标签：des style blog color 使用 os io strong
本案例使用的数据均来源于Oracle自带的emp和dept表
创建表
语法：
CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name [(col_name data_type [COMMENT col_comment], ...)] [COMMENT table_comment] [PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)] [CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS] [SKEWED BY (col_name, col_name, ...) ON ([(col_value, col_value, ...), ...|col_value, col_value, ...]) [STORED AS DIRECTORIES] (Note: Only available starting with Hive 0.10.0)] [ [ROW FORMAT row_format] [STORED AS file_format] | STORED BY ‘storage.handler.class.name‘ [WITH SERDEPROPERTIES (...)] (Note: Only available starting with Hive 0.6.0) ] [LOCATION hdfs_path] [TBLPROPERTIES (property_name=property_value, ...)] (Note: Only available starting with Hive 0.6.0) [AS select_statement] (Note: Only available starting with Hive 0.5.0, and not supported when creating external tables.)
create table emp( empno int, ename string, job string, mgr int, hiredate string, sal double, comm double, deptno int ) row format delimited fields terminated by ‘\t‘ lines terminated by ‘\n‘ stored as textfile;
create table dept( deptno int, dname string, loc string ) row format delimited fields terminated by ‘\t‘ lines terminated by ‘\n‘ stored as textfile;
注：创建表时默认列分割符是\001，行分隔符是\n
加载数据到hive表
Hive操作的数据源：文件、其他表、其他数据库
1）load：加载本地/HDFS文件到hive表
LOAD DATA [LOCAL] INPATH ‘filepath‘ [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]
默认表数据存储在HDFS上的/user/hive/warehouse目录下，该目录可以在hive-site.xml中配置。
load data inpath 加载hdfs文件到hive表中；
load data local inpath 加载本地文件到hive表中；
overwrite 是否会覆盖表里已有的数据
load data local inpath ‘/home/spark/software/data/emp.txt‘ overwrite into table emp; load data local inpath ‘/home/spark/software/data/dept.txt‘ overwrite into table dept;
2）insert：导入数据到表里/从表里导出到HDFS或者本地目录
Standard syntax: INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1 FROM from_statement; INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1 FROM from_statement; Hive extension (multiple inserts): FROM from_statement INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1 [INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2] [INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2] ...; FROM from_statement INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1 [INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2] [INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2] ...; Standard syntax: INSERT OVERWRITE [LOCAL] DIRECTORY directory1 [ROW FORMAT row_format] [STORED AS file_format] (Note: Only available starting with Hive 0.11.0) SELECT ... FROM ... Hive extension (multiple inserts): FROM from_statement INSERT OVERWRITE [LOCAL] DIRECTORY directory1 select_statement1 [INSERT OVERWRITE [LOCAL] DIRECTORY directory2 select_statement2] ...
3）sqoop: 关系型数据库和HDFS文件导入/导出操作
详见sqoop章节介绍。
select操作
select * from emp; 7369 SMITH CLERK 7902 1980-12-17 800.0 NULL 20 7499 ALLEN SALESMAN 7698 1981-2-20 1600.0 300.0 30 7521 WARD SALESMAN 7698 1981-2-22 1250.0 500.0 30 7566 JONES MANAGER 7839 1981-4-2 2975.0 NULL 20 7654 MARTIN SALESMAN 7698 1981-9-28 1250.0 1400.0 30 7698 BLAKE MANAGER 7839 1981-5-1 2850.0 NULL 30 7782 CLARK MANAGER 7839 1981-6-9 2450.0 NULL 10 7788 SCOTT ANALYST 7566 1987-4-19 3000.0 NULL 20 7839 KING PRESIDENT NULL 1981-11-17 5000.0 NULL 10 7844 TURNER SALESMAN 7698 1981-9-8 1500.0 0.0 30 7876 ADAMS CLERK 7788 1987-5-23 1100.0 NULL 20 7900 JAMES CLERK 7698 1981-12-3 950.0 NULL 30 7902 FORD ANALYST 7566 1981-12-3 3000.0 NULL 20 7934 MILLER CLERK 7782 1982-1-23 1300.0 NULL 10
select * from dept; 10 ACCOUNTING NEW YORK 20 RESEARCH DALLAS 30 SALES CHICAGO 40 OPERATIONS BOSTON
where使用
select * from emp where deptno =10; 7782 CLARK MANAGER 7839 1981-6-9 2450.0 NULL 10 7839 KING PRESIDENT NULL 1981-11-17 5000.0 NULL 10 7934 MILLER CLERK 7782 1982-1-23 1300.0 NULL 10 select * from emp where deptno <>10; 7369 SMITH CLERK 7902 1980-12-17 800.0 NULL 20 7499 ALLEN SALESMAN 7698 1981-2-20 1600.0 300.0 30 7521 WARD SALESMAN 7698 1981-2-22 1250.0 500.0 30 7566 JONES MANAGER 7839 1981-4-2 2975.0 NULL 20 7654 MARTIN SALESMAN 7698 1981-9-28 1250.0 1400.0 30 7698 BLAKE MANAGER 7839 1981-5-1 2850.0 NULL 30 7788 SCOTT ANALYST 7566 1987-4-19 3000.0 NULL 20 7844 TURNER SALESMAN 7698 1981-9-8 1500.0 0.0 30 7876 ADAMS CLERK 7788 1987-5-23 1100.0 NULL 20 7900 JAMES CLERK 7698 1981-12-3 950.0 NULL 30 7902 FORD ANALYST 7566 1981-12-3 3000.0 NULL 20 select * from emp where ename =‘SCOTT‘; 7788 SCOTT ANALYST 7566 1987-4-19 3000.0 NULL 20 select ename,sal from emp where sal between 800 and 1500; SMITH 800.0 WARD 1250.0 MARTIN 1250.0 TURNER 1500.0 ADAMS 1100.0 JAMES 950.0 MILLER 1300.0
limit使用
select * from emp limit 4; 7369 SMITH CLERK 7902 1980-12-17 800.0 NULL 20 7499 ALLEN SALESMAN 7698 1981-2-20 1600.0 300.0 30 7521 WARD SALESMAN 7698 1981-2-22 1250.0 500.0 30 7566 JONES MANAGER 7839 1981-4-2 2975.0 NULL 20
(not) in使用
select ename,sal,comm from emp where ename in (‘SMITH‘,‘KING‘); SMITH 800.0 NULL KING 5000.0 NULL select ename,sal,comm from emp where ename not in (‘SMITH‘,‘KING‘); ALLEN 1600.0 300.0 WARD 1250.0 500.0 JONES 2975.0 NULL MARTIN 1250.0 1400.0 BLAKE 2850.0 NULL CLARK 2450.0 NULL SCOTT 3000.0 NULL TURNER 1500.0 0.0 ADAMS 1100.0 NULL JAMES 950.0 NULL FORD 3000.0 NULL MILLER 1300.0 NULL
is (not) null使用
select ename,sal,comm from emp where comm is null; SMITH 800.0 NULL JONES 2975.0 NULL BLAKE 2850.0 NULL CLARK 2450.0 NULL SCOTT 3000.0 NULL KING 5000.0 NULL ADAMS 1100.0 NULL JAMES 950.0 NULL FORD 3000.0 NULL MILLER 1300.0 NULL select ename,sal,comm from emp where comm is not null; ALLEN 1600.0 300.0 WARD 1250.0 500.0 MARTIN 1250.0 1400.0 TURNER 1500.0 0.0
order by的使用
与关系型数据库的order by功能一致，按照某个字段或某几个字段排序输出；
与关系型数据库区别在于：当hive.mapred.mode=strict模式下，必须指定limit否则执行报错；
hive.mapred.mode默认值为nonstrict；
select * from dept; 10 ACCOUNTING NEW YORK 20 RESEARCH DALLAS 30 SALES CHICAGO 40 OPERATIONS BOSTON select * from dept order by deptno desc; 40 OPERATIONS BOSTON 30 SALES CHICAGO 20 RESEARCH DALLAS 10 ACCOUNTING NEW YORK select ename,sal,deptno from emp order by deptno asc,ename desc; MILLER 1300.0 10 KING 5000.0 10 CLARK 2450.0 10 SMITH 800.0 20 SCOTT 3000.0 20 JONES 2975.0 20 FORD 3000.0 20 ADAMS 1100.0 20 WARD 1250.0 30 TURNER 1500.0 30 MARTIN 1250.0 30 JAMES 950.0 30 BLAKE 2850.0 30 ALLEN 1600.0 30
set hive.mapred.mode=strict; select * from emp order by empno desc;
报错：FAILED: SemanticException 1:27 In strict mode, if ORDER BY is specified, LIMIT must also be specified. Error encountered near token ‘empno‘
正确写法：
select * from emp order by empno desc limit 4; 7934 MILLER CLERK 7782 1982-1-23 1300.0 NULL 10 7902 FORD ANALYST 7566 1981-12-3 3000.0 NULL 20 7900 JAMES CLERK 7698 1981-12-3 950.0 NULL 30 7876 ADAMS CLERK 7788 1987-5-23 1100.0 NULL 20
为什么会报错呢？
在order by状态下所有数据会分发到一个节点上进行reduce操作也就只有一个reduce作业，如果在数据量大的情况下会出现无法输出结果的情况，如果进行limit n，那就只有n*map数个记录而已，只有一个reduce也可以处理的过来。
select嵌套查询、别名
from(select ename, sal from emp) e select e.ename, e.sal where e.sal>1000;
等价于
select ename, sal from emp where sal>1000;
ALLEN 1600.0 WARD 1250.0 JONES 2975.0 MARTIN 1250.0 BLAKE 2850.0 CLARK 2450.0 SCOTT 3000.0 KING 5000.0 TURNER 1500.0 ADAMS 1100.0 FORD 3000.0 MILLER 1300.0
组函数：max(), min(), avg(), sum(), count()等
select count(*) from emp where deptno=10; 3 select count(ename) from emp where deptno=10; #count某个字段,如果这个字段不为空就算一个. 3 select count(distinct deptno) from emp; 3 select sum(sal) from emp; 29025.0
group by的使用
出现在select中的字段,如果没出现在组函数中,必须出现在Group by语句中
求每个部门的平均薪水：
select deptno, avg(sal) from emp group by deptno; 10 2916.6666666666665 20 2175.0 30 1566.6666666666667
求每个部门中每个工作最高的薪水：
select deptno,job,max(sal) from emp group by deptno,job; 10 CLERK 1300.0 10 MANAGER 2450.0 10 PRESIDENT 5000.0 20 ANALYST 3000.0 20 CLERK 1100.0 20 MANAGER 2975.0 30 CLERK 950.0 30 MANAGER 2850.0 30 SALESMAN 1600.0
having的使用
对分组结果筛选，后跟聚合函数，hive0.11版本之后才支持；where是对单条纪录进行筛选,Having是对分组结果进行筛选。
求每个部门的平均薪水大于2000的部门：
select avg(sal),deptno from emp group by deptno having avg(sal)>2000; 2916.6666666666665 10 2175.0 20
having是hive0.11后才支持的，如果不使用having而想达到having一样的功能，语句如何写？
select deptno, e.avg_sal from (select deptno, avg(sal) as avg_sal from emp group by deptno) e where e.avg_sal > 2000;
CASE...WHEN..THEN使用
select ename, sal, case when sal > 1 and sal <=1000 then ‘LOWER‘ when sal >1000 and sal <=2000 then ‘MIDDLE‘ when sal >2000 and sal <=4000 then ‘HIGH‘ ELSE ‘HIGHEST‘ end from emp; SMITH 800.0 LOWER ALLEN 1600.0 MIDDLE WARD 1250.0 MIDDLE JONES 2975.0 HIGH MARTIN 1250.0 MIDDLE BLAKE 2850.0 HIGH CLARK 2450.0 HIGH SCOTT 3000.0 HIGH KING 5000.0 HIGHEST TURNER 1500.0 MIDDLE ADAMS 1100.0 MIDDLE JAMES 950.0 LOWER FORD 3000.0 HIGH MILLER 1300.0 MIDDLE
Hive基础之Hive表常用操作,布布扣,bubuko.com
标签：des style blog color 使用 os io strong
原文地址：http://www.cnblogs.com/luogankun/p/3910442.html
