📅 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。
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;
如下所示，使用DUMP运算符验证关系group_data 。
grunt> Dump group_data;
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。
另一个是一个包，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)}|
-------------------------------------------------------------------------------------------------
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)})
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)})