目录
  1. 1. Hive
    1. 1.1. 概念
    2. 1.2. 作用
    3. 1.3. 架构
      1. 1.3.1. 元数据
      2. 1.3.2. 数据存储
        1. 1.3.2.1. 数据库
        2. 1.3.2.2. 数据表
        3. 1.3.2.3. 分区和分桶
        4. 1.3.2.4. 表数据
    4. 1.4. 基础操作示例
Hive相关

Hive

概念

基于Hadoop的一个数据仓库工具(Data warehouse)
4个特点

  1. 面向主题的
  2. 集成的
  3. 相对稳定的
  4. 反应历史变化的
    数据集合,用于支持管理决策

HDFS 为Hive提供存储
MapReduce 为Hive提供计算引擎
YARN 为Hive提供资源调度

作用

可以将可结构化的数据映射为一张数据库表, 并提供HQL(Hive QL)查询功能,底层数据存储在HDFS中
本质上是 将Hql语句转化为mapReduce任务运行

架构

元数据

存放数据描述的数据(用于映射表数据 )
域(id)、表名和文件的对应关系(确认要查询那个数据表)、字段名和对应域值的关系(哪列数据)、分隔符(按照什么符号区分列数据)

存储介质:RDBMS (关系型数据库) 用关系型数据库存元数据信息。

数据存储

数据库

数据表

分区和分桶

表数据

库+表+分区 = HDFS上的一个目录
分区和分桶 = HDFS上的一个文件

基础操作示例

一、DDL

1、创建内部表
create table student(id int, name string, sex string, age int, department string) row format delimited fields terminated by “,”;

2、创建外部表

// 没有指定外部路径, 表的数据目录存储在默认的仓库路径中
create external table student_ext_1(id int, name string, sex string, age int, department string) row format delimited fields terminated by “,”;

// 指定一个不存在的外部路径: 创建表的时候,会自动给你创建表目录
create external table student_ext_2(id int, name string, sex string, age int, department string) row format delimited fields terminated by “,” location “/student_ext_2”;

// 指定一个已经存在的目录: 并且有数据
//在linux中执行
hadoop fs -mkdir -p /student_ext_3
hadoop fs -put /home/data/student.txt /student_ext_3
//在hive命令行中执行
create external table student_ext_3(id int, name string, sex string, age int, department string) row format delimited fields terminated by “,” location “/student_ext_3”;

3、创建分区表

// 创建只有一个分区字段的分区表:
create table student_ptn(id int, name string, sex string, age int, department string) partitioned by (city string comment “partitioned field”) row format delimited fields terminated by “,”;

load data local inpath “/home/data/student.txt” into table student_ptn; XXXXXXX

// 把数据导入到一个不存在的分区,它会自动创建该分区
load data local inpath “/home/data/student.txt” into table student_ptn partition(city=”beijing”); √√√√

// 把数据导入到一个已经存在的分区
alter table student_ptn add partition (city=”chongqing”);
load data local inpath “/home/data/student.tx” into table student_ptn partition(city=”chongqing”);

// 创建有多个分区字段的分区表:
create table student_ptn_date(id int, name string, sex string, age int, department string) partitioned by (city string comment “partitioned field”, dt string) row format delimited fields terminated by “,”;

// 往分区中导入数据:
load data local inpath “/home/data/student.txt” into table student_ptn_date partition(city=”beijing”); //报错

load data local inpath “/home/data/student.txt” into table student_ptn_date partition(city=”beijing”, dt=’2012-12-12’); //正确

// 不能在导入数据的时候指定多个分区定义
load data local inpath “/home/data/student.txt” into table student_ptn_date partition(city=”beijing”, dt=’2012-12-14’) partition (city=”beijing” , dt=’2012-12-13’); XXXXXX

// 添加分区
alter table student_ptn_date add partition(city=”beijing”, dt=’2012-12-14’) partition (city=”beijing” , dt=’2012-12-13’); √√√√√√√√
alter table student_ptn_date add partition(city=”chongqing”, dt=’2012-12-14’) partition (city=”chongqing” , dt=’2012-12-13’);

// 查询一个分区表有那些分区
show partitions student_ptn;
show partitions student_ptn_date;
show partitions student;

4、创建分桶表

// 创建一个分桶表
create table student_bucket (id int, name string, sex string, age int, department string) clustered by (department) sorted by (age desc, id asc) into 3 buckets row format delimited fields terminated by “,”;

5、从查询语句的结果创建新表
通过下面的命令:
create table … as select ….
查询例子:
select department, count() as total from student group by department;
完整的CTAS语句:
create table dpt_count as select department, count(
) as total from student group by department;

6、通过like复制已有表的结构创建新表
create table student_like like student;

删除表

drop table student;
drop table if exists student;

修改表

1、修改表名

alter table student rename to studentss;

2、修改字段

    添加字段: 
    alter table student add columns (city string, dt string);
    删除字段: 
    alter table student drop columns (city);   XXXXXXXX
    替换字段:
    alter table student replace columns (id int, name string, sex string, age int);
    改变列的定义:
    alter table student change id newid string comment "new id";
    改变列的顺序:
    alter table student change sex sex string first;
    alter table student change name name string after sex;

3、修改分区

    添加分区:
    alter table student_ptn add partition(city='tiajin') partition(city='shanghai');

    删除分区:
    alter table student_ptn drop partition(city='tiajin');  
    alter table student_ptn drop partition(city='tiajin'),partition(city='shanghai'); 

    修改分区的数据目录:
    alter table student_ptn partition(city="beijing") set location "/stu_beijing";   XXXX
    alter table student_ptn partition(city="beijing") set location "hdfs://hadoop02:9000/stu_beijing";  √√√√√√√

清空表:

truncate table student;
等价于下面:
hadoop fs -rm -r /user/hive/warehouse/myhive.db/student/*
前面的load和hadoop fs -put命令也是等价的。

显示创建表的详细信息

show create table student;

// 准备student表:以及数据:  
create database if not exists myhive;
use myhive;
create table student(id int, name string, sex string, age int, department string) row format delimited fields terminated by ",";
load data local inpath "/home/data/student.txt" into table student;
select * from student;

修改表

1、修改表名
alter table student rename to studentss;

2、修改字段

    添加字段: 
    alter table student add columns (city string, dt string);
    删除字段: 
    alter table student drop columns (city);   //报错XXXXXXXX
    替换字段:
    alter table student replace columns (id int, name string, sex string, age int);
    改变列的定义:
    alter table student change id newid string comment "new id";
    改变列的顺序:
    alter table student change sex sex string first;
    alter table student change name name string after sex;

3、修改分区

    添加分区:
    alter table student_ptn add partition(city='tiajin') partition(city='shanghai');

    删除分区:
    alter table student_ptn drop partition(city='tiajin');  
    alter table student_ptn drop partition(city='tiajin'),partition(city='shanghai'); 

    修改分区的数据目录:
    alter table student_ptn partition(city="beijing") set location "/stu_beijing";   XXXX
    alter table student_ptn partition(city="beijing") set location "hdfs://hadoop0:8020/stu_beijing";  √√√√√√√

二、DML

1、导入数据

load
load data local inpath “/home/data/student.txt” into table student;

insert
insert into table student (id, name, sex, age, department) values (101,”huangbo”,”M”,222,”IT”);

创建分区表:

create table student_ptn (id int, name string, sex string, age int) partitioned by (department string) row format delimited fields terminated by “,”;

单重插入:
insert into table student_ptn partition (department = ‘IS’) select id,sex,name,age from student where department = ‘IS’;
insert into table student_ptn partition (department = ‘CS’) select id,sex,name,age from student where department = ‘CS’;
insert into table student_ptn partition (department = ‘MA’) select id,sex,name,age from student where department = ‘MA’;

多重插入:
from student
insert into table student_ptn partition (department = ‘IS’) select id,sex,name,age where department = ‘IS’
insert into table student_ptn partition (department = ‘CS’) select id,sex,name,age where department = ‘CS’
insert into table student_ptn partition (department = ‘MA’) select id,sex,name,age where department = ‘MA’

2、导出数据

insert overwrite local directory "/home/data/cs_student" select * from student where department = 'CS';

insert overwrite directory "/home/data/cs_student" select * from student where department = 'CS';

3、查询

select ... from ...  join   ... on... where  group by  having  limit 
文章作者: sovwcwsfm
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