hive having count 不能去重

本文讨论了在Hive查询中使用having子句结合distinct计数时遇到的问题,并提供了解决方案。通过调整查询语法,确保正确执行去重计数并满足having条件,最终成功获取所需数据。

hive在使用having count()是,不支持去重计数

 

hive (default)> select username from t_test_phonenum where ds=20150701 group by username having count(distinct sex)>1 limit 10; 

FAILED: SemanticException [Error 10002]: Line 1:95 Invalid column reference 'sex'

 

hive (default)> select username from t_test_phonenum where ds=20150701 group by username having count(sex)>1 limit 10;          

Total MapReduce jobs = 1

Launching Job 1 out of 1

Number of reduce tasks not specified. Estimated from input data size: 1

In order to change the average load for a reducer (in bytes):

  set hive.exec.reducers.bytes.per.reducer=<number>

In order to limit the maximum number of reducers:

  set hive.exec.reducers.max=<number>

In order to set a constant number of reducers:

  set mapred.reduce.tasks=<number>

Starting Job = job_201503201830_2570778, Tracking URL = http://10-198-131-242:8080/jobdetails.jsp?jobid=job_201503201830_2570778

Kill Command = /data/home/hadoop-1.2.1/libexec/../bin/hadoop job  -kill job_201503201830_2570778

Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1

2015-07-03 11:07:16,954 Stage-1 map = 0%,  reduce = 0%

2015-07-03 11:07:33,530 Stage-1 map = 100%,  reduce = 0%

2015-07-03 11:07:47,620 Stage-1 map = 100%,  reduce = 33%, Cumulative CPU 14.32 sec

2015-07-03 11:07:55,742 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 20.78 sec

MapReduce Total cumulative CPU time: 20 seconds 780 msec

Ended Job = job_201503201830_2570778

MapReduce Jobs Launched: 

Job 0: Map: 1  Reduce: 1   Cumulative CPU: 20.78 sec   HDFS Read: 17371199 HDFS Write: 98 SUCCESS

Total MapReduce CPU Time Spent: 20 seconds 780 msec

OK

02541213XXXXX

 

特此记录一下

 

评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符  | 博主筛选后可见
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值