作乙個查詢的效能優化。
先清快取
dbcc dropcleanbuffersdbcc freeproccache
原查詢 前人遺留。
1declare
@total
float,@total_person
float,@times_person
float,@date
varchar(50) 2
select
@date
=convert(char(10),getdate(),120) 3
4select
@total
=sum(price*person)*
1.0from db_time t inner
join db_movie m on t.movieid=m.id inner
join db_cinema c on t.cinemaid=
c.id
5where
cast(showdate as date)=
'2014-02-27
'and t.sta=16
7select
@times_person
=sum(1) from db_time t inner
join db_movie m on t.movieid=m.id inner
join db_cinema c on t.cinemaid=
c.id
8where
cast(showdate as date)=
'2014-02-27
'and t.sta=19
10select
@total_person
=sum(person) from db_time t inner
join db_movie m on t.movieid=m.id inner
join db_cinema c on t.cinemaid=
c.id
11where
cast(showdate as date)=
'2014-02-27
'and t.sta=1;
1213
with sr as(14
select
15--
row_number() over(order by sum(price*person) desc) as 'index'
16--,17
movieid id
18,m.name name
19,m.enname
20 ,sum(price*person)*
1.0as
boxoffice
21 ,sum(price*person)*
1.0/
@total
boxpercent
22 ,sum(1
) showcount
23 ,sum(1)*
1.0/
@times_person
showpercent
24 ,sum
(person) audiencecount
25 ,sum(person)*
1.0/
@total_person
audiencepercent
26 ,cast(round(sum(price*person)*
1.0/
sum(person),0) as
int) price
27--
,sum(person)*1.0/sum(1) as test
28--
,sum(person)*1.0 as t1
29--
,sum(1) as t2
30 ,cast(round(sum(person)*
1.0/
sum(1),0) as
int) as
renci
31 ,round(cast(sum(person) as
float)/
sum(seat),4) as
shangzl
32from db_time t inner
join db_movie m on t.movieid=m.id inner
join db_cinema c on t.cinemaid=
c.id
33where
cast(showdate as date)=
'2014-02-27
'and t.sta=134
group
bymovieid,m.name,m.enname35)
3637
select
*from sr order
by boxoffice desc
執行時間18s
最開始想著是把上面3條求總量的查詢改成在一條裡完成，where條件重複多次，想想開脆改成開窗函式好了
經開窗函式改造後的查詢。
1with sr as(2
select
3distinct4--
row_number() over(order by sum(price*person) desc) as 'index'5--
,6movieid id
7,m.name name
8,m.enname
9 ,(sum(price*person) over(partition by movieid))*
1.0as
boxoffice
10 ,(sum(price*person) over(partition by movieid))*
1.0/(sum(price*person) over()) as
boxpercent
11 ,sum(1) over(partition by movieid) as
showcount
12 ,(sum(1) over(partition by movieid))*
1.0/(sum(1) over
()) showpercent
13 ,sum(person) over(partition by
movieid) audiencecount
14 ,((sum(person) over(partition by movieid))*
1.0)/((sum(person) over
())) audiencepercent
15 ,cast(round((sum(price*person) over(partition by movieid))*
1.0/(sum(person) over(partition by movieid)),0) as
int) price
16 ,cast(round(((sum(person) over(partition by movieid))*
1.0/(count(0) over(partition by movieid))),0) as
int) as
renci
17 ,round(cast((sum(person) over(partition by movieid)) as
float)/(sum(seat) over(partition by movieid)),4) as
shangzl
18from db_time t inner
join db_movie m on t.movieid=m.id inner
join db_cinema c on t.cinemaid=
c.id
19where
cast(showdate as date)=
'2014-02-27
'and t.sta=120
)21select
*from sr order
by boxoffice desc
**確實精簡不少，同樣的where子句消除了。（兩個查詢中的rownumber完全沒用，注掉了）
執行時間17s，心裡隱隱期待的是查詢時間有明顯減少，實際查詢時間在誤差範圍內，基本未變化，看來開發開窗函式的目的不是為效能提公升，而是為了方便開發人員編寫查詢**，減少查詢難度，提高查詢可讀性。
查詢計畫有很大變化，經開窗函式改造後的查詢計畫，多了很多「表假離線」的執行步驟
但兩種查詢最耗時的依然是97%聚集索引掃瞄（表上只有id的自增聚集索引）
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