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所在平台: Udemy |
课程主页: https://www.udemy.com/course/apache-spark-with-scala-hands-on-with-big-data/
课程评论：没有评论
课程名称：Apache Spark与Scala - 大数据实践！ 概述：本课程针对Spark 3进行了全面更新和重新录制，涵盖IntelliJ、结构化流处理以及对DataSet API的更强关注。“大数据”分析是一项非常热门且有价值的技能。本课程将教授您当前大数据领域最热门的技术：Apache Spark。包括亚马逊、eBay、NASA JPL和雅虎等公司都在使用Spark快速从大量数据集中提取有意义的信息。您将在自己的Windows系统上学习这些技术，简单易行。课程的讲师是前亚马逊和IMDb的工程师及高级经理。 Spark与Scala编程语言配合使用效果最佳，本课程包含了Scala的快速入门，以帮助您迅速掌握。对于更熟悉Python的学习者，本课程也提供Python版本：“使用Apache Spark和Python驾驭大数据 - 实践篇”。 通过超过20个实践示例，您将学习并掌握将数据分析问题转化为Spark问题的艺术，并将其扩展到云计算服务上运行。课程内容包括： - 了解Spark的弹性分布式数据集、DataFrames和Datasets的概念 - 深入学习Scala编程语言 - 使用Scala、IntelliJ和SBT快速开发和运行Spark作业 - 将复杂的分析问题转化为迭代或多阶段的Spark脚本 - 使用亚马逊的Elastic MapReduce服务扩展至更大数据集 - 理解Hadoop YARN如何在计算集群上分配Spark作业 - 练习使用其他Spark技术，如Spark SQL、DataFrames、Datasets、Spark Streaming、机器学习和GraphX 课程结束时，您将能够在云端迅速运行分析数十亿信息的代码。学习过程中将进行一些简单的例子，例如分析电影评分数据和书中的文本。在掌握基础之后，我们将展开更复杂和值得兴趣的任务，比如利用一百万条电影评分数据寻找相似电影，甚至可能发现一些您可能喜欢的新电影。此外，我们还将分析超级英雄的社交图谱，学习最“受欢迎”的超级英雄，并开发找到超级英雄之间“分隔度”的系统。 该课程非常注重实践，您将大部分时间与讲师一起编写、分析和运行真实代码，不论是在自己的系统上，还是在使用亚马逊Elastic MapReduce服务的云端上。课程包含超过8小时的视频内容，以及20多个复杂性逐步增加的真实示例，您可以根据自己的节奏和时间安排进行学习。课程最后将概述其他基于Spark的技术，包括Spark SQL、Spark Streaming和GraphX。 立即报名，享受课程吧！
Completely updated and re-recorded for Spark 3, IntelliJ, Structured Streaming, and a stronger focus on the DataSet API."Big data" analysis is a hot and highly valuable skill - and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon, EBay, NASA JPL, and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think, and you'll be learning from an ex-engineer and senior manager from Amazon and IMDb.Spark works best when using the Scala programming language, and this course includes a crash-course in Scala to get you up to speed quickly. For those more familiar with Python however, a Python version of this class is also available: "Taming Big Data with Apache Spark and Python - Hands On".Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples, and then scale them up to run on cloud computing services in this course.Learn the concepts of Spark's Resilient Distributed Datasets, DataFrames, and Datasets.Get a crash course in the Scala programming languageDevelop and run Spark jobs quickly using Scala, IntelliJ, and SBTTranslate complex analysis problems into iterative or multi-stage Spark scriptsScale up to larger data sets using Amazon's Elastic MapReduce serviceUnderstand how Hadoop YARN distributes Spark across computing clustersPractice using other Spark technologies, like Spark SQL, DataFrames, DataSets, Spark Streaming, Machine Learning, and GraphXBy the end of this course, you'll be running code that analyzes gigabytes worth of information - in the cloud - in a matter of minutes. We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most "popular" superhero is - and develop a system to find "degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to SpiderMan? You'll find the answer.This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together - both on your own system, and in the cloud using Amazon's Elastic MapReduce service. over 8 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX.Enroll now, and enjoy the course!"I studied Spark for the first time using Frank's course "Apache Spark with Scala - Hands On with Big Data!". It was a great starting point for me, gaining knowledge in Scala and most importantly practical examples of Spark applications. It gave me an understanding of all the relevant Spark core concepts, RDDs, Dataframes & Datasets, Spark Streaming, AWS EMR. Within a few months of completion, I used the knowledge gained from the course to propose in my current company to work primarily on Spark applications. Since then I have continued to work with Spark. I would highly recommend any of Franks courses as he simplifies concepts well and his teaching manner is easy to follow and continue with! " - Joey Faherty
