hive array、map、struct使用

hive提供了复合数据类型：

Structs： structs内部的数据可以通过DOT（.）来存取，例如，表中一列c的类型为STRUCT{a INT; b INT}，我们可以通过c.a来访问域a

Maps（K-V对）：访问指定域可以通过["指定域名称"]进行，例如，一个Map M包含了一个group-》gid的kv对，gid的值可以通过M['group']来获取

Arrays：array中的数据为相同类型，例如，假如array A中元素['a','b','c']，则A[1]的值为'b'

Struct使用

建表：

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hive> create table student_test(id INT, info struct<name:STRING, age:INT>)

> ROW FORMAT DELIMITED FIELDS TERMINATED BY ','

> COLLECTION ITEMS TERMINATED BY ':';

OK

Time taken: 0.446 seconds

'FIELDS TERMINATED BY' ：字段与字段之间的分隔符

''COLLECTION ITEMS TERMINATED BY' ：一个字段各个item的分隔符

导入数据：

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$ cat test5.txt

1,zhou:30

2,yan:30

3,chen:20

4,li:80

hive> LOAD DATA LOCAL INPATH '/home/work/data/test5.txt' INTO TABLE student_test;

Copying data from file:/home/work/data/test5.txt

Copying file: file:/home/work/data/test5.txt

Loading data to table default.student_test

OK

Time taken: 0.35 seconds

查询：

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hive> select info.age from student_test;

Total MapReduce jobs = 1

......

Total MapReduce CPU Time Spent: 490 msec

OK

30

30

20

80

Time taken: 21.677 seconds

Array使用

建表：

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hive> create table class_test(name string, student_id_list array<INT>)

> ROW FORMAT DELIMITED

> FIELDS TERMINATED BY ','

> COLLECTION ITEMS TERMINATED BY ':';

OK

Time taken: 0.099 seconds

导入数据：

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$ cat test6.txt

034,1:2:3:4

035,5:6

036,7:8:9:10

hive> LOAD DATA LOCAL INPATH '/home/work/data/test6.txt' INTO TABLE class_test ;

Copying data from file:/home/work/data/test6.txt

Copying file: file:/home/work/data/test6.txt

Loading data to table default.class_test

OK

Time taken: 0.198 seconds

查询：

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hive> select student_id_list[3] from class_test;

Total MapReduce jobs = 1

......

Total MapReduce CPU Time Spent: 480 msec

OK

4

NULL

10

Time taken: 21.574 seconds

Map使用

建表：

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hive> create table employee(id string, perf map<string, int>)

> ROW FORMAT DELIMITED

> FIELDS TERMINATED BY '\t'

> COLLECTION ITEMS TERMINATED BY ','

> MAP KEYS TERMINATED BY ':';

OK

Time taken: 0.144 seconds

‘MAP KEYS TERMINATED BY’ ：key value分隔符

导入数据：

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$ cat test7.txt

1 job:80,team:60,person:70

2 job:60,team:80

3 job:90,team:70,person:100

hive> LOAD DATA LOCAL INPATH '/home/work/data/test7.txt' INTO TABLE employee;

查询：

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hive> select perf['person'] from employee;

Total MapReduce jobs = 1

......

Total MapReduce CPU Time Spent: 460 msec

OK

70

NULL

100

Time taken: 20.902 seconds

hive> select perf['person'] from employee where perf['person'] is not null;

Total MapReduce jobs = 1

.......

Total MapReduce CPU Time Spent: 610 msec

OK

70

100

Time taken: 21.989 seconds

hive>

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