学习自《Hive编程指南》

1. 向管理表中装载数据

hive (default)> load data local inpath "/home/hadoop/workspace/student.txt"> overwrite into table student1;

分区表可以跟 partition (key1 = v1, key2 = v2, …)

有 local ：复制本地路径文件 到 hdfs
无 local：移动 hdfs 文件 到 新的 hdfs 路径

overwrite： 目标文件夹中的数据将会被删除
没有 overwrite ： 把新增加的文件添加到目标文件夹中，不删除原数据

inpath 后的路径下，不能包含任何文件夹

2. 通过查询语句向表中插入数据

hadoop@dblab-VirtualBox:~/workspace$ cat stu.txt
1	michael	male	china
2	ming	male	china1
3	haha	female	china
4	huahua	female	china1

• 创建表，加载数据

hive (default)> create table stu(> id int,> name string,> sex string,> country string)> row format delimited fields terminated by '\t';hive (default)> load data local inpath '/home/hadoop/workspace/stu.txt'> into table stu;

• 通过 select 语句向其他表填入数据

hive (default)> create table employee(> name string,> country string)> row format delimited fields terminated by '\t';

hive (default)> from stu s> insert overwrite table employee> select s.name, s.country where s.id%2=1;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = hadoop_20210408224138_1df23614-7945-40c0-9a4d-df88e4f58ea1
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Job running in-process (local Hadoop)
2021-04-08 22:41:40,081 Stage-1 map = 100%,  reduce = 0%
Ended Job = job_local1437521177_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://localhost:9000/user/hive/warehouse/employee/.hive-staging_hive_2021-04-08_22-41-38_345_1863326332876590299-1/-ext-10000
Loading data to table default.employee
MapReduce Jobs Launched: 
Stage-Stage-1:  HDFS Read: 83 HDFS Write: 180 SUCCESS
Total MapReduce CPU Time Spent: 0 msec

hive (default)> select * from employee;
OK
michael	china
haha	china

• 向多表插入数据

hive (default)> from stu s> insert into table employee> select s.name, s.country where s.sex='female'> insert into table employee1> select s.name, s.country where s.sex='male';
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = hadoop_20210408230623_bc69bccf-348e-467d-b88e-498664f27017
Total jobs = 5
Launching Job 1 out of 5
Number of reduce tasks is set to 0 since there's no reduce operator
Job running in-process (local Hadoop)
2021-04-08 23:06:24,405 Stage-2 map = 100%,  reduce = 0%
Ended Job = job_local2065691620_0003
Stage-5 is selected by condition resolver.
Stage-4 is filtered out by condition resolver.
Stage-6 is filtered out by condition resolver.
Stage-11 is selected by condition resolver.
Stage-10 is filtered out by condition resolver.
Stage-12 is filtered out by condition resolver.
Moving data to directory hdfs://localhost:9000/user/hive/warehouse/employee/.hive-staging_hive_2021-04-08_23-06-23_001_7974131043339100692-1/-ext-10000
Moving data to directory hdfs://localhost:9000/user/hive/warehouse/employee1/.hive-staging_hive_2021-04-08_23-06-23_001_7974131043339100692-1/-ext-10002
Loading data to table default.employee
Loading data to table default.employee1
MapReduce Jobs Launched: 
Stage-Stage-2:  HDFS Read: 470 HDFS Write: 474 SUCCESS
Total MapReduce CPU Time Spent: 0 msechive (default)> select * from employee;
ming	china1
huahua	china1
haha	china
huahua	china1hive (default)> select * from employee1;
michael	china
ming	china1

3. 动态分区插入

hive (default)> from stu s> insert overwrite table employee2> partition (country, sex)> select s.id, s.name, s.country, s.sex;hive (default)> select * from employee2;
OK
3	haha	china	female
1	michael	china	male
4	huahua	china1	female
2	ming	china1	male

4. 从单个查询语句创建表并加载数据

表的模式由 select 生成

hive (default)> create table employee3> as select id, name from stu> where country='china';hive (default)> select * from employee3;
1	michael
3	haha

此功能不能用于外部表（数据没有装载，在外部）

5. 导出数据

hive (default)> from stu s> insert overwrite local directory '/tmp/employee'> select s.id, s.name, s.sex> where country='china';

可以同时写入多个文件，insert 重复写几次

hive (default)> ! ls /tmp/employee -r;
000000_0hive (default)> ! cat /tmp/employee/000000_0;
1michaelmale
3hahafemale