UdemyIT & SoftwarePaid courseIntermediate levelCertificate

Spark Performance Tuning for Data Engineers: Part1 - Storage (Udemy.com)

Data Engineering & Apache Spark Optimization Techniques on Databricks to Boost Speed, Reduce cost & Handle Big Data

4.7

49 reviews

Created by: S Santra

Last updated March 2026

What you will 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

How it compares

Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:

Rating4.7 out of 5higher than 86% of them
Reviews49#1,118 of 1,183 by number of reviews
Length3.4 hoursshorter than 67% of them
Last updatedMarch 2026more recently than 70% of them

Course Description

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)

Intermediate Level

Time: 3.4h

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Instructor Details

S Santra

4.7 Rating
49 Reviews

- Microsoft Certified Sr Data Engineer with expertise in Data Engineering /Data warehouse domain in designing an implementing solutions for ETL, reporting, analytics on Cloud such as MS Azure.

- Seasoned Data Engineering / Data warehouse professional having experience of 12+ years.

- International work experience at locations such as USA, Japan & India in Banking, Insurance & Shipping domain.