATEADD(DAY, Increment, @MaxDate), 
        DATENAME(WEEKDAY, DATEADD(DAY, Increment, @MaxDate)), 
        DATEPART(DAY, DATEADD(DAY, Increment, @MaxDate)),
        DATEPART(WEEK, DATEADD(DAY, Increment, @MaxDate)),
        DATEPART(MONTH, DATEADD(DAY, Increment, @MaxDate)),
        DATEPART(QUARTER, DATEADD(DAY, Increment, @MaxDate)),
        DATEPART(YEAR, DATEADD(DAY, Increment, @MaxDate))
FROM    (   SELECT  ROW_NUMBER() OVER(ORDER BY Object_ID) - 1 [Increment]
            FROM    Sys.Objects
        ) obj
WHERE   NOT EXISTS
        (   SELECT  1
            FROM    Dim.Date
            WHERE   Date.DateKey = DATEADD(DAY, Increment, @MaxDate)
        )


INSERT INTO Fact.Sales
SELECT  [Date], SellerID, COUNT(*), SUM(Price)
FROM    LiveDatabase..Sales
WHERE   [Date] >= @MaxDate
GROUP BY [Date], SellerID

这将为您提供以下查询以生成您的报告

SELECT  SellerID,
        SUM(CASE WHEN Today.DateKey = Date.DateKey THEN Amount ELSE O END) [Today],
        SUM(CASE WHEN Today.Week = Date.Week THEN Amount ELSE O END) [ThisWeek],
        SUM(CASE WHEN Today.Month = Date.Month THEN Amount ELSE O END) [ThisMonth],
        SUM(CASE WHEN Today.Quarter = Date.Quarter THEN Amount ELSE O END) [ThisQuarter],
        SUM(CASE WHEN Today.Year = Date.Year THEN Amount ELSE O END) [ThisYear]
FROM    Fact.Sales
        INNER JOIN Dim.Date
            ON Date.DateKey = Sales.DateKey
        INNER JOIN Dim.Date Today
            ON Today.DateKey = CAST(GETDATE() AS DATE)
            AND Today.Year = Date.Year
GROUP BY SellerID

它看起来(如果有的话)比原始查询更复杂,但是在线数据库越多,你就会看到越多的好处.我已经做了一个SQL小提琴来演示它的优点,它用10000个随机销售记录填充实时数据,然后创建一个仓库(可能需要几秒钟来构建模式).您应该注意到仓库上查询的执行时间明显更快(c.20x).它在第一次运行时可能不会快20倍,但是一旦为两个查询缓存了查询计划,仓库查询的速度就会快20倍(无论如何都是为了我).