hive数据类型
Hive的内置数据类型可以分为两大类：
- 基础数据类型；
- 复杂数据类型；
1、基础数据类型包括：
| 数据类型 |
所占字节 |
开始支持版本 |
| TINYINT |
1byte，-128 ~ 127 |
|
| SMALLINT |
2byte，-32,768 ~ 32,767 |
|
| INT |
4byte,-2,147,483,648 ~ 2,147,483,647 |
|
| BIGINT |
8byte,-9,223,372,036,854,775,808 ~ 9,223,372,036,854,775,807 |
|
| BOOLEAN |
|
|
| FLOAT |
4byte单精度 |
|
| DOUBLE |
8byte双精度 |
|
| STRING |
|
|
| BINARY |
|
从Hive0.8.0开始支持 |
| TIMESTAMP |
|
从Hive0.8.0开始支持 |
| DECIMAL |
|
从Hive0.11.0开始支持 |
| CHAR |
|
从Hive0.13.0开始支持 |
| VARCHAR |
|
从Hive0.12.0开始支持 |
| DATE |
|
从Hive0.12.0开始支持 |
2、复杂数据类型：
- ARRAY：ARRAY类型是由一系列相同数据类型的元素组成，这些元素可以通过下标来访问。比如有一个ARRAY类型的变量fruits，它是由['apple','orange','mango']组成，那么我们可以通过fruits[1]来访问元素orange，因为ARRAY类型的下标是从0开始的；
- MAP：MAP包含key->value键值对，可以通过key来访问元素。比如”userlist”是一个map类型，其中username是key，password是value；那么我们可以通过userlist['username']来得到这个用户对应的password；
- STRUCT：STRUCT可以包含不同数据类型的元素。这些元素可以通过”点语法”的方式来得到所需要的元素，比如user是一个STRUCT类型，那么可以通过user.address得到这个用户的地址。
- UNION: UNIONTYPE，他是从Hive 0.7.0开始支持的。
3、hive array使用：
1）创建表：
hive> createtable test(name string,col1 array
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY '\t'
> COLLECTIONITEMS TERMINATED BY ','
> STORED AS TEXTFILE;
2）导入数据：
$ cat test
test 20,21
liuxiao 30,60,90
xiaoli 29,69,89
导入：
hive> load datalocal inpath '/home/qytt/test' overwrite into table test;
Copying data from file:/home/qytt/test
Copying file: file:/home/qytt/test
Loading data totable qytt.test
OK
Time taken: 0.305seconds
3）查询：
hive> select *from test;
OK
test ["20","21"]
liuxiao ["30","60","90"]
xiaoli ["29","69","89"]
Time taken: 0.06seconds, Fetched: 3 row(s)
hive> selectname,col1[0] from test;
Total jobs = 1
...
OK
test 20
liuxiao 30
xiaoli 29
hive> selectname,col1[2] from test;
Total jobs = 1
...
OK
test NULL
liuxiao 90
xiaoli 89
4、hive map使用：
1）创建表：
hive> createtable test(name string,col1 map
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY '\t'
> COLLECTIONITEMS TERMINATED BY ','
> MAP KEYS TERMINATED BY ':'
> STORED AS TEXTFILE;
2）导数据：
$ cat test
test age:20,sex:1,addredd:beijingshi
liuxiao age:30,job:abc
xiaoli age:28,sex:0,intrest:happy
hive> load datalocal inpath '/home/qytt/test' overwrite into table test;
Copying data from file:/home/qytt/test
Copying file: file:/home/qytt/test
Loading data totable qytt.test
OK
Time taken: 0.745seconds
3）查询：
hive> select *from test;
OK
test {"age":"20","sex":"1","addredd":"beijingshi"}
liuxiao {"age":"30","job":"abc"}
xiaoli {"age":"28","sex":"0","intrest":"happy"}
Time taken: 0.045seconds, Fetched: 3 row(s)
hive> selectname,col1['age'],col1['sex'] from test;
Total jobs = 1
...
OK
test 20 1
liuxiao 30 NULL
xiaoli 28 0
Time taken: 26.358seconds, Fetched: 3 row(s)
5、hive struct使用：
1）创建表：
hive> createtable test(name string,col1 struct
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY '\t'
> COLLECTION ITEMS TERMINATED BY ','
> STORED AS TEXTFILE;
OK
Time taken: 0.043seconds
2）导入数据：
$ cat test
test 20,1,beijingshi
liuxiao 30,0,abc
xiaoli 28,0,happy
hive> load datalocal inpath '/home/qytt/test' overwrite into table test;
Copying data from file:/home/qytt/test
Copying file: file:/home/qytt/test
Loading data totable qytt.test
OK
Time taken: 0.186seconds
3）查询：
hive> select *from test;
OK
test {"age":20,"sex":1,"address":"beijingshi"}
liuxiao {"age":30,"sex":0,"address":"abc"}
xiaoli {"age":28,"sex":0,"address":"happy"}
Time taken: 0.028seconds, Fetched: 3 row(s)
hive> selectname,col1.age,col1.address from test;
Total jobs = 1
...
OK
test 20 beijingshi
liuxiao 30 abc
xiaoli 28 happy
Time taken: 22.054seconds, Fetched: 3 row(s)
https://my.oschina.net/leejun2005/blog/120463