A digital type
TINYINT (1-byte signed integer, from -128 to 127)
SMALLINT (2-byte signed integer, from -32,768 to 32,767)
INT/INTEGER (4-byte signed integer, from -2,147,483,648 to 2,147,483,647)
BIGINT (8-byte signed integer, from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807)
FLOAT (4-byte single precision floating point number)
DOUBLE (8-byte double precision floating point number)
Example:
create table t_test(a string ,b int,c bigint,d float,e double,f tinyint,g smallint)
Second, the date and time type
TIMESTAMP (Note: Only available starting with Hive 0.8.0)
DATE (Note: Only available starting with Hive 0.12.0)
Example, if the file has the following data:
. 1 , zhangsan, 1985 - 06 - 30 2 , Lisi, 1986 - 07 - 10 . 3 , wangwu, 1985 - 08 - 09
So, you can build a table of data to map
create table t_customer(id int,name string,birthday date)
row format delimited fields terminated by ',';
Then import data
load data local inpath '/root/customer.dat' into table t_customer;
Then, you can query correctly
Third, the string type
STRING
VARCHAR (Note: Only available starting with Hive 0.12.0)
CHAR (Note: Only available starting with Hive 0.13.0)
Fourth, the hybrid type
BOOLEAN
BINARY (Note: Only available starting with Hive 0.8.0)
Fifth, the composite type
5-1 array array type
arrays: ARRAY<data_type> (Note: negative values and non-constant expressions are allowed as of Hive 0.14.)
Example: array type of application
If the following data is needed hive demapping table:
Wolf 2, Wu Jing: Wu Gang: Dragon Mother, 2017 - 08 - 16 Sansei III miles peach, Liu Yifei: itch, 2017 - 08 - 20
Idea: If the information is starred in an array to map more convenient
Built table:
create table t_movie(moive_name string,actors array<string>,first_show date)
row format delimited fields terminated by ','
collection items terminated by ':';
Import Data:
load data local inpath '/root/movie.dat' into table t_movie;
Inquire:
select * from t_movie;
select moive_name,actors[0] from t_movie;
select moive_name,actors from t_movie where array_contains(actors,'吴刚');
select moive_name,size(actors) from t_movie;
5-2 map type
maps: MAP<primitive_type, data_type> (Note: negative values and non-constant expressions are allowed as of Hive 0.14.)
Example:
. 1 , zhangsan, Father: Xiaoming # Mother: xiaohuang # Brother: Xiaoxu, 28 2 , Lisi, Father: mayun # Mother: huangyi # Brother: Guanyu, 22 is . 3 , wangwu, Father: wangjianlin # Mother: Inner Feeling # SISTER: Jingtian, 29 4 , mayun, Father: Mother mayongzhen #: Angelababy, 26
Can be described in a family member with said data type of a map
Construction of the table statement:
create table t_person(id int,name string,family_members map<string,string>,age int)
row format delimited fields terminated by ','
collection items terminated by '#'
map keys terminated by ':';
Inquire:
select * from t_person;
## takes the value of the specified key field map
select id,name,family_members['father'] as father from t_person;
Take ## map all key fields
select id,name,map_keys(family_members) as relation from t_person;
## take all the value of a field map
select id,name,map_values(family_members) from t_person;
select id,name,map_values(family_members)[0] from t_person;
Comprehensive ##: user information query has a brother
select id,name,father from (select id,name,family_members['brother'] as father from t_person) tmp where father is not null;
5-3 struct type
structs: STRUCT<col_name : data_type, ...>
Examples
| 1, zhangsan, 18: male: beijing 2, lisi, 28: female: shanghai |
Which contain user information: Age: integer, gender: string, address: String
Envisions a field to describe the entire user information, may be employed struct
Built table:
create table t_person_struct(id int,name string,info struct<age:int,sex:string,addr:string>)
row format delimited fields terminated by ','
collection items terminated by ':';
Inquire
select * from t_person_struct;
select id,name,info.age from t_person_struct;