2014年12月18日更新

随着对主要问题“否”的压倒性答复，更有趣的答复集中在第2部分，即如何使用显式ORDER BY解决性能难题。尽管我已经标记了答案，但是如果有一个性能更好的解决方案，我也不会感到惊讶。

原始

出现此问题是因为唯一快速的解决方案我可以发现只有在没有ORDER BY子句的情况下，特定问题才有效。以下是产生此问题所需的完整T-SQL，以及我提出的解决方案（如果有问题，我正在使用SQL Server 2008 R2。）

--Create Orders table
IF OBJECT_ID('tempdb..#Orders') IS NOT NULL DROP TABLE #Orders
CREATE TABLE #Orders
(  
       OrderID    INT NOT NULL IDENTITY(1,1)
     , CustID     INT NOT NULL
     , StoreID    INT NOT NULL       
     , Amount     FLOAT NOT NULL
)
CREATE CLUSTERED INDEX IX ON #Orders (StoreID, Amount DESC, CustID)

--Add 1 million rows w/ 100K Customers each of whom had 10 orders
;WITH  
    Cte0 AS (SELECT 1 AS C UNION ALL SELECT 1), --2 rows  
    Cte1 AS (SELECT 1 AS C FROM Cte0 AS A, Cte0 AS B),--4 rows  
    Cte2 AS (SELECT 1 AS C FROM Cte1 AS A ,Cte1 AS B),--16 rows 
    Cte3 AS (SELECT 1 AS C FROM Cte2 AS A ,Cte2 AS B),--256 rows 
    Cte4 AS (SELECT 1 AS C FROM Cte3 AS A ,Cte3 AS B),--65536 rows 
    Cte5 AS (SELECT 1 AS C FROM Cte4 AS A ,Cte2 AS B),--1048576 rows 
    FinalCte AS (SELECT  ROW_NUMBER() OVER (ORDER BY C) AS Number FROM   Cte5)
INSERT INTO #Orders (CustID, StoreID, Amount)
SELECT CustID = Number / 10
     , StoreID    = Number % 4
     , Amount     = 1000 * RAND(Number)
FROM  FinalCte
WHERE Number <= 1000000

SET STATISTICS IO ON
SET STATISTICS TIME ON

--For StoreID = 1, find the top 500 customers ordered by their most expensive purchase (Amount)

--Solution A: Without ORDER BY
DECLARE @Top INT = 500
SELECT DISTINCT TOP (@Top) CustID
FROM #Orders WITH(FORCESEEK)
WHERE StoreID = 1
OPTION(OPTIMIZE FOR (@Top = 1), FAST 1);
--9 logical reads, CPU Time = 0 ms, elapsed time = 1 ms
GO
--Solution B: With ORDER BY
DECLARE @Top INT = 500
SELECT TOP (@Top) CustID
FROM #Orders
WHERE StoreID = 1
GROUP BY CustID
ORDER BY MAX(Amount) DESC
OPTION(MAXDOP 1)
--745 logical reads, CPU Time = 141 ms, elapsed time = 145 ms
--Uses Sort operator

GO


这里解决方案A和B的执行计划分别是：





解决方案A提供了我所需的性能，但我做不到当添加任何种类的ORDER BY子句时（例如，请参阅解决方案B），请使其具有相同的性能。当然，解决方案A似乎必须按顺序传递其结果，因为1）表仅具有一个索引，2）强制执行查找，因此消除了使用基于IAM页的分配顺序扫描的可能性。

所以我的问题是：


我是正确的，它可以保证在这种情况下没有order by子句的顺序吗？
如果没有，是否有另一种方法可以强制执行与解决方案A一样快的计划，最好是避免排序的方法？请注意，这将必须解决完全相同的问题（对于StoreID = 1，请按购买价格最高的订单找到前500名客户）。它还必须仍然使用#Orders表，但是可以使用不同的索引方案。


评论

仅在使用ORDER BY的情况下才能保证订购。
“我是对的，在这种情况下，可以保证没有order by子句的情况下的顺序”-不，绝对不是。
这是一篇很好的文章，对此做了解释。 blogs.msdn.com/b/conor_cunningham_msft/archive/2008/08/27/…
@SeanLange：像您和其他人一样，出于同样的原因，我不愿意取消订单。但是，a）我找不到性能与使用ORDER BY的解决方案A相同的查询，并且b）我不知道有什么方法可以错误地对它们进行排序。你做？我并不是说没有办法，我只是不知道一种办法，而是希望有人能够阐明一种办法。甚至您引用的文章中的示例仅适用于扫描，而不适用于搜索。
更新：我更改了数量数据类型和计算方法，以避免重复太多。原则仍然适用。尽管在这个问题上，我并不关心出现平局时谁会赢，但是由于有如此多的平局使得查看数据时很难看到发生了什么。现在更加清楚的是，除了联系，解决方案A和B产生的结果相同。

#1 楼



我是对的，在这种情况下，它可以保证无顺序by子句的顺序吗？




否。如今，SQL Server尚未实现保留顺序的Flow Distinct（允许ORDER BY不进行排序）。原则上可以这样做，但是如果允许我们更改SQL Server源代码，那么可以做很多事情。如果可以为该开发工作提供一个很好的理由，则可以向Microsoft建议。



如果没有，是否有另一种方法可以强制执行如此快速的计划作为解决方案A，最好是避免排序的解决方案？




是的。 （仅在使用2014年之前的基数估计量时才需要表和查询提示）：

-- Additional index
CREATE UNIQUE NONCLUSTERED INDEX i 
ON #Orders (StoreID, CustID, Amount, OrderID);

-- Query
SELECT TOP (500) 
    O.CustID, 
    O.Amount
FROM #Orders AS O
    WITH (FORCESEEK(IX (StoreID)))
WHERE O.StoreID = 1
AND NOT EXISTS
(
    SELECT NULL
    FROM #Orders AS O2
        WITH (FORCESEEK(i (StoreID, CustID, Amount)))
    WHERE 
        O2.StoreID = O.StoreID
        AND O2.CustID = O.CustID
        AND O2.Amount >= O.Amount
        AND
        (
            O2.Amount > O.Amount
            OR
            (
                O2.Amount = O.Amount
                AND O2.OrderID > O.OrderID
            )
        )
)
ORDER BY
    O.Amount DESC
OPTION (MAXDOP 1);





 (500 row(s) affected)

 SQL Server Execution Times:
   CPU time = 0 ms,  elapsed time = 4 ms.


SQL CLR解决方案

以下脚本显示了如何使用SQL CLR表值函数满足规定的要求。我不是C＃专家，因此代码可能需要改进：

USE Sandpit;
GO
-- Ensure SQLCLR is enabled
EXECUTE sys.sp_configure
    @configname = 'clr enabled',
    @configvalue = 1;
RECONFIGURE;
GO
-- Lazy, but effective to allow EXTERNAL_ACCESS
ALTER DATABASE Sandpit
SET TRUSTWORTHY ON;
GO
-- The CLR assembly
CREATE ASSEMBLY FlowDistinctOrder
AUTHORIZATION dbo
FROM 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WITH PERMISSION_SET = EXTERNAL_ACCESS;
GO
-- The CLR TVF with order guarantee
CREATE FUNCTION dbo.FlowDistinctOrder 
(
    @ServerName nvarchar(128), 
    @DatabaseName nvarchar(128), 
    @MaxRows bigint
)
RETURNS TABLE 
(
    CustID integer NULL, 
    Amount float NULL
)
ORDER (Amount DESC)
AS EXTERNAL NAME FlowDistinctOrder.UserDefinedFunctions.FlowDistinctOrder;


问题的测试表和示例数据：

-- Test table
CREATE TABLE dbo.Orders
(  
    OrderID    integer  NOT NULL IDENTITY(1,1),
    CustID     integer  NOT NULL,
    StoreID    integer  NOT NULL,
    Amount     float    NOT NULL
);
GO
-- Sample data
WITH  
    Cte0 AS (SELECT 1 AS C UNION ALL SELECT 1), --2 rows  
    Cte1 AS (SELECT 1 AS C FROM Cte0 AS A, Cte0 AS B),--4 rows  
    Cte2 AS (SELECT 1 AS C FROM Cte1 AS A ,Cte1 AS B),--16 rows 
    Cte3 AS (SELECT 1 AS C FROM Cte2 AS A ,Cte2 AS B),--256 rows 
    Cte4 AS (SELECT 1 AS C FROM Cte3 AS A ,Cte3 AS B),--65536 rows 
    Cte5 AS (SELECT 1 AS C FROM Cte4 AS A ,Cte2 AS B),--1048576 rows 
    FinalCte AS (SELECT  ROW_NUMBER() OVER (ORDER BY C) AS Number FROM   Cte5)
INSERT dbo.Orders 
    (CustID, StoreID, Amount)
SELECT 
    CustID  = Number / 10,
    StoreID = Number % 4,
    Amount  = 1000 * RAND(Number)
FROM FinalCte
WHERE 
    Number <= 1000000;
GO
-- Index
CREATE CLUSTERED INDEX IX 
ON dbo.Orders 
    (StoreID ASC, Amount DESC, CustID ASC);


功能测试：

-- Test the function
-- Run several times to ensure connection is cached
-- and CLR code fully compiled
DECLARE @Start datetime2 = SYSUTCDATETIME();

SELECT TOP (500) 
    FDO.CustID
FROM dbo.FlowDistinctOrder
(
    @@SERVERNAME,   -- For external connection
    DB_NAME(),      -- For external connection
    500             -- Number of rows to return
) AS FDO 
ORDER BY 
    FDO.Amount DESC;

SELECT DATEDIFF(MILLISECOND, @Start, SYSUTCDATETIME());


执行计划（请注意对ORDER保证书的确认）：



在我的笔记本电脑上，通常执行时间为80-100ms。这远没有上面的T-SQL重写快，但是面对不同的数据分布，它应该表现出良好的性能稳定性。

源代码：

 using Microsoft.SqlServer.Server;
using System.Collections;
using System.Collections.Generic;
using System.Data.SqlClient;

public partial class UserDefinedFunctions
{
    private sealed class ReverseComparer<T> : IComparer<T>
    {
        private readonly IComparer<T> original;

        public ReverseComparer(IComparer<T> original)
        {
            this.original = original;
        }

        public int Compare(T left, T right)
        {
            return original.Compare(right, left);
        }
    }

    [SqlFunction
        (
        DataAccess = DataAccessKind.Read,
        SystemDataAccess = SystemDataAccessKind.None,
        FillRowMethodName = "FillRow",
        TableDefinition = "CustID integer NULL, Amount float NULL"
        )
    ]
    public static IEnumerable FlowDistinctOrder
        (
        [SqlFacet (MaxSize=128)]string ServerName, 
        [SqlFacet (MaxSize=128)]string DatabaseName,
        long MaxRows
        )
    {
        var list = new SortedDictionary<double, int>
            (new ReverseComparer<double>(Comparer<double>.Default));

        var csb = new SqlConnectionStringBuilder();
        csb.ConnectTimeout = 10;
        csb.DataSource = ServerName;
        csb.Enlist = false;
        csb.InitialCatalog = DatabaseName;
        csb.IntegratedSecurity = true;

        using (var conn = new SqlConnection(csb.ConnectionString))
        {
            conn.Open();
            using (var cmd = conn.CreateCommand())
            {
                cmd.CommandText =
                    @"
                    SELECT
                        O.CustID, 
                        O.Amount
                    FROM dbo.Orders AS O
                    WHERE 
                        O.StoreID = 1 
                    ORDER BY 
                        O.Amount DESC";

                int custid;
                double amount;

                using (var rdr = cmd.ExecuteReader())
                {
                    while (rdr.Read())
                    {
                        custid = rdr.GetInt32(0);
                        amount = rdr.GetDouble(1);

                        if (!list.ContainsKey(amount))
                        {
                            list.Add(amount, custid);
                            if (list.Count == MaxRows)
                            {
                                break;
                            }
                        }
                    }
                }
            }
        }
        return list;
    }

    public static void FillRow(object obj, out int CustID, out double Amount)
    {
        var v = (KeyValuePair<double, int>)obj;
        CustID = v.Value;
        Amount = v.Key;
    }
}


#2 楼

如果没有ORDER BY，很多事情都会出错。您已经排除了我能想到的所有可能的问题，但这并不意味着没有问题，以后的版本中也不会存在。

这应该起作用：

以循环方式从表中拉出500行的批次，并在有500个不同的客户ID时停止。提取查询如下所示：

select TOP (500) Amount, CustID
into #fetchedOrders
from Orders
where StoreID = 1234 and Amount <= @lastAmountFetched
order by Amount DESC


这将对索引执行有序范围扫描。 Amount <= @lastAmountFetched谓词在那里可以逐步提取更多记录。每个查询只会实际触及500条记录。这意味着它是O（1）。进入索引越远，它的成本就越高。

必须维护变量@lastAmountFetched才能减小到该语句中获取的最小值。

这样，您将以有序方式逐步扫描索引。您最多可以读取（500-1）行，而不是最佳数量。

这将比为特定商店累计100000个左右的订单要快得多。大概只需要每次500行的几次迭代。

本质上，这是一个手动编码的流不同运算符。

或者，使用游标来获取尽可能少的迭代行。这会慢很多，因为执行500个单行查询通常比执行500个行要慢。

或者，只需按顺序查询所有没有DISTINCT的行，并创建客户端应用程序一旦返回了足够的行（使用SqlCommand.Cancel），终止查询。

评论

这缺少关键的细节-您将如何确保#fetchedOrders不包含我们已经见过的客户？大概这涉及到临时表上的索引查找，这与“流分离”并不完全相同，而且我们看到的行越多，它的代价就越高（尽管在最坏的情况下，它在所有情况下仍将胜过解决方案B）必须扫描所有行，因为只有一个客户，A和B的表现相同）。

– Jeroen Mostert
2014年12月17日23:08
@JeroenMostert-IGNORE_DUP_KEY可以做到这一点。

–马丁·史密斯
2014年12月17日23:15
@usr：谢谢你。我使用IGNORE_DUP_KEY对其进行了编码，并运行了数字，得出CPU时间= 31ms，经过时间= 27ms。尽管比解决方案B快得多，但它离解决方案A并不遥远（cpu = 0，ms = 1），就我的目的而言，这是必须的。当您说“您排除了我能想到的所有可能的问题”时，我想知道我是否排除了任何人都能想到的所有问题。令人沮丧的是，我可以想象要获得A的性能需要执行什么SQL，我只是不知道如何使用ORDER BY来告诉它。

–JohnnyM
2014-12-17 23:55