优化我的 T-SQL 查询以提高性能

Question

创建了一个 SQL 查询来汇总一些数据。它很慢，所以我想我会寻求帮助。

Table 是一个日志表，具有：

loc, tag, entrytime, exittime, visits, entrywt, exitwt

我的测试日志中有 700,000 条记录。 entrytime 和 exittime 是纪元值。

我知道我的查询效率很低，因为它会遍历表 4 次。

select 
    loc, edate, tag,
    (select COUNT(*) from mylog as ml 
     where mvlog.loc = ml.loc 
       and mvlog.edate = CONVERT(date, DATEADD(ss, ml.entrytime, '19700101')) 
       and mvlog.tag = ml.tag) as visits,
    (select SUM(entrywt - exitwt) from mylog as ml2 
     where mvlog.loc = ml2.loc 
       and mvlog.edate = CONVERT(date, DATEADD(ss, ml2.entrytime, '19700101')) 
       and mvlog.tag = ml2.tag) as consumed,
    (select SUM(exittime - entrytime) from mylog as ml3 
     where mvlog.loc = ml3.loc 
       and mvlog.edate = CONVERT(date, DATEADD(ss, ml3.entrytime, '19700101')) 
       and mvlog.tag = ml3.tag) as occupancy
from 
    eventlogV as mvlog with (INDEX(pt_index))

索引pt_index 由tag 和loc 列组成。

当我运行这个查询时，它大约在 30 秒内完成。由于我的查询效率低下，我相信它会更好。

任何想法表示赞赏。

Answer 1

似乎您只需 LEFT JOIN mylog 到 eventlogV 一次并获得相同的结果。

SELECT  mvlog.loc,
        mvlog.edate,
        mvlog.tag,
        COUNT(ml.loc) AS visits,
        SUM(entrywt - exitwt) AS consumed,
        SUM(exittime - entrytime) AS occupancy
FROM    eventlogV AS mvlog
        LEFT OUTER JOIN mylog ml ON mvlog.loc = ml.loc
                                    AND mvlog.edate = CONVERT(DATE,DATEADD(ss,ml.entrytime,'19700101'))
                                    AND mvlog.tag = ml.tag
GROUP BY mvlog.loc,
        mvlog.edate,
        mvlog.tag