使用索引连接临时表

Question

我刚刚开始了解 INDEX，我听说它可以加快结果，但我的测试却产生了相反的效果。

关于数据的几点：

我的公司使用 SQL 服务器，但我对除此之外的了解不多
我只是一名员工，没有任何管理员权限，甚至只能查看某些文件夹
#TABLE1 包含超过 23,000 行并在 1 秒内运行
#TABLE2 包含超过 310 万行，运行时间约为 1.5 分钟
使用连接大约需要 1.75 到 2.5 分钟
我尝试使用 INDEX 需要 2.5 到 3 或更多
之后我会加入更多的表格，但这 2 个基本上是其他一切的基础

我在下面尝试的查询花费的时间比我执行普通 JOIN 时要长

IF OBJECT_ID('tempdb..#TABLE1') IS NOT NULL DROP TABLE #TABLE1;
IF OBJECT_ID('tempdb..#TABLE2') IS NOT NULL DROP TABLE #TABLE2;

SELECT
cast(T1.[ID] as varchar(20)) as 'ID',
cast(T1.[Division] as int) as 'Division',
cast(T1.[Category] as int) as 'Category',
cast(T1.[Platform] as int) as 'Platform',
cast(T1.[Condition] as tinyint) as 'Condition',
cast(T1.[First Received] as date) as 'First Received',
cast(T1.[Last Received] as date) as 'Last Received'

INTO #TABLE1

FROM
CompanyTable as T1

WHERE
T1.[Name] = 'Canada'
AND T1.[Division] = '100';

CREATE NONCLUSTERED INDEX IX_TABLE1 ON #TABLE1([ID], [Division], [Category], [Platform]);

SELECT DISTINCT
SE.[Date] as 'Date',
SE.[ID] as 'ID',
SE.[Division] as 'Division',
SE.[Category] as 'Category',
SE.[Platform] as 'Platform',
sum(SE.[Units]) as 'Units',
sum(SE.[Sales]) as 'Sales',
sum(SE.[Retail]) as 'Retail',
sum(SE.[Cost]) as 'Cost'

INTO #TABLE2

FROM 
(SELECT
    cast(S1.[Date] as date) as 'Date',
    cast(S1.[ID] as varchar(20)) as 'ID',
    cast(S1.[Division] as int) as 'Division',
    cast(S1.[Category] as int) as 'Category',
    cast(S1.[Platform] as int) as 'Platform',
    cast(sum(S1.[Quantity]) * -1 as decimal(38,20)) as 'Units',
    cast(sum(S1.[Net Amount]) * -1 as decimal(38,20)) as 'Sales',
    cast(sum(S1.[Cost Amount]) * -1 as decimal(38,20)) as 'Cost',
    cast(sum(S1.[Price]) as decimal(38,20)) as 'Retail'

    FROM
    SalesTable1 as S1

    WHERE
    S1.[Division] = '100'
    
    GROUP BY
    S1.[ID], S1.[Date], S1.[Division], S1.[Category], S1.[Platform]
    
    UNION ALL
    
    SELECT
    cast(S2.[Date] as date) as 'Date',
    cast(S2.[ID] as varchar(20)) as 'ID',
    cast(S2.[Division] as int) as 'Division',
    cast(S2.[Category] as int) as 'Category',
    cast(S2.[Platform] as int) as 'Platform',
    cast(sum(S2.[Quantity]) * -1 as decimal(38,20)) as 'Units',
    cast(sum(S2.[Net Amount]) * -1 as decimal(38,20)) as 'Sales',
    cast(sum(S2.[Cost Amount]) * -1 as decimal(38,20)) as 'Cost',
    cast(sum(S2.[Price]) as decimal(38,20)) as 'Retail'
    
    FROM
    SalesTable2 as S2
    
    WHERE
    S2.[Division] = '100'
    
    GROUP BY
    S2.[ID], S2.[Date], S2.[Division], S2.[Category], S2.[Platform]
) as T2

GROUP BY
T2.[ID], T2.[Date], T2.[Division], T2.[Category], SE.[Platform]

CREATE NONCLUSTERED INDEX IX_TABLE2 ON #TABLE2([ID], [Division], [Category], [Platform]);

SELECT *
FROM #TABLE1 as T1
JOIN #TABLE2 as T2 ON T1.[ID] = T2.[ID] AND T1.[Division] = T2.[Division] AND T1.[Category] = T2.[Category] AND T1.[Platform] = T2.[Platform]

DROP INDEX IX_TABLE1 ON #TABLE1;
DROP INDEX IX_TABLE2 ON #TABLE2;

我是不是做错了什么导致速度变慢？

Answer 1

如下所示在#table1 和#table2 上创建 4 个不同的索引，运行您的查询。

CREATE NONCLUSTERED INDEX IX_TABLE1_id ON #TABLE1([ID]);
CREATE NONCLUSTERED INDEX IX_TABLE1_Div ON #TABLE1([Division]);
CREATE NONCLUSTERED INDEX IX_TABLE1_Cat ON #TABLE1([ [Category]);
CREATE NONCLUSTERED INDEX IX_TABLE1_Plt ON #TABLE1([[Platform]);

CREATE NONCLUSTERED INDEX IX_TABLE1_id ON #TABLE2([ID]);
CREATE NONCLUSTERED INDEX IX_TABLE1_Div ON #TABLE2([Division]);
CREATE NONCLUSTERED INDEX IX_TABLE1_Cat ON #TABLE3[ [Category]);
CREATE NONCLUSTERED INDEX IX_TABLE1_Plt ON #TABLE4([[Platform]);

Answer 2

您的临时表需要一个具有唯一值的主键以用作 CLUSTERED INDEX。那么您只需要在 JOIN 列上添加一个 NONCLUSTERED INDEX。假设 #TABLE1 中的 ID 是唯一的，像这样创建索引：

ALTER TABLE #TABLE1 ADD CONSTRAINT PK_TABLE1 PRIMARY KEY CLUSTERED ([ID]);
CREATE NONCLUSTERED INDEX IX_TABLE1 ON #TABLE1([Division], [Category], [Platform]);

同上 #TABLE2，再次假设 ID id 唯一：

ALTER TABLE #TABLE2 ADD CONSTRAINT PK_TABLE2 PRIMARY KEY CLUSTERED ([ID]);
CREATE NONCLUSTERED INDEX IX_TABLE2 ON #TABLE2([Division], [Category], [Platform]);

但是，如果实际瓶颈是 non-temp 表，这可能无法解决您的性能问题。您应该运行脚本的 SELECT 部分分开。如果他们自己表现良好，请尝试这些指标。如果不是，那么您需要与您的 DBA 联系并找出 SELECT 运行ning 慢的原因。

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