Session重叠问题学习(六)--极致优化
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接前文
Session重叠问题学习(二),这是问题和需求的描述,执行时间90秒
http://blog.itpub.net/29254281/viewspace-2150229/
Session重叠问题学习(三)--优化,一次优化后,执行时间25秒
http://blog.itpub.net/29254281/viewspace-2150259/
Session重叠问题学习(四)--再优化,二次优化后,执行时间10秒
http://blog.itpub.net/29254281/viewspace-2150297/
Session重叠问题学习(五)--最优化,三次优化后,执行时间1.6秒
http://blog.itpub.net/29254281/viewspace-2150339/
周五晚上终于把这个算法初步实现了.
连续加班忙碌了一个星期,终于有点曙光了.
从这个问题的缘起,到目前应该已经优化了快100倍了
但是周末的时候,想想还是不对.
小花狸Session合并算法(对,以后这个算法就叫这个名称了)实现的合并速度应该是非常快的.代价仅仅是扫描一遍记录.
这1.6秒到底用在哪里了?
后来经过反复调试.发现还有两块可以优化改进的地方.
改进后的过程如下:
第一处改进
原来同一房间同一用户重叠时间合并,然后再拆分跨天数据,用的是一条SQL
现在改进如下
先把同一房间同一用户的重叠部分合并,然后暂存临时表
记录最大的间隔时间,然后再拆分数据
拆分数据的时候 使用STRAIGHT_JOIN 强制连接顺序.
这样避免因为数字辅助表过大,而导致性能陡然变差.
第二处改进
原来使用distinct的查询, 都改为在临时表上增加主键.
然后使用insert ignore into 代替 insert into
这样大概优化了300毫秒
经过反复优化之后,执行时间大致稳定在1250毫秒 至 1300 毫秒
各个部分耗时分析如下
填充tmp_s,合并同一房间同一用户的重叠部分,耗时655毫秒
填充t1,拆分跨天的用户数据,耗时62毫秒
填充t2,用户时间段首尾相交或者首尾全部重合的数据拆分,耗时140毫秒
填充tmp_min_range,计算最小间隔范围,耗时156毫秒
小花狸Session合并算法,耗时219毫秒
结果统计展示,耗时47毫秒
Session重叠问题学习(二),这是问题和需求的描述,执行时间90秒
http://blog.itpub.net/29254281/viewspace-2150229/
Session重叠问题学习(三)--优化,一次优化后,执行时间25秒
http://blog.itpub.net/29254281/viewspace-2150259/
Session重叠问题学习(四)--再优化,二次优化后,执行时间10秒
http://blog.itpub.net/29254281/viewspace-2150297/
Session重叠问题学习(五)--最优化,三次优化后,执行时间1.6秒
http://blog.itpub.net/29254281/viewspace-2150339/
周五晚上终于把这个算法初步实现了.
连续加班忙碌了一个星期,终于有点曙光了.
从这个问题的缘起,到目前应该已经优化了快100倍了
但是周末的时候,想想还是不对.
小花狸Session合并算法(对,以后这个算法就叫这个名称了)实现的合并速度应该是非常快的.代价仅仅是扫描一遍记录.
这1.6秒到底用在哪里了?
后来经过反复调试.发现还有两块可以优化改进的地方.
改进后的过程如下:
- drop procedure p;
- DELIMITER $$
- CREATE DEFINER=`root`@`localhost` PROCEDURE `p`()
- BEGIN
- declare done int default 0;
- declare v_roomid bigint;
- declare v_time timestamp(6);
- declare v_cur_type smallint;
- declare v_before_roomid bigint default -1;
- declare v_before_type smallint default -1;
- declare v_before_time timestamp(6) ;
- declare v_num bigint default 0;
- declare cur_test CURSOR for select roomid,type,timepoint from tmp_time_point order by roomid,timepoint,type ;
- DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = 1;
- drop table if exists t1;
- drop table if exists t2;
- drop table if exists tmp_time_point;
- drop table if exists tmp_result;
- drop table if exists tmp_min_range;
- drop table if exists tmp_s;
- CREATE temporary TABLE `t1` (
- `roomid` int(11) NOT NULL DEFAULT '0',
- `userid` bigint(20) NOT NULL DEFAULT '0',
- `s` timestamp(6),
- `e` timestamp(6),
- primary key(roomid,userid,s,e)
- ) ENGINE=memory;
- CREATE temporary TABLE `t2` (
- `roomid` int(11) NOT NULL DEFAULT '0',
- `s` timestamp(6),
- `e` timestamp(6)
- ) ENGINE=memory;
- CREATE temporary TABLE `tmp_min_range` (
- `roomid` int(11) NOT NULL DEFAULT '0',
- `s` timestamp(6),
- `e` timestamp(6),
- primary key(roomid,s,e),
- key(roomid,e)
- ) ENGINE=memory;
- create temporary table tmp_time_point(
- roomid bigint,
- timepoint timestamp(6),
- type smallint,
- key(roomid,timepoint)
- ) engine=memory;
- create temporary table tmp_result(
- roomid bigint,
- timepoint timestamp(6),
- c int
- ) engine=memory;
- create temporary table tmp_s(
- roomid bigint,
- userid bigint,
- s timestamp,
- e timestamp,
- i int
- ) engine=memory;
- SET @A=0;
- SET @B=0;
- insert into tmp_s
- SELECT x.roomid,x.userid,s,e,datediff(e,s)+1 i
- FROM
- (
- (
- SELECT @B:=@B+1 AS id,roomid,userid,s
- FROM (
- SELECT DISTINCT roomid, userid, roomstart AS s
- FROM u_room_log a
- WHERE NOT EXISTS (SELECT *
- FROM u_room_log b
- WHERE a.roomid = b.roomid
- AND a.userid = b.userid
- AND a.roomstart > b.roomstart
- AND a.roomstart <= b.roomend)
- ) AS p
- ) AS x,
- (
- SELECT @A:=@A+1 AS id,roomid,userid,e
- FROM
- (
- SELECT DISTINCT roomid, userid, roomend AS e
- FROM u_room_log a
- WHERE NOT EXISTS (SELECT *
- FROM u_room_log b
- WHERE a.roomid = b.roomid
- AND a.userid = b.userid
- AND a.roomend >= b.roomstart
- AND a.roomend < b.roomend)
- ) AS o
- ) AS y
- )
- WHERE x.id = y.id AND x.roomid = y.roomid AND x.userid = y.userid ;
- select max(i) into @c from tmp_s;
- insert ignore into t1(roomid,userid,s,e)
- select
- roomid, userid,
- if(date(s)!=date(e) and id>1,date(s+interval id-1 date(s+interval id-1 date(e) ,e,date_format(s+interval id-1 '%Y-%m-%d 23:59:59')) e
- from tmp_s t1 STRAIGHT_JOIN
- nums on(nums.id<=t1.i)
- where nums.id<=@c
- ;
- insert into t2 (roomid,s,e)
- select roomid,
- s+interval startnum/1000000 second s,
- e-interval endnum/1000000 second e
- from (
- select
- roomid,
- s,e,
- startnum,
- when @eflag=eflag then @rn:=@rn+1 when @eflag:=eflag then @rn else @rn end endnum
- from (
- select * from (
- select when @sflag=sflag then @rn:=@rn+1 when @sflag:=sflag then @rn else @rn end startnum,roomid,s,e,sflag,eflag from
- (
- select * from
- (
- select t1.*,concat('[',roomid,'],',s) sflag,concat('[',roomid,'],',e) eflag from t1 order by roomid ,sflag
- )a,(select @sflag:='',@rn:=0,@eflag:='') vars
- ) b
- ) bb order by roomid,eflag
- ) c
- ) d ;
- insert into tmp_time_point(roomid,timepoint,type) select roomid,s,1 from t2;
- insert into tmp_time_point(roomid,timepoint,type) select roomid,e,0 from t2;
- insert ignore into tmp_min_range(roomid,s,e)
- select roomid,starttime starttime, endtime endtime from (
- select
- if(@roomid=roomid,@d,'') as starttime,@d:=str_to_date(timepoint,'%Y-%m-%d %H:%i:%s.%f'),@roomid:=roomid,p.roomid,str_to_date(timepoint,'%Y-%m-%d %H:%i:%s.%f') endtime
- from tmp_time_point p,(select @d:='',@roomid:=-1) vars
- order by roomid,timepoint
- ) v4 where starttime!='' and date(starttime)=date(endtime);
- open cur_test;
- repeat
- fetch cur_test into v_roomid,v_cur_type,v_time;
- if done !=1 then
- -- 第一行或者每个房间的第一行
- if v_before_roomid=-1 or v_roomid!=v_before_roomid then
- set v_before_roomid:=v_roomid;
- set v_before_type:=1;
- set v_before_time:='0000-00-00 00:00:00';
- set v_num:=0;
- end if;
- if v_before_type=1 then
- set v_num:=v_num+1;
- insert into tmp_result(roomid,timepoint,c) values(v_roomid,v_time,v_num);
- end if;
- if v_before_type=0 then
- set v_num:=v_num-1;
- insert into tmp_result(roomid,timepoint,c) values(v_roomid,v_time,v_num);
- end if;
- set v_before_roomid:=v_roomid;
- set v_before_type:=v_cur_type;
- set v_before_time:=v_time;
- end if;
- until done end repeat;
- close cur_test;
- select roomid,date(s) dt,round(second,date_format(s,'%Y-%m-%d %H:%i:%s'),date_format(e,'%Y-%m-%d %H:%i:%s')))/60) ts,max(c)-1 c from (
- select a.roomid,a.s,a.e,r.c,r.timepoint from tmp_result r
- inner join
- tmp_min_range a on( r.timepoint=a.e and r.roomid=a.roomid)
- where c>2
- ) a group by roomid,date(s);
- END
第一处改进
原来同一房间同一用户重叠时间合并,然后再拆分跨天数据,用的是一条SQL
现在改进如下
- create temporary table tmp_s(
- roomid bigint,
- userid bigint,
- s timestamp,
- e timestamp,
- i int
- ) engine=memory;
- SET @A=0;
- SET @B=0;
- insert into tmp_s
- SELECT x.roomid,x.userid,s,e,datediff(e,s)+1 i
- FROM
- (
- (
- SELECT @B:=@B+1 AS id,roomid,userid,s
- FROM (
- SELECT DISTINCT roomid, userid, roomstart AS s
- FROM u_room_log a
- WHERE NOT EXISTS (SELECT *
- FROM u_room_log b
- WHERE a.roomid = b.roomid
- AND a.userid = b.userid
- AND a.roomstart > b.roomstart
- AND a.roomstart <= b.roomend)
- ) AS p
- ) AS x,
- (
- SELECT @A:=@A+1 AS id,roomid,userid,e
- FROM
- (
- SELECT DISTINCT roomid, userid, roomend AS e
- FROM u_room_log a
- WHERE NOT EXISTS (SELECT *
- FROM u_room_log b
- WHERE a.roomid = b.roomid
- AND a.userid = b.userid
- AND a.roomend >= b.roomstart
- AND a.roomend < b.roomend)
- ) AS o
- ) AS y
- )
- WHERE x.id = y.id AND x.roomid = y.roomid AND x.userid = y.userid ;
- select max(i) into @c from tmp_s;
- insert ignore into t1(roomid,userid,s,e)
- select
- roomid, userid,
- if(date(s)!=date(e) and id>1,date(s+interval id-1 date(s+interval id-1 date(e) ,e,date_format(s+interval id-1 '%Y-%m-%d 23:59:59')) e
- from tmp_s t1 STRAIGHT_JOIN
- nums on(nums.id<=t1.i)
- where nums.id<=@c
- ;
先把同一房间同一用户的重叠部分合并,然后暂存临时表
记录最大的间隔时间,然后再拆分数据
拆分数据的时候 使用STRAIGHT_JOIN 强制连接顺序.
这样避免因为数字辅助表过大,而导致性能陡然变差.
第二处改进
原来使用distinct的查询, 都改为在临时表上增加主键.
然后使用insert ignore into 代替 insert into
这样大概优化了300毫秒
经过反复优化之后,执行时间大致稳定在1250毫秒 至 1300 毫秒
各个部分耗时分析如下
填充tmp_s,合并同一房间同一用户的重叠部分,耗时655毫秒
填充t1,拆分跨天的用户数据,耗时62毫秒
填充t2,用户时间段首尾相交或者首尾全部重合的数据拆分,耗时140毫秒
填充tmp_min_range,计算最小间隔范围,耗时156毫秒
小花狸Session合并算法,耗时219毫秒
结果统计展示,耗时47毫秒
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