Level: Advanced — Author: Writix
Level: Advanced • Duration: 15 hours
Author: Writix
Unlock the power of real-time data processing with our comprehensive course on Spark Streaming - Stream Processing in Lakehouse using PySpark. This course dives deep into Apache Spark and Databricks, guiding you through the intricacies of stream processing within a Lakehouse architecture leveraging the Python programming language and the PySpark API. Through engaging practical examples and live coding sessions, you will master the implementation of real-time streaming solutions. The journey culminates in a hands-on End-To-End Capstone Project, where you’ll gain invaluable experience in project design, coding, implementation, testing, and Continuous Integration/Continuous Deployment (CI/CD) methodologies. All practices utilize the latest technologies, including Apache Spark 3.5 on Azure Databricks Cloud with Databricks Runtime 14.1. Join us now and transform your data processing skills for the modern world!
Duration: 15 hours
XP Points: 350
Participants: 0
- Data engineers looking to enhance their streaming skills. - Software developers wanting to integrate real-time data processing into applications. - Technical professionals interested in the Lakehouse architecture. - Students or enthusiasts eager to learn about Apache Spark and PySpark. - Anyone aiming to implement CI/CD in stream processing projects.