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Hive 7、Hive 的内表、外表、分区

作者:互联网

1、Hive的内表

Hive 的内表,就是正常创建的表,在 http://www.cnblogs.com/raphael5200/p/5208437.html 中已经提到;

2、Hive的外表

创建Hive 的外表,需要使用关键字 External:

CREATE EXTERNAL TABLE [IF NOT EXISTS] [db_name.]table_name    
  [(col_name data_type [COMMENT col_comment], ...)]
  [COMMENT table_comment]
  [PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)]
  [CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS]
  [SKEWED BY (col_name, col_name, ...)                 
     ON ((col_value, col_value, ...), (col_value, col_value, ...), ...)
     [STORED AS DIRECTORIES]
  [
   [ROW FORMAT row_format]

  下面看一个例子:

create External table food_ex 
(
id int,
name string,
category string,
price double 
)
 ROW FORMAT DELIMITED
 FIELDS TERMINATED BY '\t'
 lines terminated by '\n';

  

-- 加载数据
load data local inpath '/opt/food.txt' overwrite into table food_ex;

  

select * from food_ex;

  

 

 

 

 

这两个,左边是外表,右边是内表从大体上看似乎没什么区别,但是他的主要区别在于删除操作上:

  内表删除表或者分区元数据和数据都删了

  外表删除表元数据删除,数据保留

下面分别执行两条语句:

 drop table food;
 drop table food_ex;

  执行这两条语句以后,两个表都删除了,但是结果却不一样,访问NameNode的50070端口:

 

 

 

 

 

 

 

 可以看到,虽然都执行了表删除语句,内表删除后是把元数据和数据都删除了,而外表却只删除了元数据(表的信息)但真实数据却保留了下来; 

3、Hive的分区partition

必须在表定义时创建partition

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

例:

create table log_info
 (
 ip string
 )
 PARTITIONED BY(times string)
 ROW FORMAT DELIMITED
 FIELDS TERMINATED BY '\t'
 lines terminated by '\n';

  

# 下面是log_info 的表结构信息,分区已经创建
hive> desc log_info;
OK
ip                      string                                      
times                   string                                      
          
# Partition Information          
# col_name                data_type               comment             
          
times                   string                                      
Time taken: 0.077 seconds, Fetched: 7 row(s)

  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

create table log_info2
 (
 ip string
 )
 PARTITIONED BY(days string,hours string)
 ROW FORMAT DELIMITED
 FIELDS TERMINATED BY '\t'
 lines terminated by '\n';

  

# 下面是log_info2 的表结构信息,分区已经创建
hive> desc log_info2;
OK
ip                      string                                      
days                    string                                      
hours                   string                                      
          
# Partition Information          
# col_name                data_type               comment             
          
days                    string                                      
hours                   string                                      
Time taken: 0.08 seconds, Fetched: 9 row(s)

  c、Hive添加分区表语法 (表已创建,在此基础上添加分区):

ALTER TABLE table_name ADDpartition_spec
 [ LOCATION 'location1' ]
partition_spec [ LOCATION 'location2' ] ... 
ALTER TABLE day_table 
ADDPARTITION (dt='2008-08-08', hour='08')
location '/path/pv1.txt'

  d、Hive删除分区语法:

ALTER TABLE table_name DROP PARTITION partition_spec, partition_spec,...

   用户可以用 ALTER TABLE DROP PARTITION 来删除分区。分区的元数据和数据将被一并删除。

ALTER TABLE day_hour_table DROP PARTITION (dt='2008-08-08', hour='09');

  

alter table log_info drop partition (times='20160222');

  e、Hive数据加载进分区表中语法:

 LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] 

  

例:

单分区数据加载

 load data local inpath '/opt/log' overwrite into table  log_info partition(times='20160223');
 load data local inpath '/opt/log2' overwrite into table log_info partition(times='20160222');

  

hive> select * from log_info;
OK
23.45.66.77	20160222
45.66.11.8	20160222
2.3.4.5	20160223
4.56.77.31	20160223
34.55.6.77	20160223
34.66.11.6	20160223
Time taken: 0.125 seconds, Fetched: 6 row(s)

  在Hive中会根据分区的名称新建两个分区目录

 

 

双分区数据加载

load data local inpath '/opt/log3' overwrite into table log_info2 partition(days='23',hours='12');

  

hive> select * from log_info2;
OK
12.3.33.66    23    12
23.44.56.6    23    12
12.22.33.4    23    12
8.78.99.4    23    12
233.23.211.2    23    12
Time taken: 0.069 seconds, Fetched: 5 row(s)

  

 

 当数据被加载至表中时,不会对数据进行任何转换。Load操作只是将数据复制至Hive表对应的位置。数据加载时在表下自动创建一个目录 基于分区的查询的语句:

SELECT day_table.* FROM day_table WHERE day_table.dt>= '2008-08-08';

  f、Hive查看分区语句:

hive> show partitions day_hour_table; 
OK 
dt=2008-08-08/hour=08 
dt=2008-08-08/hour=09 
dt=2008-08-09/hour=09

  

hive> show partitions log_info;
OK
times=20160222
times=20160223
Time taken: 0.06 seconds, Fetched: 2 row(s)

  

 

标签:内表,分区,Hive,name,log,table,col,string
来源: https://www.cnblogs.com/tesla-turing/p/11509297.html