hive表操做(转)

转载于:http://blog.csdn.net/lovelovelovelovelo/article/details/52234971mysql

数据类型 
基本数据类型 
集合类型,array、map、struct 
文件格式,textfile、sequencefile、rcfilesql

建立表(内部表)数据库

create table employee(
    name string comment 'name',
    salary float,
    subordinates array<string>,
    deductions map<string,float>,
    address struct<street:string,city:string,state:string,zip:int>
)
row format delimited fields termited by '\t' lines terminated by '\n' stored as textfile;

 

从文件加载数据,覆盖源表markdown

load data local infile 'path' overwrite into table 'table'

 

 

建立外部表oop

create external table employee(
    name string comment 'name',
    salary float,
    subordinates array<string>,
    deductions map<string,float>,
    address struct<street:string,city:string,state:string,zip:int>
)
row format delimited fields terminated by '\t' 
collection items terminated by ','
map keys terminated by ':'
lines terminated by '\n'
stored as textfile
location '/data/';

 

表中数据post

lucy 11000 tom,jack,dave,kate  tom:1200,jack:1560 beijing,changanjie,xichengqu,10000
lily 13000 dave,kate  dave:1300,kate:1260 beijing,changanjie,xichengqu,10000

 

 

和咱们熟悉的关系型数据库不同,Hive如今还不支持在insert语句里面直接给出一组记录的文字形式,也就是说,hive并不支持INSERT INTO …. VALUES形式的语句。spa

新建employee.txt,将数据存入文件中,注意字段间用tab,行间换行enter 
经过hive命令加载数据.net

hive> load data local inpath '/root/employee.txt' into table employee;
hive> select * from employee;                                         
OK
lucy    11000.0 ["tom","jack","dave","kate"]    {"tom":1200.0,"jack":1560.0}    {"street":"beijing","city":"changanjie","state":"xichengqu","zip":10000}
lily    13000.0 ["dave","kate"] {"dave":1300.0,"kate":1260.0}   {"street":"beijing","city":"changanjie","state":"xichengqu","zip":10000}
Time taken: 0.054 seconds, Fetched: 2 row(s)

select * from table不走mapreduce 

 


由一个表建立另外一个表code

create table table2 like table1;

 

从其余表查询建立表orm

create table table2 as select name,age,add from table1;

 

 

hive不一样文件读取

stored as textfile:
    hadoop fs -text
stored as sequencefile:
    hadoop fs -text
stored as rcfile:
    hive -service rcfilecat path
stored as input format 'class':
    outformat 'class'

 

分区表操做

alter table employee add if not exists partition(country='')
alter table employee drop if exists partition(country='')

 

 

hive分桶

create table bucket_table(
    id int,
    name string
)
clustered by(id) sorted by(name) into 4 buckets
row format  delimited fields terminated by '\t' stored as textfile;
set hive.enforce.bucketing=true;

 

 

建立分区表

create table partitionTable(
    name string,
    age int
)
partitioned by(dt string)
row format delimited fields terminated by '\t' 
lines terminated by '\n'
stored as textfile;
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