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所在平台: Udemy |
课程主页: https://www.udemy.com/course/tuning-apache-spark-powerful-big-data-processing-recipes/
课程评论：没有评论
**课程名称：** Tuning Apache Spark: Powerful Big Data Processing Recipes (调优 Apache Spark：强大的大数据处理秘诀) **课程概述：** 本课程是一条专门设计的学习路径，旨在帮助学习者掌握处理海量数据和实时数据分析的技能。通过结合实际应用与性能调优，您将学会如何高效地使用 Apache Spark 来解决大数据分析的挑战。 课程将从基础入手，循序渐进地介绍 Spark 的使用方法，并提供实用的技术来改善 Spark 编程和管理的各个方面，从而让您能够更快地完成任务并充分发挥数据处理能力。 随着学习的深入，您还将接触到一些鲜为人知的 Spark 性能优化技巧，并学会轻松解决在实际使用 Spark 时可能遇到的各种问题，快速恢复工作状态。 **课程亮点：** * **端到端的数据流管道构建：** 从蓝图架构到完整的代码解决方案，课程涵盖了数据流管道设计和开发的每一个重要环节。 * **Spark 作业的全面测试：** 掌握单元测试、集成测试和端到端测试技术，确保您的数据管道的稳健性和可靠性。 * **解决性能瓶颈：** 学习如何解决导致应用程序性能下降的慢速作业等棘手问题。 **作者简介：** * **Anghel Leonard：** Java 首席架构师，Java EE Guardians 成员，拥有 20 多年分布式系统架构经验，同时也是多本书籍的作者、演讲者，热衷于数据处理。 * **Tomasz Lelek：** 软件工程师，主要使用 Java 和 Scala 编程，拥有 5 年 Spark 和 ML API 使用经验，并有处理 PB 级数据的生产经验。热衷于软件开发，并推崇多角度解决问题。曾作为演讲嘉宾参加波兰的 Confitura、JDD（Java Developers Day）及 Krakow Scala User Group 的会议，并在 Geecon Conference 上进行了现场编码演示。是 e-learning 平台 initlearn 的联合创始人，并撰写了大量关于 Java 技术的文章。
Video Learning Path OverviewA Learning Path is a specially tailored course that brings together two or more different topics that lead you to achieve an end goal. Much thought goes into the selection of the assets for a Learning Path, and this is done through a complete understanding of the requirements to achieve a goal.Today, organizations have a difficult time working with large datasets. In addition, big data processing and analyzing need to be done in real time to gain valuable insights quickly. This is where data streaming and Spark come in.In this well thought out Learning Path, you will not only learn how to work with Spark to solve the problem of analyzing massive amounts of data for your organization, but you'll also learn how to tune it for performance. Beginning with a step by step approach, you'll get comfortable in using Spark and will learn how to implement some practical and proven techniques to improve particular aspects of programming and administration in Apache Spark. You'll be able to perform tasks and get the best out of your databases much faster.Moving further and accelerating the pace a bit, You'll learn some of the lesser known techniques to squeeze the best out of Spark and then you'll learn to overcome several problems you might come across when working with Spark, without having to break a sweat. The simple and practical solutions provided will get you back in action in no time at all!By the end of the course, you will be well versed in using Spark in your day to day projects.Key FeaturesFrom blueprint architecture to complete code solution, this course treats every important aspect involved in architecting and developing a data streaming pipelineTest Spark jobs using the unit, integration, and end-to-end techniques to make your data pipeline robust and bulletproof.Solve several painful issues like slow-running jobs that affect the performance of your application.Author BiosAnghel Leonard is currently a Java chief architect. He is a member of the Java EE Guardians with 20+ years' experience. He has spent most of his career architecting distributed systems. He is also the author of several books, a speaker, and a big fan of working with data.Tomasz Lelek is a Software Engineer, programming mostly in Java and Scala. He has been working with the Spark and ML APIs for the past 5 years with production experience in processing petabytes of data. He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. Recently he was a speaker at conferences in Poland, Confitura and JDD (Java Developers Day), and at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference. He is a co-founder of initlearn, an e-learning platform that was built with the Java language. He has also written articles about everything related to the Java world.
