从上面验证克林特的正确答案:

下面两个查询之间的性能非常有趣。52%是最高的。48%是第二个。使用DISTINCT而不是ORDER BY提高了4%的性能。但是ORDER BY具有按多列排序的优势。

IF (OBJECT_ID('tempdb..#DocumentStatusLogs') IS NOT NULL) BEGIN DROP TABLE #DocumentStatusLogs END

CREATE TABLE #DocumentStatusLogs (
    [ID] int NOT NULL,
    [DocumentID] int NOT NULL,
    [Status] varchar(20),
    [DateCreated] datetime
)

INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (2, 1, 'S1', '7/29/2011 1:00:00')
INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (3, 1, 'S2', '7/30/2011 2:00:00')
INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (6, 1, 'S1', '8/02/2011 3:00:00')
INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (1, 2, 'S1', '7/28/2011 4:00:00')
INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (4, 2, 'S2', '7/30/2011 5:00:00')
INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (5, 2, 'S3', '8/01/2011 6:00:00')
INSERT INTO #DocumentStatusLogs([ID], [DocumentID], [Status], [DateCreated]) VALUES (6, 3, 'S1', '8/02/2011 7:00:00')

选项1:

    SELECT
    [Extent1].[ID], 
    [Extent1].[DocumentID],
    [Extent1].[Status], 
    [Extent1].[DateCreated]
FROM #DocumentStatusLogs AS [Extent1]
    OUTER APPLY (
        SELECT TOP 1
            [Extent2].[ID], 
            [Extent2].[DocumentID],
            [Extent2].[Status], 
            [Extent2].[DateCreated]
        FROM #DocumentStatusLogs AS [Extent2]
        WHERE [Extent1].[DocumentID] = [Extent2].[DocumentID]
        ORDER BY [Extent2].[DateCreated] DESC, [Extent2].[ID] DESC
    ) AS [Project2]
WHERE ([Project2].[ID] IS NULL OR [Project2].[ID] = [Extent1].[ID])

选项2:

SELECT 
    [Limit1].[DocumentID] AS [ID], 
    [Limit1].[DocumentID] AS [DocumentID], 
    [Limit1].[Status] AS [Status], 
    [Limit1].[DateCreated] AS [DateCreated]
FROM (
    SELECT DISTINCT [Extent1].[DocumentID] AS [DocumentID] FROM #DocumentStatusLogs AS [Extent1]
) AS [Distinct1]
    OUTER APPLY  (
        SELECT TOP (1) [Project2].[ID] AS [ID], [Project2].[DocumentID] AS [DocumentID], [Project2].[Status] AS [Status], [Project2].[DateCreated] AS [DateCreated]
        FROM (
            SELECT 
                [Extent2].[ID] AS [ID], 
                [Extent2].[DocumentID] AS [DocumentID], 
                [Extent2].[Status] AS [Status], 
                [Extent2].[DateCreated] AS [DateCreated]
            FROM #DocumentStatusLogs AS [Extent2]
            WHERE [Distinct1].[DocumentID] = [Extent2].[DocumentID]
        )  AS [Project2]
        ORDER BY [Project2].[ID] DESC
    ) AS [Limit1]

在Microsoft SQL Server Management Studio中:在突出显示并运行第一个块后，突出显示选项1和选项2，右键单击->[显示估计的执行计划]。然后运行整个程序以查看结果。

选项1结果:

ID  DocumentID  Status  DateCreated
6   1   S1  8/2/11 3:00
5   2   S3  8/1/11 6:00
6   3   S1  8/2/11 7:00

选项2结果:

ID  DocumentID  Status  DateCreated
6   1   S1  8/2/11 3:00
5   2   S3  8/1/11 6:00
6   3   S1  8/2/11 7:00

注意:

当我想要一个连接为1到-(多个连接中的1个)时，我倾向于使用APPLY。 如果我想要连接为1对多或多对多，则使用JOIN。 我使用ROW_NUMBER()避免CTE，除非我需要做一些高级的事情，并且可以接受窗口性能损失。

我还避免在WHERE或ON子句中使用EXISTS / IN子查询，因为我曾经经历过这样会导致一些糟糕的执行计划。但具体里程各不相同。在需要的时候随时随地检查执行计划和概要文件的性能!

在你想避免使用row_count()的场景中，你也可以使用左连接:

select ds.DocumentID, ds.Status, ds.DateCreated 
from DocumentStatusLogs ds
left join DocumentStatusLogs filter 
    ON ds.DocumentID = filter.DocumentID
    -- Match any row that has another row that was created after it.
    AND ds.DateCreated < filter.DateCreated
-- then filter out any rows that matched 
where filter.DocumentID is null 

对于示例模式，你也可以使用"not in subquery"，它通常编译到与左连接相同的输出:

select ds.DocumentID, ds.Status, ds.DateCreated 
from DocumentStatusLogs ds
WHERE ds.ID NOT IN (
    SELECT filter.ID 
    FROM DocumentStatusLogs filter
    WHERE ds.DocumentID = filter.DocumentID
        AND ds.DateCreated < filter.DateCreated)

注意，如果表没有至少一个单列唯一键/约束/索引(在本例中是主键“Id”)，那么子查询模式将无法工作。

这两个查询往往比row_count()查询(由query Analyzer衡量)更“昂贵”。但是，您可能会遇到它们更快地返回结果或启用其他优化的情况。

这是一个相当老的话题，但我想我要发表我的意见，就像公认的答案对我来说并不是特别有效一样。我在一个大型数据集上尝试了gbn的解决方案，发现它非常慢(在SQL Server 2012中500多万条记录上>45秒)。看一下执行计划，很明显问题在于它需要一个SORT操作，这会大大降低速度。

下面是我从实体框架中提取的一个替代方案，它不需要SORT操作，只进行非聚集索引搜索。这将在前面提到的记录集中将执行时间减少到< 2秒。

SELECT 
[Limit1].[DocumentID] AS [DocumentID], 
[Limit1].[Status] AS [Status], 
[Limit1].[DateCreated] AS [DateCreated]
FROM   (SELECT DISTINCT [Extent1].[DocumentID] AS [DocumentID] FROM [dbo].[DocumentStatusLogs] AS [Extent1]) AS [Distinct1]
OUTER APPLY  (SELECT TOP (1) [Project2].[ID] AS [ID], [Project2].[DocumentID] AS [DocumentID], [Project2].[Status] AS [Status], [Project2].[DateCreated] AS [DateCreated]
    FROM (SELECT 
        [Extent2].[ID] AS [ID], 
        [Extent2].[DocumentID] AS [DocumentID], 
        [Extent2].[Status] AS [Status], 
        [Extent2].[DateCreated] AS [DateCreated]
        FROM [dbo].[DocumentStatusLogs] AS [Extent2]
        WHERE ([Distinct1].[DocumentID] = [Extent2].[DocumentID])
    )  AS [Project2]
    ORDER BY [Project2].[ID] DESC) AS [Limit1]

Now I'm assuming something that isn't entirely specified in the original question, but if your table design is such that your ID column is an auto-increment ID, and the DateCreated is set to the current date with each insert, then even without running with my query above you could actually get a sizable performance boost to gbn's solution (about half the execution time) just from ordering on ID instead of ordering on DateCreated as this will provide an identical sort order and it's a faster sort.

CROSS APPLY是我在解决方案中使用的方法，因为它对我和客户的需求都有效。从我所读到的，应该提供最好的整体性能，如果他们的数据库大幅增长。

I've done some timings over the various recommendations here, and the results really depend on the size of the table involved, but the most consistent solution is using the CROSS APPLY These tests were run against SQL Server 2008-R2, using a table with 6,500 records, and another (identical schema) with 137 million records. The columns being queried are part of the primary key on the table, and the table width is very small (about 30 bytes). The times are reported by SQL Server from the actual execution plan.

Query                                  Time for 6500 (ms)    Time for 137M(ms)

CROSS APPLY                                    17.9                17.9
SELECT WHERE col = (SELECT MAX(COL)…)           6.6               854.4
DENSE_RANK() OVER PARTITION                     6.6               907.1

我认为真正令人惊讶的是，无论涉及的行数是多少，CROSS APPLY的时间都是如此一致。

这里有3种不同的方法来解决这个问题，以及为每个查询建立索引的最佳选择(请自己尝试索引，并查看逻辑读取、消耗时间和执行计划。我根据自己的经验提供了关于此类查询的建议，但没有针对这个特定问题执行)。

方法1:使用ROW_NUMBER()。如果rowstore索引不能提高性能，对于具有聚合和分组的查询以及始终按不同列排序的表，可以尝试使用非聚集/聚集的columnstore索引，columnstore索引通常是最佳选择。

;WITH CTE AS
    (
       SELECT   *,
                RN = ROW_NUMBER() OVER (PARTITION BY DocumentID ORDER BY DateCreated DESC)
       FROM     DocumentStatusLogs
    )
    SELECT  ID      
        ,DocumentID 
        ,Status     
        ,DateCreated
    FROM    CTE
    WHERE   RN = 1;

方法2:使用FIRST_VALUE。如果rowstore索引不能提高性能，对于具有聚合和分组的查询以及始终按不同列排序的表，可以尝试使用非聚集/聚集的columnstore索引，columnstore索引通常是最佳选择。

SELECT  DISTINCT
    ID      = FIRST_VALUE(ID) OVER (PARTITION BY DocumentID ORDER BY DateCreated DESC)
    ,DocumentID
    ,Status     = FIRST_VALUE(Status) OVER (PARTITION BY DocumentID ORDER BY DateCreated DESC)
    ,DateCreated    = FIRST_VALUE(DateCreated) OVER (PARTITION BY DocumentID ORDER BY DateCreated DESC)
FROM    DocumentStatusLogs;

方法3:使用CROSS APPLY。在DocumentStatusLogs表上创建涵盖查询中使用的列的行存储索引应该足以覆盖查询，而不需要columnstore索引。

SELECT  DISTINCT
    ID      = CA.ID
    ,DocumentID = D.DocumentID
    ,Status     = CA.Status 
    ,DateCreated    = CA.DateCreated
FROM    DocumentStatusLogs D
    CROSS APPLY (
            SELECT  TOP 1 I.*
            FROM    DocumentStatusLogs I
            WHERE   I.DocumentID = D.DocumentID
            ORDER   BY I.DateCreated DESC
            ) CA;