Apache Pig Group运算符

由 jarodhu 创建，youj 最后一次修改 2016-12-28 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,Hyderabad002,siddarth,Battacharya,22,9848022338,Kolkata003,Rajesh,Khanna,22,9848022339,Delhi004,Preethi,Agarwal,21,9848022330,Pune005,Trupthi,Mohanthy,23,9848022336,Bhuwaneshwar006,Archana,Mishra,23,9848022335,Chennai007,Komal,Nayak,24,9848022334,trivendram008,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)})