Fast Data Processing with Spark 2 - Third Edition

版本说明：3rd

作     者：Sankar, Krishna 

I S B N：(纸本) 9781785889271;9781785882968 

出 版 社：Packt Publishing 

出 版 年：2016年

主 题 词：Real time data processing 

学科分类：0810[工学-信息与通信工程] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 081002[工学-信号与信息处理] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：About This BookA quick way to get started with Spark – and reap the rewardsFrom analytics to engineering your big data architecture, we ve got it coveredBring your Scala and Java knowledge – and put it to work on new and exciting problemsWho This Book Is ForThis book is for developers with little to no knowledge of Spark, but with a background in Scala/Java programming. It s recommended that you have experience in dealing and working with big data and a strong interest in data *** You Will LearnInstall and set up Spark in your clusterPrototype distributed applications with Spark s interactive shellPerform data wrangling using the new DataFrame APIsGet to know the different ways to interact with Spark s distributed representation of data (RDDs)Query Spark with a SQL-like query syntaxSee how Spark works with big dataUnderstand how data scientists and data engineers can use the Spark frameworkImplement machine learning systems with highly scalable algorithmsUse R, the popular statistical language, to work with SparkApply interesting graph algorithms and graph processing with GraphXIn DetailWhen people want a way to process big data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it s unsurprising that it s becoming popular with data analysts and engineers *** with the fundamentals, we ll show you how to get set up with Spark with minimum fuss. You ll then get to grips with some simple APIs before investigating machine learning and graph processing―throughout we ll make sure you know exactly how to apply your knowledge. For cloud deployments of Spark, we will look at EC2 (both traditional and EC2MR).You will also learn how to use the Spark shell and load data before finding out how to build and run your own Spark applications. Discover how to manipulate your RDD and get stuck into a range of DataFrame APIs. As if that s not enough, you ll also learn some u