Group运算符
GROUP 运算符用于在一个或多个关系中对数据进行分组,它收集具有相同key的数据。
语法
下面给出了 group 运算符的语法。
- grunt> Group_data = GROUP Relation_name BY age;
例
假设在HDFS目录 /pig_data/ 中有一个名为 student_details.txt 的文件,如下所示。
student_details.txt
- 001,Rajiv,Reddy,21,9848022337,Hyderabad
- 002,siddarth,Battacharya,22,9848022338,Kolkata
- 003,Rajesh,Khanna,22,9848022339,Delhi
- 004,Preethi,Agarwal,21,9848022330,Pune
- 005,Trupthi,Mohanthy,23,9848022336,Bhuwaneshwar
- 006,Archana,Mishra,23,9848022335,Chennai
- 007,Komal,Nayak,24,9848022334,trivendram
- 008,Bharathi,Nambiayar,24,9848022333,Chennai
将这个文件加载到Apache Pig中,关系名称为student_details,如下所示。
- grunt> student_details = LOAD 'hdfs://localhost:9000/pig_data/student_details.txt' USING PigStorage(',')
- as (id:int, firstname:chararray, lastname:chararray, age:int, phone:chararray, city:chararray);
现在,让我们按照年龄关系中的记录/元组进行分组,如下所示。
- grunt> group_data = GROUP student_details by age;
验证
使用 DUMP 运算符验证关系 group_data ,如下所示。
- grunt> Dump group_data;
输出
将获得显示名为group_data关系的内容的输出,如下所示。在这里你可以观察到结果模式有两列:
一个是age,通过它我们将关系分组。
另一个是bag,其中包含一组元组,有各自年龄的学生记录。
- (21,{(4,Preethi,Agarwal,21,9848022330,Pune),(1,Rajiv,Reddy,21,9848022337,Hydera bad)})
- (22,{(3,Rajesh,Khanna,22,9848022339,Delhi),(2,siddarth,Battacharya,22,984802233 8,Kolkata)})
- (23,{(6,Archana,Mishra,23,9848022335,Chennai),(5,Trupthi,Mohanthy,23,9848022336 ,Bhuwaneshwar)})
- (24,{(8,Bharathi,Nambiayar,24,9848022333,Chennai),(7,Komal,Nayak,24,9848022334, trivendram)})
在使用 describe 命令分组数据后,可以看到表的模式,如下所示。
- grunt> Describe group_data;
- group_data: {group: int,student_details: {(id: int,firstname: chararray,
- lastname: chararray,age: int,phone: chararray,city: chararray)}}
以同样的方式,可以使用illustrate命令获取模式的示例说明,如下所示。
- $ Illustrate group_data;
它将产生以下输出
- -------------------------------------------------------------------------------------------------
- |group_data| group:int | student_details:bag{:tuple(id:int,firstname:chararray,lastname:chararray,age:int,phone:chararray,city:chararray)}|
- -------------------------------------------------------------------------------------------------
- | | 21 | { 4, Preethi, Agarwal, 21, 9848022330, Pune), (1, Rajiv, Reddy, 21, 9848022337, Hyderabad)}|
- | | 2 | {(2,siddarth,Battacharya,22,9848022338,Kolkata),(003,Rajesh,Khanna,22,9848022339,Delhi)}|
- -------------------------------------------------------------------------------------------------
按多列分组
让我们按年龄和城市对关系进行分组,如下所示。
- grunt> group_multiple = GROUP student_details by (age, city);
可以使用Dump运算符验证名为 group_multiple 的关系的内容,如下所示。
- grunt> Dump group_multiple;
- ((21,Pune),{(4,Preethi,Agarwal,21,9848022330,Pune)})
- ((21,Hyderabad),{(1,Rajiv,Reddy,21,9848022337,Hyderabad)})
- ((22,Delhi),{(3,Rajesh,Khanna,22,9848022339,Delhi)})
- ((22,Kolkata),{(2,siddarth,Battacharya,22,9848022338,Kolkata)})
- ((23,Chennai),{(6,Archana,Mishra,23,9848022335,Chennai)})
- ((23,Bhuwaneshwar),{(5,Trupthi,Mohanthy,23,9848022336,Bhuwaneshwar)})
- ((24,Chennai),{(8,Bharathi,Nambiayar,24,9848022333,Chennai)})
- (24,trivendram),{(7,Komal,Nayak,24,9848022334,trivendram)})
Group All
你可以按所有的列对关系进行分组,如下所示。
- grunt> group_all = GROUP student_details All;
现在,请验证关系 group_all 的内容,如下所示。
- grunt> Dump group_all;
- (all,{(8,Bharathi,Nambiayar,24,9848022333,Chennai),(7,Komal,Nayak,24,9848022334 ,trivendram),
- (6,Archana,Mishra,23,9848022335,Chennai),(5,Trupthi,Mohanthy,23,9848022336,Bhuw aneshwar),
- (4,Preethi,Agarwal,21,9848022330,Pune),(3,Rajesh,Khanna,22,9848022339,Delhi),
- (2,siddarth,Battacharya,22,9848022338,Kolkata),(1,Rajiv,Reddy,21,9848022337,Hyd erabad)})
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