hive 复合类型_hive复合数据类型之map
概述
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；
操作实例
1、创建表
hive> create table map_test(id string,perf map)
> row format delimited fields terminated by "\t"
> collection items terminated by ','
> map keys terminated by ':'
> ;
与struct的区别：
create table map_test(id string,perf map)
create table student_test(id int,infostruct)
------------
再建一张map_test2，测试map字段名不一致会如何
hive> create table map_test2(id string,perf map)
> row format delimited fields terminated by "\t"
> collection items terminated by ','
> map keys terminated by ':'
> ;
2、准备文件
---------字段名一致-------
[root@hello110 data]# vi map_test
1001 job:80,team:123,person:700
1002 job:90,team:234,person:800
1003 job:70,team:345,person:900
1004 job:60,team:456,person:1000
1005 job:59,team:678,person:844
1006 job:98,team:832,person:866
---------字段名不一致------
[root@hello110 data]# vi map_test2
1001 job_1:80,team:123,person:700
1002 job_2:90,team:234,person:800
1003 job:70,team:345,person:900
1004 job:60,team:456,person:1000
1005 job:59,team:678,person:844
1006 job:98,team:832,person:866
3、文件导入表
load data local inpath "/data/map_test" into table map_test;
load data local inpath "/data/map_test2" into table map_test2;
4、查看表
------map_test表-----
hive> select * from map_test;
OK
1001 {"job":80,"team":123,"person":700}
1002 {"job":90,"team":234,"person":800}
1003 {"job":70,"team":345,"person":900}
1004 {"job":60,"team":456,"person":1000}
1005 {"job":59,"team":678,"person":844}
1006 {"job":98,"team":832,"person":866}
Time taken: 2.264 seconds, Fetched: 6 row(s)
---------用[''] 的方式获取-----------
hive> select perf['job'],perf['team'],perf['person'] from map_test;
OK
80 123 700
90 234 800
70 345 900
60 456 1000
59 678 844
98 832 866
Time taken: 4.377 seconds, Fetched: 6 row(s)
hive> select perf['job'],perf['team'],perf['person123'] from map_test;
OK
80 123 NULL
90 234 NULL
70 345 NULL
60 456 NULL
59 678 NULL
98 832 NULL
Time taken: 4.212 seconds, Fetched: 6 row(s)
hive> select perf from map_test;
OK
{"job":80,"team":123,"person":700}
{"job":90,"team":234,"person":800}
{"job":70,"team":345,"person":900}
{"job":60,"team":456,"person":1000}
{"job":59,"team":678,"person":844}
{"job":98,"team":832,"person":866}
Time taken: 4.118 seconds, Fetched: 6 row(s)
hive>
----------map_test2-------
hive (default)> select * from map_test2;
OK
map_test2.id map_test2.perf
1001 job_1:80,team:123,person:700 NULL
1002 job_2:90,team:234,person:800 NULL
1003 job:70,team:345,person:900 NULL
1004 job:60,team:456,person:1000 NULL
1005 job:59,team:678,person:844 NULL
1006 job:98,team:832,person:866 NULL
Time taken: 0.086 seconds, Fetched: 6 row(s)
----------------
hive (default)> select perf['job_1'] from map_test2;
OK
c0
NULL
NULL
NULL
NULL
NULL
NULL
Time taken: 0.284 seconds, Fetched: 6 row(s)
-----------------------
hive (default)> select perf['job'] from map_test2;
OK
c0
NULL
NULL
NULL
NULL
NULL
NULL
Time taken: 0.084 seconds, Fetched: 6 row(s)
-------------------------------
hive (default)> select perf['job_2'] from map_test2;
OK
c0
NULL
NULL
NULL
NULL
NULL
NULL
Time taken: 0.074 seconds, Fetched: 6 row(s)
------------------------------
hive (default)> select perf from map_test2;
OK
perf
NULL
NULL
NULL
NULL
NULL
NULL
Time taken: 0.076 seconds, Fetched: 6 row(s)
-----------------原来：如果map字段名不一致，会被当成id字段来处理了---------
hive (default)> select id from map_test2;
OK
id
1001 job_1:80,team:123,person:700
1002 job_2:90,team:234,person:800
1003 job:70,team:345,person:900
1004 job:60,team:456,person:1000
1005 job:59,team:678,person:844
1006 job:98,team:832,person:866
Time taken: 0.064 seconds, Fetched: 6 row(s)
5、hadoop中的文件内容