我知道这是一个旧的线程，但TOP 1与TIES解决方案是相当不错的，可能有助于阅读一些解决方案。

select top 1 with ties
   DocumentID
  ,Status
  ,DateCreated
from DocumentStatusLogs
order by row_number() over (partition by DocumentID order by DateCreated desc)

select top 1 with ties子句告诉SQL Server要返回每个组的第一行。但是SQL Server如何知道如何对数据进行分组呢?这就是按row_number()的顺序除以(按documententid分区的顺序除以DateCreated desc的顺序。分区后的列定义了SQL Server如何对数据进行分组。在每个组中，行将根据列的顺序进行排序。排序之后，查询中将返回每个组中的第一行。

关于TOP子句的更多信息可以在这里找到。

SELECT documentid, 
       status, 
       datecreated 
FROM   documentstatuslogs dlogs 
WHERE  status = (SELECT status 
                 FROM   documentstatuslogs 
                 WHERE  documentid = dlogs.documentid 
                 ORDER  BY datecreated DESC 
                 LIMIT  1) 

我刚学会如何使用交叉应用。下面是如何在这种情况下使用它:

 select d.DocumentID, ds.Status, ds.DateCreated 
 from Documents as d 
 cross apply 
     (select top 1 Status, DateCreated
      from DocumentStatusLogs 
      where DocumentID = d.DocumentId
      order by DateCreated desc) as ds

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。

一些数据库引擎*开始支持允许过滤窗口函数结果的qualifier子句(接受的答案使用该子句)。

所以公认的答案可以变成

SELECT *, ROW_NUMBER() OVER (PARTITION BY DocumentID ORDER BY DateCreated DESC) AS rn
FROM DocumentStatusLogs
QUALIFY rn = 1

查看这篇文章以获得更深入的解释:https://jrandrews.net/the-joy-of-qualify

您可以使用此工具查看哪个数据库支持此子句:https://www.jooq.org/translate/ 当目标方言不支持qualifier子句时，可以选择转换它。

*Teradata, BigQuery, H2, Snowflake…

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。