Spark Final Concepts | Optimization, Memory, AQE & Performance Tuning| DE Roadmap #25

In this session of the Data Engineering Course, we cover some of the most practical and interview-focused Spark concepts that help you understand real-world performance tuning.

🔹 What you will learn:

📌 Spark UI Deep Dive
- Understanding Jobs, Stages, and Tasks
- SQL tab and execution details
- How to debug issues using Spark UI

📌 Adaptive Query Execution (AQE)
- What is AQE?
- How Spark optimizes queries dynamically
- Handling skew joins and partition optimization

📌 Handling Slow Running Jobs
- Identifying bottlenecks
- Common reasons for slow jobs
- Debugging and optimization strategies

📌 Spark Application Configuration
- Executors, cores, and memory
- How to decide configurations
- Parallelism and performance tuning

📌 Real-world Example
- How to configure Spark for ~500MB data
- Practical understanding of resources

🎯 This session is important for:
- Data Engineering Interviews
- Spark performance tuning scenarios
- Real-world project optimization

📌 Previous sessions covered:
✔ Spark Architecture
✔ RDDs & DataFrames
✔ Advanced Spark Concepts

🚀 Next: Real-world Data Engineering Projects

👉 Subscribe for complete Data Engineering roadmap.

#Spark #DataEngineering #BigData #SparkUI #AQE #PerformanceTuning

Видео Spark Final Concepts | Optimization, Memory, AQE & Performance Tuning| DE Roadmap #25 канала PathNex - Shaping Careers