在SQL Server中优化ROW_NUMBER() [英] Optimizing ROW_NUMBER() in SQL Server

问题描述

我们有许多机器会不定期地将数据记录到数据库中.对于每个记录，我想获取从此记录到上一个记录之间的时间段.

We have a number of machines which record data into a database at sporadic intervals. For each record, I'd like to obtain the time period between this recording and the previous recording.

我可以使用ROW_NUMBER进行以下操作:

I can do this using ROW_NUMBER as follows:

WITH TempTable AS (
    SELECT *, ROW_NUMBER() OVER (PARTITION BY Machine_ID ORDER BY Date_Time) AS Ordering
    FROM dbo.DataTable
)

SELECT [Current].*, Previous.Date_Time AS PreviousDateTime
FROM TempTable AS [Current]
INNER JOIN TempTable AS Previous 
    ON [Current].Machine_ID = Previous.Machine_ID
    AND Previous.Ordering = [Current].Ordering + 1

问题是，它真的很慢(在大约有1万个条目的表上花费了几分钟)-我尝试在Machine_ID和Date_Time上创建单独的索引，并使用单个连接索引，但是没有帮助

The problem is, it goes really slow (several minutes on a table with about 10k entries) - I tried creating separate indicies on Machine_ID and Date_Time, and a single joined-index, but nothing helps.

反正有没有重写此查询以使其运行得更快?

Is there anyway to rewrite this query to go faster?

推荐答案

与该版本相比如何?:

SELECT x.*
    ,(SELECT MAX(Date_Time)
      FROM dbo.DataTable
      WHERE Machine_ID = x.Machine_ID
          AND Date_Time < x.Date_Time
    ) AS PreviousDateTime
FROM dbo.DataTable AS x

还是这个版本?:

SELECT x.*
    ,triang_join.PreviousDateTime
FROM dbo.DataTable AS x
INNER JOIN (
    SELECT l.Machine_ID, l.Date_Time, MAX(r.Date_Time) AS PreviousDateTime
    FROM dbo.DataTable AS l
    LEFT JOIN dbo.DataTable AS r
    ON l.Machine_ID = r.Machine_ID
        AND l.Date_Time > r.Date_Time
    GROUP BY l.Machine_ID, l.Date_Time
) AS triang_join
ON triang_join.Machine_ID = x.Machine_ID
    AND triang_join.Date_Time = x.Date_Time

在Machine_ID，Date_Time上使用索引，并且为了获得正确的结果，我都认为这是唯一的.

Both would perform best with an index on Machine_ID, Date_Time and for correct results, I'm assuming that this is unique.

您没有提到*中隐藏的内容，这有时可能意味着很多，因为Machine_ID和Date_Time索引通常不会被覆盖，并且如果您那里有很多列或它们有很多数据，. ..

You haven't mentioned what is hidden away in * and that can sometimes means a lot since a Machine_ID, Date_Time index will not generally be covering and if you have a lot of columns there or they have a lot of data, ...

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