Data Engineering using Kafka and Spark Structured Streaming

📚 Data Engineering using Kafka and Spark Structured Streaming - Course Description

Are you ready to dive into the world of real-time data processing? 🚀 With this comprehensive course, you'll learn to build robust streaming pipelines using Apache Kafka and Apache Spark Structured Streaming. This is not just any ordinary course; it's a deep dive into integrating these powerful technologies to handle large-scale, high-velocity data in a scalable and efficient manner. 💧➡️⚡

Course Details 🔍

Setting Up the Environment: We kick off the course by getting your hands dirty with setting up a complete lab environment on a single-node Linux system. You'll have everything you need for this course—Hadoop, Hive, Spark, and Kafka—all running smoothly on your local machine. 🛠️💻

• Lab Environment Setup: Learn to configure a one-stop shop for your data engineering needs on a single node.
• Getting Started with Kafka: Begin with the basics of Kafka, from creating topics to producing and consuming messages.
• Kafka Connect Integration: Understand how to use Kafka Connect to ingest data streams from various sources, such as web server logs, into Kafka topics, and then move the processed data to HDFS as a sink.

Spark Structured Streaming Insights: Once you're comfortable with Kafka, we'll introduce you to key concepts in Spark Structured Streaming. You'll learn how to consume data from Kafka topics using Spark and then process that data to suit your targets—be it writing back to HDFS or another storage system. 🎥✨

• Kafka & Spark Integration: Learn the ins and outs of combining Kafka with Spark Structured Streaming for a powerful streaming pipeline.
• Incremental Data Processing: Master incremental loads with Spark Structured Streaming, ensuring your data processing remains efficient and up-to-date.

Course Outline 📐

The course is structured to guide you through each step with clarity and precision. Whether you choose to provision a server using AWS Cloud9 or Google Cloud Platform (GCP), you'll have the necessary tools at your fingertips. Here's what you can expect:

1. Provision Server & Set Up Environment: Choose between AWS Cloud9 or GCP for your development environment.
2. Single Node Hadoop Cluster Setup: Get familiar with the foundational platform for distributed computing.
3. Hive & Spark Configuration: Learn to configure and use Hive and Spark on top of your Hadoop cluster.
4. Kafka Setup on Hadoop Cluster: Integrate Kafka into your Hadoop setup for real-time data processing.
5. Kafka Basics & Data Ingestion: Dive into Kafka basics and master data ingestion from web server logs to Kafka topics, as well as outputting to HDFS.
6. Spark Structured Streaming Overview: Get to grips with Spark Structured Streaming capabilities.
7. Kafka & Spark Integration: Combine Kafka's data ingestion power with Spark's processing capabilities.
8. Incremental Loads with Spark Structured Streaming: Learn how to handle incremental data loads in a streaming context.

Support & Resources 🤝

You won't be alone on this journey! If you encounter any technical hurdles while taking the course, Udemy's support team is here to assist you. Reach out via Udemy Messenger, and we guarantee to resolve your issue within 48 hours. 🛠️🤓

Ready to become a data engineering pro with Kafka and Spark Structured Streaming? Enroll in this course today and transform the way you handle real-time data! 🎓🎉