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所在平台: Udemy |
课程主页: https://www.udemy.com/course/apache-spark-course-with-java/
课程评论：没有评论
课程名称：Apache Spark 2.0与Java - 从大数据专家那里学习Spark 课程概述：本课程涵盖了Apache Spark与Java的所有基础知识，并教您开发Spark应用所需的一切技能。完成此课程后，您将深入理解Apache Spark及其在大数据分析和处理中的应用，帮助您的公司利用Apache Spark构建大数据处理管道和数据分析应用。课程包括10多个实际操作的大数据实例，您将学习如何将数据分析问题框架化为Spark问题。课程中将探索多个有趣的案例，例如：聚合来自不同来源的NASA Apache网站日志；分析加州房地产数据的价格趋势；使用Stack Overflow调查数据计算不同国家开发者的中位数薪资；开发分析英国各地区制作空间分布的系统等。 您将从本课程中学到： - Apache Spark的架构概述。 - 使用Java开发Apache Spark 2.0应用，包括RDD转换和行动以及Spark SQL。 - 利用弹性分布式数据集（RDDs）处理和分析大数据集。 - 深入研究优化和调优Apache Spark作业的高级技术，如分区、缓存和持久化RDDs。 - 通过Amazon的Elastic MapReduce服务在Hadoop YARN集群上扩展Spark应用。 - 使用数据集和数据框架分析结构化和半结构化数据，并深入理解Spark SQL。 - 在Apache Spark集群中通过广播变量和累加器在不同节点之间共享信息。 - 处理Apache Spark的最佳实践。 - 大数据生态系统概述。 学习Apache Spark的原因：Apache Spark为我们提供了构建尖端应用的无限可能性，是过去十年里对大数据领域影响最大的技术之一。Spark提供内存集群计算，极大提升了迭代算法和交互式数据挖掘任务的速度，成为下一代大数据处理引擎。许多公司正在采用Apache Spark来从海量数据集中提取有意义的信息，您现在也可以在您的桌面上访问这一先进技术。 关于作者：自2015年以来，James一直在帮助他的公司采用Apache Spark构建大数据处理管道和数据分析应用，他的公司通过在生产中使用Apache Spark获得了巨大的好处。在本课程中，James将分享他多年的知识和真实领域的工作最佳实践。 选择本课程的理由：本课程非常实践，James为您提供了理论和实际开发Spark应用的真实示例，您可以在自己的笔记本电脑上尝试。所有源代码均已上传至Github，您可以在Windows、MAC OS或Linux上进行跟随学习。完成本课程后，James相信您将获得对Spark的深入理解和大数据分析、数据处理的技能，能够在您的笔记本电脑上以及使用Amazon的Elastic MapReduce服务在云中分析千兆字节级别的数据！ 30天退款保证：您可以在30天内申请退款，如果不满意，随时要求全额退款，无需任何理由。准备好提升您的大数据分析技能和职业生涯吗？现在就参加这门课程吧！您将从零基础变为Spark高手，仅需4小时。
What is this course about: This course covers all the fundamentals about Apache Spark with Java and teaches you everything you need to know about developing Spark applications with Java. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipeline and data analytics applications. This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom. And much much more. What will you learn from this lecture: In particularly, you will learn: An overview of the architecture of Apache Spark.Develop Apache Spark 2.0 applications with Java using RDD transformations and actions and Spark SQL.Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.Deep dive into advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.Scale up Spark applications on a Hadoop YARN cluster through Amazon's Elastic MapReduce service.Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Spark SQL.Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators.Best practices of working with Apache Spark in the field.Big data ecosystem overview. Why shall we learn Apache Spark: Apache Spark gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world. Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks. Apache Spark is the next-generation processing engine for big data. Tons of companies are adapting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop. Apache Spark is becoming a must tool for big data engineers and data scientists. About the author: Since 2015, James has been helping his company to adapt Apache Spark for building their big data processing pipeline and data analytics applications. James' company has gained massive benefits by adapting Apache Spark in production. In this course, he is going to share with you his years of knowledge and best practices of working with Spark in the real field. Why choosing this course? This course is very hands-on, James has put lots effort to provide you with not only the theory but also real-life examples of developing Spark applications that you can try out on your own laptop. James has uploaded all the source code to Github and you will be able to follow along with either Windows, MAC OS or Linux. In the end of this course, James is confident that you will gain in-depth knowledge about Spark and general big data analysis and data manipulation skills. You'll be able to develop Spark application that analyzes Gigabytes scale of data both on your laptop, and in the cloud using Amazon's Elastic MapReduce service! 30-day Money-back Guarantee! You will get 30-day money-back guarantee from Udemy for this course. If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked. Are you ready to take your big data analysis skills and career to the next level, take this course now! You will go from zero to Spark hero in 4 hours.
