Pig GROUP 运算符



  • GROUP 运算符

    GROUP运算符用于组中的数据的一个或多个关系。它收集具有相同key的数据。
    句法
    下面给出的是组运算符的语法。
    
    grunt> Group_data = GROUP Relation_name BY age;
    
    
    例子
    假设我们在HDFS目录/pig_data/中有一个名为student_details.txt的文件,如下所示。
    
    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
    
    
    并且我们已将这个文件以关系名称Student_details加载到Apache Pig中,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age对关系中的记录/元组进行分组,如下所示。
    
    grunt> group_data = GROUP student_details by age;
    
    
    验证
    如下所示,使用DUMP运算符验证关系group_data。
    
    grunt> Dump group_data;
    
    
    输出
    然后,您将获得输出,显示名为group_data的关系的内容,如下所示。在这里您可以观察到生成的模式有两列-
    一个是age,通过它我们将关系分组。
    另一个是一个bag,其中包含元组,带有相应年龄的学生记录。
    
    (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)})
    
    
    使用describe命令对数据进行分组后,可以看到表的架构,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,您可以使用Illustra命令获得该模式的样本插图,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age和city分组关系,如下所示。
    
    grunt> group_multiple = GROUP student_details by (age, city);
    
    
    您可以使用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)})
    
    
  • 全部分组

    您可以按如下所示的所有列对关系进行分组。
    
    grunt> group_all = GROUP student_details All;
    
    
    现在,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)})