A step-by-step tutorial on building a real-time data streaming pipeline using Apache Airflow, Kafka, Spark, Cassandra, and Docker.
In this video, you will be building a real-time data streaming pipeline, covering each phase from data ingestion to processing and finally storage. We'll utilize a powerful stack of tools and technologies, including Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra—all neatly containerized using Docker.
MORE FREE COURSES: datamasterylab.com
📚 What You'll Learn:
👉 Setting up a data pipeline with Apache Airflow
👉 Streaming data with Kafka and Kafka Connect
👉 Using Zookeeper for distributed synchronization
👉 Data processing with Apache Spark
👉 Data storage solutions with Cassandra and PostgreSQL
👉 Containerizing your data engineering environment with Docker
✨ Timestamps: ✨
Introduction
System architecture
Getting data from API with Airflow
Docker Compose for the architecture
Streaming data into Kafka
Apache Spark and Cassandra setup
Streaming data into cassandra
Outro
👦🏻 My Linkedin: linkedin.com/in/yusuf-ganiyu-b90140107/
🚀 Twitter: twitter.com/YusufOGaniyu
📝 Medium: medium.com/@yusuf.ganiyu
🌟 Please LIKE ❤️ and SUBSCRIBE for more AMAZING content! 🌟
Like this video? Buy me a coffee ❤️ buymeacoffee.com/yusuf.ganiyu/
🔗 Useful Links and Resources:
✅ Code: github.com/airscholar/e2e-data-engineering.git
✅ Medium Article: medium.com/@yusuf.ganiyu/realtime-data-engineering-project-w…
✅ Docker Compose Documentation: docs.docker.com/compose/
✅ Apache Kafka Official Site: kafka.apache.org/
✅ Apache Spark Official Site: spark.apache.org/
✅ Apache Airflow Official Site: airflow.apache.org/
✅ Cassandra: cassandra.apache.org/
✅ Confluent Docs: docs.confluent.io/home/overview.html
✨ Tags ✨
Data Engineering, Apache Airflow, Kafka, Apache Spark, Cassandra, PostgreSQL, Zookeeper, Docker, Docker Compose, ETL Pipeline, Data Pipeline, Big Data, Streaming Data, Real-time Analytics, Kafka Connect, Spark Master, Spark Worker, Schema Registry, Control Center, Data Streaming
✨ Hashtags ✨
#confluent #DataEngineering #ApacheAirflow #Kafka #ApacheSpark #Cassandra #PostgreSQL #Docker #ETLPipeline #DataPipeline #StreamingData #RealTimeAnalytics
Why it's here
1 person recommends this
What people say. Recommended as a practical project tutorial for learning how to set up and integrate data engineering pipelines.
What's the quickest way to become skilled at debugging data pipelines?
I've been asked to debug a small data pipeline that is producing incorrect data. It's all running in a Linux environment and I'm expected to use Bash.
I'm curious how I can best prepare for such a task in advance, especially if I don't yet know what that data pipeline looks like?
I'm currently getting some practice with setting up data pipelines. I'm currently building a project from a YouTube tutorial to get my first experience with setting up a basic data pipeline.
Considering data engineering, and would appreciate some feedback on my planned method of breaking into the field
# Background
I'm in the US. I graduated back in 2021 with a bachelor's in math. I was soon hired at an AI startup and worked there as a solutions engineer. Essentially, my role meant I was the bridge between clients and the company's tech. That involved:
1. Building custom solutions for clients using the company's AI
2. Supporting the sales team with product demonstrations and technical presentations
3. Prototyping new features to expand out the company's AI product offerings
Most days involved me programming in Python, using and managing Docker containers, managing repos wi…
