hive 多字段同时count(distinct)优化
1. 需求与现状:
源表:pcup_3month_login_dtl_mes,记录数12亿,文件数300
统计SQL:insert overwrite table pcup_logininfo_tmp partition(data_type = 1) select popt_id, null as sndaid, count(distinct case when login_date>='2012-02-01' and login_date<'2012-05-01' then login_date else null end) as m3_login, null as m3_login_top5, count(distinct case when login_date>='2012-05-01' and login_date<='2012-05-09' then login_date else null end) as mn_login, null as mn_login_top5, null as m3_apptype, null as mn_apptype, count(distinct case when login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='1' then login_date else null end) as m3_g_login, null as m3_g_login_top5, count(distinct case when login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='2' then login_date else null end) as m3_l_login, null as m3_l_login_top5, count(distinct case when login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='3' then login_date else null end) as m3_s_login, null as m3_s_login_top5, count(distinct case when login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='4' then login_date else null end) as m3_o_login, null as m3_o_login_top5, count(distinct case when login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='1' then login_date else null end) as mn_g_login, null as mn_g_login_top5, count(distinct case when login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='2' then login_date else null end) as mn_l_login, null as mn_l_login_top5, count(distinct case when login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='3' then login_date else null end) as mn_s_login, null as mn_s_login_top5, count(distinct case when login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='4' then login_date else null end) as mn_o_login, null as mn_o_login_top5 from pcup_3month_login_dtl_mes group by popt_id;
特点:group by 维度少,多字段count(distinct), reduce task非常少(7个)耗时:1个半小时以上
2. 优化思路:
利用unionall+groupby+rownumber代替所有的count(distinct);
根据文件大小设置合理的reduce task数量;3. 优化后的代码:耗时20分钟左右SET mapred.reduce.tasks = 100;
//初步过滤+去重
create table lxw_test3 as select popt_id,login_date,apptypeid from pcup_3month_login_dtl_mes where login_date>='2012-02-01' and login_date <= '2012-05-09' group by popt_id,login_date,apptypeid;
//利用rownumber 函数做去重标记
add jar hdfs://nn.dc.sh-wgq.sdo.com:8020/group/p_sdo_data/udf/snda_udf.jar; CREATE TEMPORARY FUNCTION row_number AS 'com.snda.hive.udf.UDFrow_number'; create table lxw_test4 as select type,popt_id,login_date,row_number(type,login_date,popt_id) as rn from ( select type,popt_id,login_date from ( select 'm3_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-02-01' and login_date<'2012-05-01' union all select 'mn_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-05-01' and login_date<='2012-05-09' union all select 'm3_g_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='1' union all select 'm3_l_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='2' union all select 'm3_s_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='3' union all select 'm3_o_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-02-01' and login_date<'2012-05-01' and apptypeid='4' union all select 'mn_g_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='1' union all select 'mn_l_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='2' union all select 'mn_s_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='3' union all select 'mn_o_login' as type,popt_id,login_date from lxw_test3 where login_date>='2012-05-01' and login_date<='2012-05-09' and apptypeid='4' ) x distribute by type,login_date,popt_id sort by type,login_date,popt_id ) y;
//用普通的聚合函数进行汇总
insert overwrite table pcup_logininfo_tmp partition(data_type = 99) select popt_id, null as sndaid, sum(case when type = 'm3_login' and rn = 1 then 1 else 0 end) as m3_login, null as m3_login_top5, sum(case when type = 'mn_login' and rn = 1 then 1 else 0 end) as mn_login, null as mn_login_top5, null as m3_apptype, null as mn_apptype, sum(case when type = 'm3_g_login' and rn = 1 then 1 else 0 end) as m3_g_login, null as m3_g_login_top5, sum(case when type = 'm3_l_login' and rn = 1 then 1 else 0 end) as m3_l_login, null as m3_l_login_top5, sum(case when type = 'm3_s_login' and rn = 1 then 1 else 0 end) as m3_s_login, null as m3_s_login_top5, sum(case when type = 'm3_o_login' and rn = 1 then 1 else 0 end) as m3_o_login, null as m3_o_login_top5, sum(case when type = 'mn_g_login' and rn = 1 then 1 else 0 end) as mn_g_login, null as mn_g_login_top5, sum(case when type = 'mn_l_login' and rn = 1 then 1 else 0 end) as mn_l_login, null as mn_l_login_top5, sum(case when type = 'mn_s_login' and rn = 1 then 1 else 0 end) as mn_s_login, null as mn_s_login_top5, sum(case when type = 'mn_o_login' and rn = 1 then 1 else 0 end) as mn_o_login, null as mn_o_login_top5 from lxw_test4 group by popt_id
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