- Programming MapReduce with Scalding
- Antonios Chalkiopoulos
- 138字
- 2021-12-08 12:44:20
Chapter 1. Introduction to MapReduce
In this first chapter, we will take a look at the core technologies used in the distributed model of Hadoop; more specifically, we cover the following:
- The Hadoop platform and the framework it provides
- The MapReduce programming model
- Technologies built on top of MapReduce that provide an abstraction layer and an API that is easier to understand and work with
In the following diagram, Hadoop stands at the base, and MapReduce as a design pattern enables the execution of distributed jobs. MapReduce is a low-level programming model. Thus, a number of libraries such as Cascading, Pig, and Hive provide alternative APIs and are compiled into MapReduce. Cascading, which is a Java application framework, has a number of extensions in functional programming languages, with Scalding being the one presented in this book.

推薦閱讀
- ExtGWT Rich Internet Application Cookbook
- 基于粒計算模型的圖像處理
- Mobile Application Development:JavaScript Frameworks
- Boost C++ Application Development Cookbook(Second Edition)
- 算法零基礎一本通(Python版)
- Access 數據庫應用教程
- PHP網絡編程學習筆記
- 零基礎學Java程序設計
- Nexus規模化Scrum框架
- 從Excel到Python:用Python輕松處理Excel數據(第2版)
- Visual C#.NET程序設計
- R大數據分析實用指南
- Mastering JBoss Enterprise Application Platform 7
- ElasticSearch Cookbook(Second Edition)
- Hands-On Nuxt.js Web Development