中This hands-on course equips learners with the skills to design, build, and manage end-to-end ETL (Extract, Transform, Load) workflows using Apache Spark in a real-world data engineering context. Structured into two comprehensive modules, the course begins with foundational setup, guiding learners through the installation of essential components such as PySpark, Hadoop, and MySQL. Participants will learn how to configure their environment, organize project structures, and explore source datasets effectively.
Apache Spark: Design & Execute ETL Pipelines Hands-On
您将学到什么
Install and configure PySpark, Hadoop, and MySQL for ETL workflows.
Build Spark applications for full and incremental data loads via JDBC.
Apply transformations, handle deployment issues, and optimize ETL pipelines.
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最近已更新！
August 2025
作业
6 项作业
授课语言：英语（English）
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本课程是 Spark and Python for Big Data with PySpark 专项课程 专项课程的一部分
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该课程共有2个模块
This module introduces learners to the fundamentals of building an ETL framework using Apache Spark. It begins by providing an overview of the Spark ecosystem and its advantages in big data processing. Learners will be guided through the installation and configuration of essential software packages, setting up the development environment, and understanding the structure of a Spark-based ETL project. The module also covers how to work with real-world datasets and prepare configuration files for database interactions—laying a strong groundwork for scalable data processing workflows.
涵盖的内容
5个视频3个作业
This module guides learners through the practical implementation of Extract, Transform, and Load (ETL) processes using Apache Spark. Learners will explore full data loads into MySQL, apply transformation logic using Spark SQL, and handle incremental loading scenarios by tracking and managing new records. The lessons include error handling, filtering strategies, data type compatibility, and database integration using JDBC—all within a hands-on PySpark environment. This module reinforces applied knowledge of Spark for real-world data engineering tasks.
涵盖的内容
6个视频3个作业
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