|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/overcoming-common-performance-issues-in-apache-spark/
课程评论：没有评论
课程名称：战胜Apache Spark中的常见性能问题 课程概述： Apache Spark是一个强大的框架，能够并行处理大规模数据集。然而，复杂的架构往往伴随着频繁的性能问题。在我的经验中，在线寻找能够清晰阐释Spark内部机制并解决这些问题的资源常常令人沮丧。因此，我创建了这门课程！这不是一个代码演练课程，而是针对已经掌握Spark编程的学员，讨论在开发过程中遇到的性能问题及其解决方案。我们将探讨相关理论，并提供可操作的步骤，以帮助你解决性能问题。 课程内容包括： - Apache Spark架构 - Apache Spark的部署模式 - Apache Spark任务的结构 - 如何处理Spark中的三大主要性能问题 如果你还未掌握Spark编程，欢迎参加我在Udemy上的60分钟PySpark速成课程。让我们一起探讨为何你的脚本表现不如预期，并共同解决性能问题！在这门课程结束后，Shuffle、Skew和Spill将不再是你需要担心的问题。
Spark is a powerful framework for processing large datasets in parallel. But, with the complex architecture come frequent performance issues.In my experience, it can be frustrating looking everywhere, trying to find a resource online that is worded in such a way that you fully understand the inner workings of Spark and how to address these issues. So, I created this course!This is not a code-along course. This course assumes you already know how to code in Spark. Here, we're talking about how you resolve the performance issues that you encounter during your development journey! We will walk through all of the theory & you'll have actionable steps to take to resolve your performance issues.In this course, we will cover off:The Apache Spark ArchitectureThe type of deployment modes in Apache SparkThe structure of jobs in Apache SparkHow to handle the three main performance concerns in SparkIf you don't yet know how to code in Spark, you can join my 60 minute crash course in PySpark, here on Udemy.Let's get to work understanding why your scripts are not performing as you may hope and resolve your performance issues together. Shuffle, Skew and Spill will be concerns of the past after this course!
