hive> select * from tb_in_base where job_time=030729 order by devid limit 2;

Total MapReduce jobs = 1

Launching Job 1 out of 1

Number of reduce tasks determined at compile time: 1

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

set hive.exec.reducers.bytes.per.reducer=

In order to limit the maximum number of reducers:

set hive.exec.reducers.max=

In order to set a constant number of reducers:

set mapred.reduce.tasks=

Starting Job = job_201307151509_15432, Tracking URL = http://mwtec-50:50030/jobdetails.jsp jobid=job_201307151509_15432

Kill Command = /home/hadoop/hadoop-0.20.2/bin/hadoop job -Dmapred.job.tracker=mwtec-50:9002 -kill job_201307151509_15432

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

2013-08-05 16:47:32,900 Stage-1 map = 0%, reduce = 0%

2013-08-05 16:47:34,920 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:35,927 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:36,934 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:37,941 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:38,946 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:39,953 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:40,959 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:41,965 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.39 sec

2013-08-05 16:47:42,971 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.05 sec

2013-08-05 16:47:43,977 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.05 sec

2013-08-05 16:47:44,983 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.05 sec

MapReduce Total cumulative CPU time: 3 seconds 50 msec

Ended Job = job_201307151509_15432

MapReduce Jobs Launched:

Job 0: Map: 1 Reduce: 1 Cumulative CPU: 3.05 sec HDFS Read: 458 HDFS Write: 44 SUCCESS

Total MapReduce CPU Time Spent: 3 seconds 50 msec

OK

1 121212 test1 030729

2 131313 test2 030729

Time taken: 17.597 seconds

结果说明：严格模式下，使用order by 不仅需要指定limit 数量，若有表分区还需要指定表分区。

2.2 sort by

sort可以控制每个reduce产生的文件都是排序，再对多个排序的好的文件做二次归并排序。sort by 特点如下：

1) . sort by 基本受hive.mapred.mode是否为strict、nonstrict的影响，但若有分区需要指定分区。

2). sort by 的数据在同一个reduce中数据是按指定字段排序。

3). sort by 可以指定执行的reduce个数，如：set mapred.reduce.tasks=5 ,对输出的数据再执行归并排序，即可以得到全部结果。

-- 在hive.mapred.mode为nonstrict时

hive> select id,devid from tb_in_base sort by devid;

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=

In order to limit the maximum number of reducers:

set hive.exec.reducers.max=

In order to set a constant number of reducers:

set mapred.reduce.tasks=

Starting Job = job_201307151509_15434, Tracking URL = http://mwtec-50:50030/jobdetails.jsp jobid=job_201307151509_15434

Kill Command = /home/hadoop/hadoop-0.20.2/bin/hadoop job -Dmapred.job.tracker=mwtec-50:9002 -kill job_201307151509_15434

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