Scala Programming for Big Data Analytics: Get Started with Big Data Analytics Using Apache Spark (大數據分析的Scala程式設計:使用Apache Spark入門大數據分析)
Elahi, Irfan
- 出版商: Apress
- 出版日期: 2019-07-06
- 定價: $1,200
- 售價: 8.0 折 $960
- 語言: 英文
- 頁數: 175
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1484248090
- ISBN-13: 9781484248096
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相關分類:
JVM 語言、Spark、大數據 Big-data、Data Science
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相關翻譯:
快速上手 Scala:Spark 大數據分析入門 (簡中版)
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商品描述
Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you'll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks.
The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scala's powerful collections system because many of Apache Spark's APIs bear a strong resemblance to Scala collections.
Along the way you'll see the development life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You'll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications. Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics.
What You Will Learn
- See the fundamentals of Scala as a general-purpose programming language
- Understand functional programming and object-oriented programming constructs in Scala
- Use Scala collections and functions
- Develop, package and run Apache Spark applications for big data analytics
Who This Book Is For
Data scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics.
商品描述(中文翻譯)
在大數據分析和Apache Spark的背景下,掌握Scala的關鍵語言概念和編程技巧。本書首先介紹Scala,並建立了一個堅實的背景理解,解釋了為什麼你應該學習這門語言,它與Java相比的優勢,以及Scala與Apache Spark在大數據分析中的關聯。接下來,您將設置Scala環境,準備好檢查您的第一個Scala程序。然後,介紹Scala的基礎知識,包括可變/不可變變量、類型層次結構、控制流表達式和代碼塊。
作者詳細討論了函數並突出了一些相關概念,如函數式編程和匿名函數。然後,更深入地探討了Scala強大的集合系統,因為Apache Spark的許多API與Scala集合非常相似。
在學習過程中,您將了解Scala程序的開發生命周期。這包括使用行業標準的Scala Build Tool(SBT)編譯和構建程序。您將學習使用SBT進行依賴管理的相關指南,因為這對於構建大型Apache Spark應用程序至關重要。
《Scala Programming for Big Data Analytics》最後展示了如何利用這些概念編寫在Apache Spark框架上運行的程序。這些程序將提供分佈式和並行計算,這對於大數據分析至關重要。
你將學到什麼
- 瞭解Scala作為通用編程語言的基礎知識
- 理解Scala中的函數式編程和面向對象編程構造
- 使用Scala集合和函數
- 開發、打包和運行用於大數據分析的Apache Spark應用程序
本書適合對象
- 數據科學家、數據分析師和數據工程師,打算使用Apache Spark進行大規模分析。
作者簡介
Irfan Elahi is a senior consultant in Deloitte Australia specializing in big data and machine learning. His primary focus lies in using big data and machine learning to support business growth with multifaceted and strong ties to the telecommunications, energy, retail and media industries. He has worked on a number of projects in Australia to design, prototype, develop, and deploy production-grade big data solutions in Amazon Web Services (AWS) and Azure to support a number of use-cases ranging from enterprise data warehousing, ETL offloading, analytics, batch processing and stream processing while employing leading commercial Hadoop solutions such as Cloudera and Hortonworks. He has worked closely with clients' systems and software engineering teams using DevOps to enhance the continuous integration and continuous deployment (CICD) processes and manage a Hadoop cluster's operations and security.
In addition to his technology competencies, Irfan has recently presented at the DataWorks Summit in Sydney on the subject of in-memory big data technologies and in a number of meetups all around the world. He also remains involved delivering knowledge-transfer sessions, training and workshops about big data and machine learning, both within his firm and at clients. He also has launched Udemy courses on Apache Spark for big data analytics and R programming for data science with more than 18,000 students from 145 countries enrolled.
作者簡介(中文翻譯)
Irfan Elahi是Deloitte Australia的高級顧問,專注於大數據和機器學習。他的主要重點是利用大數據和機器學習來支持電信、能源、零售和媒體行業的業務增長。他在澳大利亞進行了多個項目,設計、原型開發和部署了Amazon Web Services(AWS)和Azure中的生產級大數據解決方案,以支持從企業數據倉儲、ETL卸載、分析、批處理和流處理等多種用例,並使用Cloudera和Hortonworks等領先的商業Hadoop解決方案。他與客戶的系統和軟件工程團隊密切合作,使用DevOps來增強持續集成和持續部署(CICD)流程,並管理Hadoop集群的運營和安全性。
除了技術能力外,Irfan最近在悉尼的DataWorks Summit上就內存大數據技術發表了演講,並在世界各地的多個聚會上發表了演講。他還積極參與在公司內部和客戶處進行關於大數據和機器學習的知識傳遞會議、培訓和研討會。他還在Udemy上推出了關於Apache Spark大數據分析和R編程數據科學的課程,已有來自145個國家的超過18,000名學生報名參加。