实验步骤
注意:由于数据库对大小写不敏感,因此大写和小写都可以使用。
1. HiveQL:数据操作
(1)进入HiveQL,命令如下:
hive
(2)Hive创建数据库:创建一个名为userdb的数据库
命令:
create database userdb;
随时可以通过show命令来查看Hive中所包含的数据库:
命令:
show databases;
Hive会为每个数据库创建一个目录。数据库中的表将会以这个数据库目录的子目录形式存储。
(3)Hive创建表
首先需要使用use命令使用数据库userdb:
use userdb;
再根据相应要求在userdb数据库中创建表(仅仅是创建表结构,表中并没有内容):
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create table if not exists employee ( id int, name String, salary String, designation String)
comment 'employee1 details'
row format delimited
fields terminated BY '\t'
lines terminated BY '\n'
stored as textfile;
</pre>
(4)Hive加载数据:向建的表employee中加载数据
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load data local inpath '/opt/sample.txt'
overwrite into table employee;
</pre>
(5)查看数据是否加载成功
select * from employee;
(5)Hive修改表
①. 重命名表,将表名由employee修改为emp
alter table employee rename to emp;
查看名称是否正确修改:
show tables;
②. 删除表emp
drop table emp;
查看是否删除成功:
show tables;
(6)删除数据库
①. 若删除的数据库不为空则会报错。如下图所示:
drop database if exists userdb1;
②. 若删除的数据库为空则可以成功删除,如下图所示:
drop database if exists userdb;
此时,再查看数据库则会看到userdb1没有被删除,而userdb已被删除。
show databases;
(7)使用数据库userdb1,接下来所有操作均在此数据库中执行。
use userdb1;
(8)Hive分区
我们已经有一张分区表,名为employee1,下面为这张表添加分区。
①. 添加分区
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alter table employee1
add partition (year='2012') location '/opt/empdata/2012/part2012.txt'
partition (year='2013') location '/opt/empdata/2013/part2013.txt';
</pre>
②. 查看分区:
show partitions employee1;
③. 写入数据:
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load data local inpath '/opt/empdata/2013/file3'
into table employee1 partition(year='2013');
load data local inpath '/opt/empdata/2012/file2'
into table employee1 partition(year='2012');
</pre>
(9)导出数据
①. 将表employee1中的数据导出到HDFS
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insert overwrite directory '/home/Test/hdfs'
row format delimited
fields terminated by '\t'
select * from employee1;
</pre>
查看(注意:在集群中查看,需要先退出hiveQL,输入quit;命令来退出数据库到root用户下执行查询命令)
hadoop fs -cat /home/Test/hdfs/000000_0
②. 将表employee1中的数据导出到本地文件系统(注意:在HiveQL中操作,需要先进入hiveQL,输入命令hive。每次重新进入hiveQL都要使用“use userdb1;”命令来指定需要操作的数据库。)
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insert overwrite local directory '/home/Test/sample'
row format delimited
fields terminated by '\t'
select * from employee1;
</pre>
查看(注意:在集群中查看,需要先退出hiveQL,输入quit;命令来退出数据库到root用户下执行查询命令)
cat /home/Test/sample/000000_0
③. 将表employee1中的数据导出到已经存在的表employee2(注意:在HiveQL中操作,需要先进入hiveQL,输入命令hive。每次重新进入hiveQL都要使用“use userdb1;”命令来指定需要操作的数据库。)
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insert into table employee2
select * from employee1;
</pre>
查看数据是否导入到表employee2中:
select * from employee2;
④. 给分区重命名,并且查看重命名是否成功:
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alter table employee1 partition (year='2013')
rename to partition (year='2014');
</pre>
show partitions employee1;
⑤. 删除分区,并且查看分区是否删除成功:
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alter table employee1 drop
partition (year='2014');
</pre>
show partitions employee1;
[图片上传中...(image-78082e-1509677357636-21)]
(10)外部表的基本操作
①. 创建外部表,表名为exter_emp:
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create external table exter_emp( id int, name String, age int, tel String)
row format delimited
fields terminated by '\t'
lines terminated by '\n'
stored as textfile
location '/home/Test/External';
</pre>
[图片上传中...(image-c08f8d-1509677357636-20)]
②. 向外部表中加载数据:
load data local inpath '/opt/empdata/file4' into table exter_emp;
③. 查看表中是否成功导入数据:
select * from exter_emp;
④. 删除外部表exter_emp:
drop table exter_emp;
⑤. 查看文件本体依然存在:删除外部表的时候,Hive仅仅删除外部表的元数据,数据是不会删除的。
dfs -ls /home/Test/External;
2. HiveQL查询操作
(1)创建外部表employees
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create external table employees(eid int,name String,salary float,age int,birthday date,
subordinates array<String>,
deductions map<String,float>,
address struct<street:String,city:String,state:String>)
row format delimited
fields terminated by '\t'
collection items terminated by ','
map keys terminated by ':'
location '/home/Test/external-1';
</pre>
向外部表employees中加载数据:
load data local inpath '/opt/empdata/file5' into table employees;
(2)SELECT...FROM语句的使用
①. 查看employees表中的薪水数据
select name,salary from employees;
②. 查看employees表中的下属数据信息
select name,subordinates from employees;
③. 查看employees表中的扣除税数据
select name,deductions from employees;
④. 引用复合字段查看下级数据
select name,subordinates[0] from employees;
⑤. 选择一个deductions元素进行查询
select name,deductions["FedTax"] from employees;
(3)使用列值计算
①. 把查询得到的员工姓名转换为大写并计算员工的税后薪资
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select upper(name),salary,deductions["FedTax"],
round(salary*(1-deductions["FedTax"])) from employees;
</pre>
②. 内置函数查询表employees中有多少员工,以及计算员工平均薪水
select count(*),avg(salary) from employees;
③. 将employees表中每行记录中的subordinates字段内容转换成0个或者多个新的记录行。如果某行员工记录subordinates字段内容为空的话,就不会产生记录;如果不为空,那么这个数组的每个元素都将产生一行新记录:
select explode(subordinates) as sub from employees;
(4)SELECT...WHERE语句的使用
查看薪资超过30000的员工
select * from employees2 where salary > 30000;
(5)GROUP BY 语句的使用
查询获取每个部门的员工人数的查询语句如下:
select dept,count(*) from employees2 group by dept;
(6)ORDER BY语句的使用
获取员工的详细信息,并把结果按照部门名称排序:
select id,name, dept from employees2 order by dept;
(7)JOIN语句的使用
①. 下面的查询对customers和orders进行连接,找出每个客户下的订单信息。连接的条件是customers表中的id必须与orders表中的customer_id相同。这个JOIN操作实际上就是获取每个下了订单的客户的订单情况。如果某个客户没有下过任何订单,那么该客户的信息将不会返回。
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select c.id, c.name, c.age, o.amount
from customers c join orders o
on (c.id = o.customer_id);
②. HiveQL LEFT OUTER JOIN(左外连接)返回所有行左表,即使是在右边的表中没有匹配。这意味着,如果ON子句匹配的右表0(零)记录,JOIN还是返回结果行,但在右表中的每一列的值为NULL。这个LEFT OUTER JOIN操作实际上就是获取每个客户的订单情况,不管客户是不是下过订单,该客户的信息都将会返回。通过这个操作,用户可以了解到整个客户的情况,包括下过订单的客户和没有下过订单的客户。
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select c.id, c.name, o.amount, o.time
from customers c
left outer join orders o
on (c.id = o.customer_id);
③. HiveQL RIGHT OUTER JOIN(右外连接)返回右边表的所有行,即使在左表中没有匹配。如果ON子句的左表匹配0(零)的记录,JOIN结果返回一行,但在左表中的每一列为NULL。这个RIGHT OUTER JOIN操作实际上就是获取所有订单的订单和下单客户的情况,即使某个订单没有下单客户ID,也会返回该订单的情况,有关客户信息项将为NULL.
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select c.id, c.name, o.amount, o.time
from customers c
right outer join orders o
on (c.id = o.customer_id);
④. HiveQL FULL OUTER JOIN(完全外连接)将会返回两个表的所有记录。如果任一表的指定字段没有符合条件的值的话,那么就使用NULL值替代。这个FULL OUTER JOIN操作实际上就是首先进行LEFT OUTER JOIN,再进行RIGHT OUTER JOIN。也就是说,首先获取所有客户的订单信息,如果没有订单,相应的订单信息项就返回NULL;然后再获取所有订单的客户信息,如果没有客户,那么有关客户信息项将为NULL。
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select c.id, c.name, o.amount, o.time
from customers c
full outer join orders o
on (c.id = o.customer_id);
</pre>