创建表

创建内表

create table customer(

customerId int,

firstName string,

lastName STRING,

birstDay timestamp

) row format delimited fields terminated by ','

创建外表

CREATE EXTERNAL table salaries(

gender string,

age int ,

salary DOUBLE,

zip int

)row format delimited fields terminated by ',' LOCATION '/user/train/salaries/';

载入数据

load DATA LOCAL inpath '/root/user/customer.txt' overwrite into table customer;

load DATA LOCAL inpath '/root/user/salaries.txt' overwrite into table salaries;

查看文本数据

[root@centos172 user]# cat /root/user/customer.txt

1,f,jack,,

2,f,luccy,,

[root@centos172 user]# cat /root/user/salaries.txt

male,21,10000,1

female,22,12000,2

查看数据库数据

hive> desc customer;

OK

customerid int

firstname string

lastname string

birstday timestamp

Time taken: 0.053 seconds, Fetched: 4 row(s)

hive> desc salaries;

OK

gender string

age int

salary double

zip int

Time taken: 0.041 seconds, Fetched: 4 row(s)

hive> select * from customer;

OK

1 f jack NULL

2 f luccy NULL

Time taken: 0.067 seconds, Fetched: 2 row(s)

hive> select * from salaries;

OK

male 21 10000.0 1

female 22 12000.0 2

Time taken: 0.066 seconds, Fetched: 2 row(s)

hive>

区别

因为我hive也是刚开始了解，所以只讲一部分

1.内表主要放在hdfs中默认的hive目录。外表指定了location

2.删除内表，重新创建一个一样的内表，数据不会装载

删除外表，重新创建一个一样的外表，数据会自动的装载

删除外表的操作如下

hive> drop table salaries;

OK

Time taken: 0.092 seconds

hive> select * from salaries;

FAILED: SemanticException [Error 10001]: Line 1:14 Table not found 'salaries'

hive> show tables;

OK

customer

Time taken: 0.035 seconds, Fetched: 1 row(s)

hive> CREATE EXTERNAL table salaries(

> gender string,

> age int ,

> salary DOUBLE,

> zip int

> )row format delimited fields terminated by ',' LOCATION '/user/train/salaries/';

OK

Time taken: 0.058 seconds

hive> show tables;

OK

customer

salaries

Time taken: 0.025 seconds, Fetched: 2 row(s)

hive> select * from salaries;

OK

male 21 10000.0 1

female 22 12000.0 2

Time taken: 0.058 seconds, Fetched: 2 row(s)

hive>

区别1的：

内表的默认路径

指定外表的路径如图：

hive是什么

我当前接触到就是：

1.把hdf文件具体为table

2.用来查询，类似sql语句处理