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Apache Pig 介绍

Apache Pig 概述Apache Pig 架构

Apache Pig 环境

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Pig Latin 介绍

Pig Latin 基础

Apache Pig 加载和存储

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Apache Pig 诊断运算符

Apache Pig Diagnostic运算符Apache Pig Describe运算符Apache Pig Explain运算符Apache Pig illustrate运算符

Apache Pig 分组和连接

Apache Pig Group运算符Apache Pig Cogroup运算符Apache Pig Join运算符Apache Pig Cross运算符

Apache Pig 合并和拆分

Apache Pig Union运算符Apache Pig Split运算符

Apache Pig 过滤

Apache Pig Filter运算符Apache Pig Distinct运算符Apache Pig Foreach运算符

Apache Pig 排序

Apache Pig Order By运算符Apache Pig Limit运算符

Pig Latin 内置函数

Apache Pig Eval函数Apache Pig 加载和存储函数Apache Pig 包和元组函数Apache Pig 字符串函数Apache Pig 日期时间函数Apache Pig 数学函数

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Apache Pig 有用的资源

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Apache Pig Cross运算符


CROSS 运算符计算两个或多个关系的向量积。本章将以示例说明如何在Pig Latin中使用cross运算符。

语法

下面给出了 CROSS 运算符的语法。

grunt> Relation3_name = CROSS Relation1_name, Relation2_name;

假设在HDFS的 /pig_data/ 目录中有两个文件,即 customers.txt 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

将这两个文件加载到Pig中,通过关系 customers  orders,如下所示。

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);

现在让我们使用 cross 运算符获得这两个关系的向量积,如下所示。

grunt> cross_data = CROSS customers, orders;

验证

使用 DUMP 运算符验证关系 cross_data ,如下所示。

grunt> Dump cross_data;

输出

它将产生以下输出,显示关系 cross_data 的内容。

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



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