我的代码从每组中选择top 1

select a.* from #DocumentStatusLogs a where 
 datecreated in( select top 1 datecreated from #DocumentStatusLogs b
where 
a.documentid = b.documentid
order by datecreated desc
)

如果你担心性能问题，你也可以用MAX()这样做:

SELECT *
FROM DocumentStatusLogs D
WHERE DateCreated = (SELECT MAX(DateCreated) FROM DocumentStatusLogs WHERE ID = D.ID)

ROW_NUMBER()要求对SELECT语句中的所有行进行排序，而MAX则不需要。应该会大大加快你的查询速度。

;WITH cte AS
(
   SELECT *,
         ROW_NUMBER() OVER (PARTITION BY DocumentID ORDER BY DateCreated DESC) AS rn
   FROM DocumentStatusLogs
)
SELECT *
FROM cte
WHERE rn = 1

如果您希望每天有2个条目，那么这将任意选择一个。要获得一天的两个条目，请使用DENSE_RANK代替

至于是否正常化，这取决于你是否想:

在两个地方保持状态 保存状态历史 .．.

目前，您保留了状态历史。如果你也想在父表中保持最新状态(这是非规范化的)，你需要一个触发器来维持父表中的“状态”。或者删除这个状态历史表。

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;

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.