大数据-地域维度清洗

将地域代码和地域名称清洗到一列中

启动hadoop和hive

创建表

create table tab03(

ID int,

QA04 string,

QA05 string,

QA07 string,

QA15 int,

QA19 int,

HYWD string,

QB03 int,

QB03ONE string,

QB03TWO string,

QB03_1 int,

QB06 int,

QB16 int,

QB16V string,

GXWD string,

QB16_1 int,

QB16_1V string,

QC02 double,

QC05_0 double,

QC24 double,

QC40 double,

QD01 int,

QD28 int,

QJ09 int,

QJ20 int,

QJ55 int,

QJ74 int,

DYWD string,

SYEAR int

row format delimited fields terminated by ','

lines terminated by '\n';

导入文件

load data local inpath ‘/home/lt/file/1.csv' overwrite into table tab03;

create table tab04(

dm int,

dmms string

row format delimited fields terminated by ','

lines terminated by '\n';

load data local inpath '/home/lt/file/2.csv' overwrite into table tab04;

insert overwrite table tab05 select 

ID,

QA04,

QA05,

QA07,

QA15,

QA19,

HYWD,

QB03,

QB03ONE,

QB03TWO ,

QB03_1,

QB06,

QB16,

QB16V,

GXWD,

QB16_1,

QB16_1V,

QC02,

QC05_0,

QC24,

QC40,

QD01,

QD28,

QJ09,

QJ20,

QJ55,

QJ74,

concat(QA19,t4.dmms),

SYEAR

from tab04 t4 join tab03 t3 on (t4.dm=t3.QA19);

清洗后的数据

导入mysql