hive复合数据类型之map

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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<string,int>)

> 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,perfmap<string,int>)

create table student_test(id int,infostruct<name:string,age:int>)

------------

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<string,int>)
> 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

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