Hive中的集合数据类型

Hive系列文章

除了使用础的数据类型string等，Hive中的列支持使用struct, map, array集合数据类型。

数据类型	描述	语法示例
STRUCT	和C语言中的struct或者"对象"类似，都可以通过"点"符号访问元素内容。	struct{'John', 'Doe'}
MAP	MAP是一组键-值对元素集合，使用key可以访问元素。	map('fisrt', 'John', 'last', 'Doe')
ARRAY	数组是一组具有相同数据类型和名称的变量的集合。	Array('John', 'Doe')

1. Array的使用

创建数据库表，以array作为数据类型

create table  person(name string,work_locations array<string>)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
COLLECTION ITEMS TERMINATED BY ',';

数据

biansutao beijing,shanghai,tianjin,hangzhou
linan changchu,chengdu,wuhan

入库数据

LOAD DATA LOCAL INPATH '/home/hadoop/person.txt' OVERWRITE INTO TABLE person;

查询

hive> select * from person;
biansutao       ["beijing","shanghai","tianjin","hangzhou"]
linan   ["changchu","chengdu","wuhan"]
Time taken: 0.355 seconds
hive> select name from person;
linan
biansutao
Time taken: 12.397 seconds
hive> select work_locations[0] from person;
changchu
beijing
Time taken: 13.214 seconds
hive> select work_locations from person;   
["changchu","chengdu","wuhan"]
["beijing","shanghai","tianjin","hangzhou"]
Time taken: 13.755 seconds
hive> select work_locations[3] from person;
NULL
hangzhou
Time taken: 12.722 seconds
hive> select work_locations[4] from person;
NULL
NULL
Time taken: 15.958 seconds

2. Map 的使用

创建数据库表

create table score(name string, score map<string,int>)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
COLLECTION ITEMS TERMINATED BY ','
MAP KEYS TERMINATED BY ':';

要入库的数据

biansutao '数学':80,'语文':89,'英语':95
jobs '语文':60,'数学':80,'英语':99

入库数据

LOAD DATA LOCAL INPATH '/home/hadoop/score.txt' OVERWRITE INTO TABLE score;

查询

hive> select * from score;
biansutao       {"数学":80,"语文":89,"英语":95}
jobs    {"语文":60,"数学":80,"英语":99}
Time taken: 0.665 seconds
hive> select name from score;
jobs
biansutao
Time taken: 19.778 seconds
hive> select t.score from score t;
{"语文":60,"数学":80,"英语":99}
{"数学":80,"语文":89,"英语":95}
Time taken: 19.353 seconds
hive> select t.score['语文'] from score t;
60
89
Time taken: 13.054 seconds
hive> select t.score['英语'] from score t;
99
95
Time taken: 13.769 seconds

修改map字段的分隔符

Storage Desc Params:         
    colelction.delim        ##                  
    field.delim             \t                  
    mapkey.delim            =                   
    serialization.format    \t

可以通过desc formatted tableName查看表的属性。
hive-2.1.1中，可以看出colelction.delim，这里是colelction而不是collection，hive里面这个单词写错了，所以还是要按照错误的来。

alter table t8 set serdepropertyes('colelction.delim'=',');

3. Struct 的使用

创建数据表

CREATE TABLE test(id int,course struct<course:string,score:int>)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
COLLECTION ITEMS TERMINATED BY ',';

数据

1 english,80
2 math,89
3 chinese,95

入库

LOAD DATA LOCAL INPATH '/home/hadoop/test.txt' OVERWRITE INTO TABLE test;

查询

hive> select * from test;
OK
1       {"course":"english","score":80}
2       {"course":"math","score":89}
3       {"course":"chinese","score":95}
Time taken: 0.275 seconds
hive> select course from test;
{"course":"english","score":80}
{"course":"math","score":89}
{"course":"chinese","score":95}
Time taken: 44.968 seconds
select t.course.course from test t; 
english
math
chinese
Time taken: 15.827 seconds
hive> select t.course.score from test t;
80
89
95
Time taken: 13.235 seconds

4. 不支持组合的复杂数据类型

我们有时候可能想建一个复杂的数据集合类型，比如下面的a字段，本身是一个Map，它的key是string类型的，value是Array集合类型的。

建表

create table test1(id int,a MAP<STRING,ARRAY<STRING>>)
row format delimited fields terminated by '\t' 
collection items terminated by ','
MAP KEYS TERMINATED BY ':';

导入数据

1 english:80,90,70
2 math:89,78,86
3 chinese:99,100,82

LOAD DATA LOCAL INPATH '/home/hadoop/test1.txt' OVERWRITE INTO TABLE test1;

这里查询出数据：

hive> select * from test1;
OK
1   {"english":["80"],"90":null,"70":null}
2   {"math":["89"],"78":null,"86":null}
3   {"chinese":["99"],"100":null,"82":null}

可以看到，已经出问题了，我们意图是想"english":["80", "90", "70"]，实际上把90和70也当作Map的key了，value值都是空的。分析一下我们的建表语句，collection items terminated by ','制定了集合类型（map, struct, array）数据元素之间分隔符是", "，实际上map也是属于集合的，那么也会按照逗号分出3个key-value对；由于MAP KEYS TERMINATED BY ':'定义了map中key-value的分隔符是":"，第一个“english”可以准确识别，后面的直接把value置为"null"了。

1. Array的使用

2. Map 的使用

3. Struct 的使用

4. 不支持组合的复杂数据类型

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