- Apache Pig 教程
- Apache Pig - 首頁
- Apache Pig 簡介
- Apache Pig - 概述
- Apache Pig - 架構
- Apache Pig 環境
- Apache Pig - 安裝
- Apache Pig - 執行
- Apache Pig - Grunt Shell
- Pig Latin
- Pig Latin - 基礎
- 載入 & 儲存運算子
- Apache Pig - 讀取資料
- Apache Pig - 儲存資料
- 診斷運算子
- Apache Pig - 診斷運算子
- Apache Pig - Describe 運算子
- Apache Pig - Explain 運算子
- Apache Pig - Illustrate 運算子
- Pig Latin 內建函式
- Apache Pig - Eval 函式
- 載入 & 儲存函式
- Apache Pig - Bag & Tuple 函式
- Apache Pig - 字串函式
- Apache Pig - 日期時間函式
- Apache Pig - 數學函式
- Apache Pig 有用資源
- Apache Pig - 快速指南
- Apache Pig - 有用資源
- Apache Pig - 討論
Apache Pig - 交叉運算子
CROSS 運算子計算兩個或多個關係的笛卡爾積。本章透過示例解釋如何在 Pig Latin 中使用交叉運算子。
語法
以下是 CROSS 運算子的語法。
grunt> Relation3_name = CROSS Relation1_name, Relation2_name;
示例
假設我們在 HDFS 的 /pig_data/ 目錄下有兩個檔案,分別為 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
並且我們已使用關係 customers 和 orders 將這兩個檔案載入到 Pig 中,如下所示。
grunt> customers = LOAD 'hdfs://:9000/pig_data/customers.txt' USING PigStorage(',')
as (id:int, name:chararray, age:int, address:chararray, salary:int);
grunt> orders = LOAD 'hdfs://:9000/pig_data/orders.txt' USING PigStorage(',')
as (oid:int, date:chararray, customer_id:int, amount:int);
現在,讓我們使用這兩個關係上的 cross 運算子獲取這兩個關係的笛卡爾積,如下所示。
grunt> cross_data = CROSS customers, orders;
驗證
使用 DUMP 運算子驗證關係 cross_data,如下所示。
grunt> Dump cross_data;
輸出
它將生成以下輸出,顯示關係 cross_data 的內容。
(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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