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18-Hive DML&分区表&内部函数

18-Hive DML&分区表&内部函数

作者: CrUelAnGElPG | 来源:发表于2018-06-08 23:16 被阅读0次

    select

    聚合函数

    max/min/count/sum/avg  多进一出

    分组函数  group by

    求每个部门的平均工资

    select deptno, avg(salary) from ruozedata_emp group by deptno;

    Expression not in GROUP BY key 'ename'

    select中出现的字段,如果没有出现在组函数/聚合函数中,必须出现在group by里面

    求每个部门(deptno)、工作岗位(job)的最高工资(salary)

    求每个部门的平均工资大于2000的部门

    select deptno, avg(salary)  from ruozedata_emp group by deptno where avg(salary)>2000;

    where是需要写在group by之前

    where和having的执行之在什么位置?

    case when then

    select ename,salary,

    case

    when salary>1 and salary<=1000 then 'lower'

    when salary>1000 and salary<=2000 then 'middle'

    when salary>2000 and salary<=4000 then 'high'

    else 'highest'

    end

    from ruozedata_emp;

    join

    1      ruoze

    2      j

    3      k

    1      30

    2      29

    4      21

    create table a(

    id int, name string

    ) row format delimited fields terminated by '\t';

    create table b(

    id int, age int

    ) row format delimited fields terminated by '\t';

    load data local inpath '/home/hadoop/data/join_a.txt' overwrite into table a;

    inner join = join

    1      ruoze  30

    2      j      29

    outer join : left right full

    1      ruoze  30

    2      j      29

    3      k      NULL

    分区表  partition

    who when what

    click_log

    click_log_yyyyMMdd

    hive hdfs + partition <== where partition

    ==> reduce io

    分区表存在的意义

    静态分区

    create table order_partition(

    ordernumber string,

    eventtime string

    )

    partitioned by (event_month string)

    row format delimited fields terminated by '\t';

    LOAD DATA LOCAL INPATH '/home/hadoop/data/order.txt'

    OVERWRITE INTO TABLE order_partition

    PARTITION(event_month='2014-05');

    alter table PARTITIONS convert to character set latin1;

    alter table PARTITION_KEYS convert to character set latin1;

    ALTER TABLE order_partition ADD IF NOT EXISTS

    PARTITION (event_month='2014-07') ;

    create table order_4_partition(

    ordernumber string,

    eventtime string

    )

    row format delimited fields terminated by '\t';

    load data local inpath '/home/hadoop/data/order.txt' overwrite into table order_4_partition;

    insert overwrite table order_partition

    partition(event_month='2014-08')

    select * from order_4_partition;

    以上讲解的是静态分区中的单级分区

    多级分区

    create table order_mulit_partition(

    ordernumber string,

    eventtime string

    )

    partitioned by (event_month string,event_day string)

    row format delimited fields terminated by '\t';

    LOAD DATA LOCAL INPATH '/home/hadoop/data/order.txt'

    OVERWRITE INTO TABLE order_mulit_partition

    PARTITION(event_month='2014-05', event_day='01');

    动态分区

    create table ruozedata_static_emp

    (empno int, ename string, job string, mgr int, hiredate string, salary double, comm double)

    PARTITIONED by(deptno string)

    ROW FORMAT DELIMITED

    FIELDS TERMINATED BY '\t' ;

    create table ruozedata_dynamic_emp

    (empno int, ename string, job string, mgr int, hiredate string, salary double, comm double)

    PARTITIONED by(deptno string)

    ROW FORMAT DELIMITED

    FIELDS TERMINATED BY '\t' ;

    动态分区明确要求:分区字段写在select的最后面

    insert into table ruozedata_dynamic_emp partition(deptno)

    select empno,ename,job,mgr,hiredate,salary,comm,deptno from ruozedata_emp ;

    set hive.exec.dynamic.partition.mode=nonstrict;

    这是hive中常用的设置key=value的方式

    语法格式:

    set key=value; 设置

    set key;      取值

    function

    build-in

    show functions

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