📜  Apache Pig-组操作员

📅  最后修改于: 2020-12-02 05:34:35             🧑  作者: Mango


GROUP运算符用于将数据分组为一个或多个关系。它收集具有相同密钥的数据。

句法

下面给出的是group运算符的语法。

grunt> Group_data = GROUP Relation_name BY age;

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。

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

并且我们已将该文件以关系名称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,让我们按年龄对关系中的记录/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,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)}}

以相同的方式,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);

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

您可以按所有列将关系分组,如下所示。

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)})