Data Engineering & Apache Spark Optimization Techniques on Databricks to Boost Speed, Reduce cost & Handle Big Data
Unlock the true potential of Apache Spark by mastering storage-related performance tuning techniques. This hands-on course is packed with real-world scenarios, guided demos, and practical use cases that will help you fine-tune Spark storage strategies for speed, efficiency, and scalability.
What you’ll learn
- Hands on Demo based on different Scenarios & Usecases.
- Learn the nuances of spark performance tuning.
- Get detailed insights about different operations in spark.
- Get clear understanding about how spark configs work hand in hand & best combination for optimal results.
- Learn to identify and solve bottlenecks & errors in your spark application.
Course Content
- Introduction –> 3 lectures • 18min.
- Important Concepts –> 5 lectures • 1hr 20min.
- Optimizing Storage –> 7 lectures • 1hr 45min.
Requirements
Unlock the true potential of Apache Spark by mastering storage-related performance tuning techniques. This hands-on course is packed with real-world scenarios, guided demos, and practical use cases that will help you fine-tune Spark storage strategies for speed, efficiency, and scalability.
This course is perfect for Intermediate Data Engineers & Spark Developers as well as Aspiring Achitects who wants to optimize Spark jobs, reduce resource costs, and ensure fast, reliable performance for large-scale data applications.
What You’ll Learn
1. Understand how Apache Spark handles storage internally: memory vs disk
2. Learn when and how to use Spark caching and persistence effectively
3. Compare and choose the right storage levels: MEMORY_ONLY, MEMORY_AND_DISK, etc.
4. Use real-world examples and hands-on demos to benchmark storage decisions
5. Learn how to monitor storage metrics using the Spark UI
6. Handle memory spills, disk I/O bottlenecks, and storage tuning in cluster environments
7. Apply best practices for storage optimization in cloud and on-prem Spark clusters
Why Take This Course?
- 100% Hands-on: Focused on practical implementation, not just theory
- Designed for Data Engineers, Spark Developers, and Big Data Practitioners
- Covers both foundational concepts and advanced tuning techniques
- Teaches how to measure performance gains using real metrics
- Helps you make cost-efficient decisions for big data storage
Tools & Technologies Covered
- Apache Spark (2.x and 3.x)
- DataBricks
- Spark UI
- HDFS, DataLake (for storage scenarios)