Hive在查询中使用排序

一 按照某字段排序

hive> select empno,ename,sal from emp order by sal;

Total 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_201708302015_0002, Tracking URL = http://localhost:50030/jobdetails.jsp?jobid=job_201708302015_0002

Kill Command = /opt/hadoop-1.2.1/libexec/../bin/hadoop job -kill job_201708302015_0002

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

2017-08-30 20:30:16,554 Stage-1 map = 0%, reduce = 0%

2017-08-30 20:30:35,866 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.41 sec

2017-08-30 20:30:51,257 Stage-1 map = 100%, reduce = 33%, Cumulative CPU 1.41 sec

2017-08-30 20:30:54,287 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.32 sec

MapReduce Total cumulative CPU time: 3 seconds 320 msec

Ended Job = job_201708302015_0002

MapReduce Jobs Launched:

Job 0: Map: 1 Reduce: 1 Cumulative CPU: 3.32 sec HDFS Read: 635 HDFS Write: 319 SUCCESS

Total MapReduce CPU Time Spent: 3 seconds 320 msec

OK

7369.0 SMITH 4800.0

7900.0 JAMES 4950.0

1001.0 Tome 5000.0

1002.0 Tome 5000.0

7876.0 ADAMS 5100.0

7521.0 WARD 5250.0

7654.0 MARTIN 5250.0

7934.0 MILLER 5300.0

7844.0 TURNER 5500.0

7499.0 ALLEN 5600.0

7788.0 SCOTT 7000.0

7902.0 FORD 7000.0

7782.0 CLARK 8450.0

7698.0 BLAKE 8850.0

7566.0 JONES 9075.0

7839.0 KING 12111.0

Time taken: 61.037 seconds, Fetched: 16 row(s)

二 按表达式排序

hive> select empno,ename,sal,sal*12 from emp order by sal*12;

Total 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_201708302015_0003, Tracking URL = http://localhost:50030/jobdetails.jsp?jobid=job_201708302015_0003

Kill Command = /opt/hadoop-1.2.1/libexec/../bin/hadoop job -kill job_201708302015_0003

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

2017-08-30 20:34:15,655 Stage-1 map = 0%, reduce = 0%

2017-08-30 20:34:25,747 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.07 sec

2017-08-30 20:34:42,236 Stage-1 map = 100%, reduce = 33%, Cumulative CPU 2.07 sec

2017-08-30 20:34:45,276 Stage-1 map = 100%, reduce = 67%, Cumulative CPU 2.07 sec

2017-08-30 20:34:46,288 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 4.24 sec

MapReduce Total cumulative CPU time: 4 seconds 240 msec

Ended Job = job_201708302015_0003

MapReduce Jobs Launched:

Job 0: Map: 1 Reduce: 1 Cumulative CPU: 4.24 sec HDFS Read: 635 HDFS Write: 451 SUCCESS

Total MapReduce CPU Time Spent: 4 seconds 240 msec

OK

7369.0 SMITH 4800.0 57600.0

7900.0 JAMES 4950.0 59400.0

1001.0 Tome 5000.0 60000.0

1002.0 Tome 5000.0 60000.0

7876.0 ADAMS 5100.0 61200.0

7521.0 WARD 5250.0 63000.0

7654.0 MARTIN 5250.0 63000.0

7934.0 MILLER 5300.0 63600.0

7844.0 TURNER 5500.0 66000.0

7499.0 ALLEN 5600.0 67200.0

7788.0 SCOTT 7000.0 84000.0

7902.0 FORD 7000.0 84000.0

7782.0 CLARK 8450.0 101400.0

7698.0 BLAKE 8850.0 106200.0

7566.0 JONES 9075.0 108900.0

7839.0 KING 12111.0 145332.0

Time taken: 46.63 seconds, Fetched: 16 row(s)

三 按别名排序

hive> select empno,ename,sal,sal*12 annsal from emp order by annsal;

Total 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_201708302015_0004, Tracking URL = http://localhost:50030/jobdetails.jsp?jobid=job_201708302015_0004

Kill Command = /opt/hadoop-1.2.1/libexec/../bin/hadoop job -kill job_201708302015_0004

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

2017-08-30 20:36:11,063 Stage-1 map = 0%, reduce = 0%

2017-08-30 20:36:24,233 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.24 sec

2017-08-30 20:36:41,527 Stage-1 map = 100%, reduce = 33%, Cumulative CPU 2.24 sec

2017-08-30 20:36:44,554 Stage-1 map = 100%, reduce = 67%, Cumulative CPU 2.24 sec

2017-08-30 20:36:45,561 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 4.2 sec

MapReduce Total cumulative CPU time: 4 seconds 200 msec

Ended Job = job_201708302015_0004

MapReduce Jobs Launched:

Job 0: Map: 1 Reduce: 1 Cumulative CPU: 4.2 sec HDFS Read: 635 HDFS Write: 451 SUCCESS

Total MapReduce CPU Time Spent: 4 seconds 200 msec

OK

7369.0 SMITH 4800.0 57600.0

7900.0 JAMES 4950.0 59400.0

1001.0 Tome 5000.0 60000.0

1002.0 Tome 5000.0 60000.0

7876.0 ADAMS 5100.0 61200.0

7521.0 WARD 5250.0 63000.0

7654.0 MARTIN 5250.0 63000.0

7934.0 MILLER 5300.0 63600.0

7844.0 TURNER 5500.0 66000.0

7499.0 ALLEN 5600.0 67200.0

7788.0 SCOTT 7000.0 84000.0

7902.0 FORD 7000.0 84000.0

7782.0 CLARK 8450.0 101400.0

7698.0 BLAKE 8850.0 106200.0

7566.0 JONES 9075.0 108900.0

7839.0 KING 12111.0 145332.0

Time taken: 50.667 seconds, Fetched: 16 row(s)

四 按序号排序

必须设置：

set hive.groupby.orderby.position.alias=true;

hive> select empno,ename,sal,sal*12 annsal from emp order by 4;

Total 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_201708302015_0005, Tracking URL = http://localhost:50030/jobdetails.jsp?jobid=job_201708302015_0005

Kill Command = /opt/hadoop-1.2.1/libexec/../bin/hadoop job -kill job_201708302015_0005

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

2017-08-30 20:37:59,324 Stage-1 map = 0%, reduce = 0%

2017-08-30 20:38:07,379 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.08 sec

2017-08-30 20:38:22,512 Stage-1 map = 100%, reduce = 33%, Cumulative CPU 2.08 sec

2017-08-30 20:38:24,535 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.74 sec

MapReduce Total cumulative CPU time: 3 seconds 740 msec

Ended Job = job_201708302015_0005

MapReduce Jobs Launched:

Job 0: Map: 1 Reduce: 1 Cumulative CPU: 3.74 sec HDFS Read: 635 HDFS Write: 451 SUCCESS

Total MapReduce CPU Time Spent: 3 seconds 740 msec

OK

1001.0 Tome 5000.0 60000.0

1002.0 Tome 5000.0 60000.0

7369.0 SMITH 4800.0 57600.0

7499.0 ALLEN 5600.0 67200.0

7521.0 WARD 5250.0 63000.0

7566.0 JONES 9075.0 108900.0

7654.0 MARTIN 5250.0 63000.0

7698.0 BLAKE 8850.0 106200.0

7782.0 CLARK 8450.0 101400.0

7788.0 SCOTT 7000.0 84000.0

7839.0 KING 12111.0 145332.0

7844.0 TURNER 5500.0 66000.0

7876.0 ADAMS 5100.0 61200.0

7900.0 JAMES 4950.0 59400.0

7902.0 FORD 7000.0 84000.0

7934.0 MILLER 5300.0 63600.0

Time taken: 42.186 seconds, Fetched: 16 row(s)

五 关于null

如果含有null

若是升序，则null排在最前面

若是降序，则null排在最后面