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：

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：

$ 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：

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：

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：

$ 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：

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：

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：

$ 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：

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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