Hive表的基本操作
Hive中的集合数据类型
Hive动态分区详解
hive中orc格式表的数据导入
Java通过jdbc连接hive
通过HiveServer2访问Hive
SpringBoot连接Hive实现自助取数
hive关联hbase表
Hive udf 使用方法
Hive基于UDF进行文本分词
Hive窗口函数row number的用法
数据仓库之拉链表
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)
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 seconds2. Map 的使用
创建数据库表
create table score(name string, score map)
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)
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 seconds4. 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>)
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。
