命令行操作Hive

朴灿烈づ我的快乐病毒、 2022-09-01 14:56 258阅读 0赞

针对命令行这种方式，其实还有两种使用  
第一个是使用bin目录下的hive命令，这个是从hive一开始就支持的使用方式。后来又出现一个beeline命令，它是通过HiveServer2服务连接hive，它是一个轻量级的客户端工具，所以 后来官方开始推荐使用这个。

1:先看第一种，这种直接就可以连进去

[root@test apache-hive-3.1.2-bin]# bin/hive
    Hive-on-MR is deprecated in Hive 2 and may not be available in the future ver
    Hive Session ID = e106db23-21b8-488f-8c13-85efd30f395a
    hive>

这里有一行信息提示，从Hive2开始Hive-on-MR就过时了，并且在以后的版本中可能就不维护了，建议 使用其它的计算引擎，例如:`spark`或者`tez`

下面以hive开头的内容就是说明我们进入了Hive的命令行中，在这里就可以写Hive的SQL了

创建一个表

hive> create table t1(id int,name string);
    OK
    Time taken: 1.064 seconds

查看有哪些表

hive> show tables;
    OK
    t1
    Time taken: 0.18 seconds

向表里面添加数据

hive> insert into t1(id,name) values(1,"zs");
    Query ID = root_20200506162317_02b2802a-5640-4656-88e6-1e4eaa811017
    Total jobs = 3
    Launching Job 1 out of 3
    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=<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 mapreduce.job.reduces=<number>
    Starting Job = job_1588737504319_0001, Tracking URL = http://bigdata01:8088/
    Kill Command = /data/soft/hadoop-3.2.0/bin/mapred job -kill job_15887375043 Hadoop job information for Stage-1: number of mappers: 1; number of reducers 2020-05-06 16:23:36,954 Stage-1 map = 0%, reduce = 0%
    2020-05-06 16:23:47,357 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 3.1 2020-05-06 16:23:56,917 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 5 MapReduce Total cumulative CPU time: 5 seconds 160 msec
    Ended Job = job_1588737504319_0001
    Stage-4 is selected by condition resolver.
    Stage-3 is filtered out by condition resolver.
    Stage-5 is filtered out by condition resolver.
    Moving data to directory hdfs://bigdata01:9000/user/hive/warehouse/t1/.hive- Loading data to table default.t1
    MapReduce Jobs Launched:  Stage-Stage-1: Map: 1 Reduce: 1 Cumulative CPU: 5.16 sec HDFS Read: 1520 Total MapReduce CPU Time Spent: 5 seconds 160 msec
    OK
    Time taken: 41.534 seconds

可以看到，此时就产生了MapReduce任务

查询数据

hive> select * from t1;
    OK
    1       zs
    Time taken: 2.438 seconds, Fetched: 1 row(s)

删除表

hive> drop table t1;
    OK
    Time taken: 0.89 seconds

2:接着看一下第二种方式 beeline  
我们要先启动hive的服务

bin/hiveserver2

然后使用beeline连接

bin/beeline -u jdbc:hive2://localhost:10000

这里可能会碰到匿名用户对/tmp/hadoop-yarn没有权限的问题，解决方案有两个：

1.  给hdfs中的`/tmp/hadoop-yarn`设置777权限，让匿名用户具备权限可以直接给tmp及下面的所有目录设置777权限

hdfs dfs -chmod -R 777 /tmp