1.Hive 分区partition

必须在表定义时指定对应的partition字段
a、单分区建表语句:
create table day_table (id int, content string) partitioned by (dt string);
单分区表,按天分区,在表结构中存在id,content,dt三列。
以dt为文件夹区分
b、 双分区建表语句:
create table day_hour_table (id int, content string) partitioned by (dt string, hour string);
双分区表,按天和小时分区,在表结构中新增加了dt和hour两列。
先以dt为文件夹,再以hour子文件夹区分
 

2.创建2个表psn2 psn3

create table psn2 (
id int,
name string,
hobby array<string>,
address map<string,string>
)
partitioned by (age int)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
COLLECTION ITEMS TERMINATED BY '-'
MAP KEYS TERMINATED BY ':'
LINES TERMINATED BY '\n';

3.插入数据

load data local inpath '/root/data' into table psn2 partition (age=10);

4.查询psn2

hive> select * from psn2;
OK
1 小明1 ["lol","book","movie"] {"beijing":"changping","shanghai":"pudong"} 10
2 小明2 ["lol","book","movie"] {"beijing":"changping","shanghai":"pudong"} 10
3 小明3 ["lol","book","movie"] {"beijing":"changping","shanghai":"pudong"} 10
4 小明4 ["lol","book","movie"] {"beijing":"changping","shanghai":"pudong"} 10
5 小明5 ["lol","movie"] {"beijing":"changping","shanghai":"pudong"} 10
6 小明6 ["lol","book","movie"] {"beijing":"changping","shanghai":"pudong"} 10
7 小明7 ["lol","book"] {"beijing":"changping","shanghai":"pudong"} 10
8 小明8 ["lol","book"] {"beijing":"changping","shanghai":"pudong"} 10
9 小明9 ["lol","book","movie"] {"beijing":"changping","shanghai":"pudong"} 10
Time taken: 7.93 seconds, Fetched: 9 row(s)
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alt="" />
理论上分区可以无限分,但是实际需要根据需求来分区。
如:历史数据按天分区
 

5.错误实例psn3

create table psn3 (
id int,
name string,
age int,
hobby array<string>,
address map<string,string>
)
partitioned by (age int)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
COLLECTION ITEMS TERMINATED BY '-'
MAP KEYS TERMINATED BY ':'
LINES TERMINATED BY '\n';
报错提示:FAILED: SemanticException [Error 10035]: Column repeated in partitioning columns
原因:分区字段不能再表的列中
 

6.同时创建两个分区

create table psn3 (
id int,
name string,
hobby array<string>,
address map<string,string>
)
partitioned by (age int,sex string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
COLLECTION ITEMS TERMINATED BY '-'
MAP KEYS TERMINATED BY ':'
LINES TERMINATED BY '\n';
 
注意:添加两个字段相应的插入数据时要指定两个字段,一个字段会报错。
hive> create table psn3 (
> id int,
> name string,
> hobby array<string>,
> address map<string,string>
> )
> partitioned by (age int,sex string)
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY ','
> COLLECTION ITEMS TERMINATED BY '-'
> MAP KEYS TERMINATED BY ':'
> LINES TERMINATED BY '\n';
OK
Time taken: 1.167 seconds

7.向双分区加载数据

hive> load data local inpath '/root/data' into table psn3 partition (age=10);
FAILED: SemanticException [Error 10006]: Line 1:63 Partition not found ''
hive> load data local inpath '/root/data' into table psn3 partition (age=10,sex='boy');
Loading data to table default.psn3 partition (age=10, sex=boy)
OK
Time taken: 3.115 seconds
hive>

8.删除分区

alter table psn2 drop partition (sex='boy');
hive> alter table psn3 drop partition (sex='boy');
Dropped the partition age=10/sex=boy
OK
Time taken: 0.195 seconds

9.结论:

添加分区的时候,必须在现有分区的基础之上
删除分区的时候,会将所有存在的分区都删除
 

10.添加分区

添加时必须指定age=10 还是 age=20的分区删除,不然会报错
hive> alter table psn3 add partition(sex='man');
FAILED: ValidationFailureSemanticException default.psn3: partition spec {sex=man} doesn't contain all (2) partition columns
hive> alter table psn3 add partition(age=10,sex='man');
OK
Time taken: 0.418 seconds
删除前age=10 和age=20下分别有boy和man两个目录
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alt="" />

11.执行删除

hive> alter table psn3 drop partition(sex='man');
Dropped the partition age=10/sex=man
OK
Time taken: 0.389 seconds
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alt="" />
load 加载数据的过程其实是在上传文件 partition 是对应hdfs的目录
 

12.通过一个表的查询结果的数据插入到另一个表中

create table psn4 (
id int,
name string,
hobby array<string>
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
COLLECTION ITEMS TERMINATED BY '-'
LINES TERMINATED BY '\n';
这种插入数据会转换成mapreduce任务
from psn3 insert overwrite table psn4 select id,name,hobby;
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" alt="" />

13.这种操作的作用:

1.复制表
2.可以作为中间表存在
 
 

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