JOIN 运算符用于组合来自两个或多个关系的记录。在执行连接操作时，我们从每个关系中声明一个（或一组）元组作为key。 当这些key匹配时，两个特定的元组匹配，否则记录将被丢弃。连接可以是以下类型：

• Self-join
• Inner-join
• Outer-join − left join, right join, and full join

本章介绍了如何在Pig Latin中使用join运算符的示例。假设在HDFS的 /pig_data/ 目录中有两个文件，即customers.txt 和 orders.txt ，如下所示。

customers.txt

1,Ramesh,32,Ahmedabad,2000.00
2,Khilan,25,Delhi,1500.00
3,kaushik,23,Kota,2000.00
4,Chaitali,25,Mumbai,6500.00 
5,Hardik,27,Bhopal,8500.00
6,Komal,22,MP,4500.00
7,Muffy,24,Indore,10000.00

orders.txt

102,2009-10-08 00:00:00,3,3000
100,2009-10-08 00:00:00,3,1500
101,2009-11-20 00:00:00,2,1560
103,2008-05-20 00:00:00,4,2060

grunt> customers = LOAD 'hdfs://localhost:9000/pig_data/customers.txt' USING PigStorage(',')
   as (id:int, name:chararray, age:int, address:chararray, salary:int);
  
grunt> orders = LOAD 'hdfs://localhost:9000/pig_data/orders.txt' USING PigStorage(',')
   as (oid:int, date:chararray, customer_id:int, amount:int);

Self-join（自连接）

Self-join 用于将表与其自身连接，就像表是两个关系一样，临时重命名至少一个关系。通常，在Apache Pig中，为了执行self-join，我们将在不同的别名（名称）下多次加载相同的数据。那么，将文件 customers.txt 的内容加载为两个表，如下所示。

grunt> customers1 = LOAD 'hdfs://localhost:9000/pig_data/customers.txt' USING PigStorage(',')
   as (id:int, name:chararray, age:int, address:chararray, salary:int);
  
grunt> customers2 = LOAD 'hdfs://localhost:9000/pig_data/customers.txt' USING PigStorage(',')
   as (id:int, name:chararray, age:int, address:chararray, salary:int); 

下面给出使用 JOIN 运算符执行self-join操作的语法。

grunt> Relation3_name = JOIN Relation1_name BY key, Relation2_name BY key ;

例

通过如图所示加入两个关系 customers1 和 customers2 ，对关系 customers 执行self-join 操作。

grunt> customers3 = JOIN customers1 BY id, customers2 BY id;

使用 DUMP 运算符验证关系 customers3 ，如下所示。

grunt> Dump customers3;

输出

将产生以下输出，显示关系 customers 的内容。

(1,Ramesh,32,Ahmedabad,2000,1,Ramesh,32,Ahmedabad,2000)
(2,Khilan,25,Delhi,1500,2,Khilan,25,Delhi,1500)
(3,kaushik,23,Kota,2000,3,kaushik,23,Kota,2000)
(4,Chaitali,25,Mumbai,6500,4,Chaitali,25,Mumbai,6500)
(5,Hardik,27,Bhopal,8500,5,Hardik,27,Bhopal,8500)
(6,Komal,22,MP,4500,6,Komal,22,MP,4500)
(7,Muffy,24,Indore,10000,7,Muffy,24,Indore,10000)

Inner Join（内部连接）

Inner Join使用较为频繁；它也被称为等值连接。当两个表中都存在匹配时，内部连接将返回行。基于连接谓词（join-predicate），通过组合两个关系（例如A和B）的列值来创建新关系。查询将A的每一行与B的每一行进行比较，以查找满足连接谓词的所有行对。当连接谓词被满足时，A和B的每个匹配的行对的列值被组合成结果行。

语法

以下是使用 JOIN 运算符执行inner join操作的语法。

grunt> result = JOIN relation1 BY columnname, relation2 BY columnname;

让我们对customers和orders执行inner join操作，如下所示。

grunt> coustomer_orders = JOIN customers BY id, orders BY customer_id;

验证

使用 DUMP 运算符验证 coustomer_orders 关系，如下所示。

grunt> Dump coustomer_orders;

将获得以下输出，是名为 coustomer_orders 的关系的内容。

(2,Khilan,25,Delhi,1500,101,2009-11-20 00:00:00,2,1560)
(3,kaushik,23,Kota,2000,100,2009-10-08 00:00:00,3,1500)
(3,kaushik,23,Kota,2000,102,2009-10-08 00:00:00,3,3000)
(4,Chaitali,25,Mumbai,6500,103,2008-05-20 00:00:00,4,2060)

注意：

Outer Join：与inner join不同，outer join返回至少一个关系中的所有行。outer join操作以三种方式执行：

• Left outer join
• Right outer join
• Full outer join

Left Outer Join（左外连接）

left outer join操作返回左表中的所有行，即使右边的关系中没有匹配项。

语法

下面给出使用 JOIN 运算符执行left outer join操作的语法。

grunt> Relation3_name = JOIN Relation1_name BY id LEFT OUTER, Relation2_name BY customer_id;

让我们对customers和orders的两个关系执行left outer join操作，如下所示。

grunt> outer_left = JOIN customers BY id LEFT OUTER, orders BY customer_id;

验证

使用 DUMP 运算符验证关系 outer_left ，如下所示。

grunt> Dump outer_left;

它将产生以下输出，显示关系 outer_left 的内容。

(1,Ramesh,32,Ahmedabad,2000,,,,)
(2,Khilan,25,Delhi,1500,101,2009-11-20 00:00:00,2,1560)
(3,kaushik,23,Kota,2000,100,2009-10-08 00:00:00,3,1500)
(3,kaushik,23,Kota,2000,102,2009-10-08 00:00:00,3,3000)
(4,Chaitali,25,Mumbai,6500,103,2008-05-20 00:00:00,4,2060)
(5,Hardik,27,Bhopal,8500,,,,)
(6,Komal,22,MP,4500,,,,)
(7,Muffy,24,Indore,10000,,,,)

Right Outer Join（右外连接）

right outer join操作将返回右表中的所有行，即使左表中没有匹配项。

语法

下面给出使用 JOIN 运算符执行right outer join操作的语法。

grunt> outer_right = JOIN customers BY id RIGHT, orders BY customer_id;

让我们对customers和orders执行right outer join操作，如下所示。

grunt> outer_right = JOIN customers BY id RIGHT, orders BY customer_id;

验证

使用 DUMP 运算符验证关系 outer_right ，如下所示。

grunt> Dump outer_right

输出

它将产生以下输出，显示关系 outer_right 的内容。

(2,Khilan,25,Delhi,1500,101,2009-11-20 00:00:00,2,1560)
(3,kaushik,23,Kota,2000,100,2009-10-08 00:00:00,3,1500)
(3,kaushik,23,Kota,2000,102,2009-10-08 00:00:00,3,3000)
(4,Chaitali,25,Mumbai,6500,103,2008-05-20 00:00:00,4,2060)

Full Outer Join（全外连接）

当一个关系中存在匹配时，full outer join操作将返回行。

语法

下面给出使用 JOIN 运算符执行full outer join的语法。

grunt> outer_full = JOIN customers BY id FULL OUTER, orders BY customer_id;

让我们对customers和orders执行full outer join操作，如下所示。

grunt> outer_full = JOIN customers BY id FULL OUTER, orders BY customer_id;

使用 DUMP 运算符验证关系 outer_full ，如下所示。

grun> Dump outer_full; 

输出

它将产生以下输出，显示关系 outer_full 的内容。

(1,Ramesh,32,Ahmedabad,2000,,,,)
(2,Khilan,25,Delhi,1500,101,2009-11-20 00:00:00,2,1560)
(3,kaushik,23,Kota,2000,100,2009-10-08 00:00:00,3,1500)
(3,kaushik,23,Kota,2000,102,2009-10-08 00:00:00,3,3000)
(4,Chaitali,25,Mumbai,6500,103,2008-05-20 00:00:00,4,2060)
(5,Hardik,27,Bhopal,8500,,,,)
(6,Komal,22,MP,4500,,,,)
(7,Muffy,24,Indore,10000,,,,)

我们可以使用多个key执行JOIN操作。

语法

下面是如何使用多个key对两个表执行JOIN操作。

grunt> Relation3_name = JOIN Relation2_name BY (key1, key2), Relation3_name BY (key1, key2);

employee.txt

001,Rajiv,Reddy,21,programmer,003
002,siddarth,Battacharya,22,programmer,003
003,Rajesh,Khanna,22,programmer,003
004,Preethi,Agarwal,21,programmer,003
005,Trupthi,Mohanthy,23,programmer,003
006,Archana,Mishra,23,programmer,003
007,Komal,Nayak,24,teamlead,002
008,Bharathi,Nambiayar,24,manager,001

001,9848022337,Rajiv@gmail.com,Hyderabad,003
002,9848022338,siddarth@gmail.com,Kolkata,003
003,9848022339,Rajesh@gmail.com,Delhi,003
004,9848022330,Preethi@gmail.com,Pune,003
005,9848022336,Trupthi@gmail.com,Bhuwaneshwar,003
006,9848022335,Archana@gmail.com,Chennai,003
007,9848022334,Komal@gmail.com,trivendram,002
008,9848022333,Bharathi@gmail.com,Chennai,001

grunt> employee = LOAD 'hdfs://localhost:9000/pig_data/employee.txt' USING PigStorage(',')
   as (id:int, firstname:chararray, lastname:chararray, age:int, designation:chararray, jobid:int);
  
grunt> employee_contact = LOAD 'hdfs://localhost:9000/pig_data/employee_contact.txt' USING PigStorage(',') 
   as (id:int, phone:chararray, email:chararray, city:chararray, jobid:int);

grunt> emp = JOIN employee BY (id,jobid), employee_contact BY (id,jobid);

使用 DUMP 运算符验证关系 emp ，如下所示。

grunt> Dump emp; 

输出

它将产生以下输出，显示名为 emp 的关系的内容，如下所示。

(1,Rajiv,Reddy,21,programmer,113,1,9848022337,Rajiv@gmail.com,Hyderabad,113)
(2,siddarth,Battacharya,22,programmer,113,2,9848022338,siddarth@gmail.com,Kolka ta,113)  
(3,Rajesh,Khanna,22,programmer,113,3,9848022339,Rajesh@gmail.com,Delhi,113)  
(4,Preethi,Agarwal,21,programmer,113,4,9848022330,Preethi@gmail.com,Pune,113)  
(5,Trupthi,Mohanthy,23,programmer,113,5,9848022336,Trupthi@gmail.com,Bhuwaneshw ar,113)  
(6,Archana,Mishra,23,programmer,113,6,9848022335,Archana@gmail.com,Chennai,113)  
(7,Komal,Nayak,24,teamlead,112,7,9848022334,Komal@gmail.com,trivendram,112)  
(8,Bharathi,Nambiayar,24,manager,111,8,9848022333,Bharathi@gmail.com,Chennai,111)