Hive中SQL的优化技巧，核心思想是避免数据倾斜。

1、避免在同一个查询中同时出现count, distinct,group by

2、left join 时把小数据量的表放在前面

3、尽量使用子查询

参数配置

SET mapred.reduce.tasks=50;
SET mapreduce.reduce.memory.mb=6000;
SET mapreduce.reduce.shuffle.memory.limit.percent=0.06;

涉及数据倾斜的话，主要是reduce中数据倾斜的问题，可能通过设置hive中reduce的并行数，reduce的内存大小单位为m，reduce中 shuffle的刷磁盘的比例，来解决。

实例一

–分月
select substr(a.day,1,6)month,count(distinct a.userid)
from dms.tracklog_5min a
join default.site_activeuser_tmp c
on a.userid=c.id
where a.day>=’201505′ and a.day<‘201506’
group by substr(a.day,1,6) ;

–优化后
select ‘201505’,count(*) from
(
select distinct c.userid
from
(select userid from default.site_activeuser_tmp where month=’201505′) c
left join
(
select userid from
dms.tracklog_5min
where day>=’201505′ and day<‘201506’
) tmp
on tmp.userid=c.userid
) t;

实例二

–分事业部
select substr(a.day,1,6)month,count(distinct a.userid) ,b.dept_name
from dms.tracklog_5min a join default.d_channel b
on a.host=b.host
join default.site_activeuser_tmp c
on a.userid=c.id
where a.day>=’201505′ and a.day<‘201506’
group by substr(a.day,1,6),b.dept_name;

–优化后
SET mapred.reduce.tasks=50;
SET mapreduce.reduce.memory.mb=6000;
SET mapreduce.reduce.shuffle.memory.limit.percent=0.06;

select “201505” month,count(t.userid),t.dept_name
from
(select userid from default.site_activeuser_tmp where month=’201505′) c
left join
(
select distinct a.userid userid,b.dept_name dept_name from default.d_channel b
left join
(select host,userid from dms.tracklog_5min where day>=’201505′ and day<‘201506’ ) a
on a.host=b.host
)t
on t.userid=c.userid
group by t.dept_name ;

实例三

–分产品
select substr(a.day,1,6)month,count(distinct a.userid) ,b.dept_name,b.prod_name
from dms.tracklog_5min a join default.d_channel b
on a.host=b.host
join default.site_activeuser_tmp c
on a.userid=c.id
where a.day>=’201505′ and a.day<‘201506’
group by substr(a.day,1,6),b.dept_name,b.prod_name;

–优化后
select “201505” month,count(t.userid) cnt,t.dept_name dept_name,t.prod_name prod_name
from
(select userid from default.site_activeuser_tmp where month=’201505′) c
left join
(
select distinct a.userid userid,b.dept_name dept_name,b.prod_name prod_name from default.d_channel b
left join
(select host,userid from dms.tracklog_5min where day>=’201505′ and day<‘201506’ ) a
on a.host=b.host
)t
on t.userid=c.userid
group by t.prod_name,t.dept_name ;