Apache Spark — 1:1 Live Session (2 Hours)
If you've been hearing about Apache Spark everywhere but don't know where to start — this session is built for you.
In just 2 focused hours, we'll go from the very basics of how data was processed before Spark existed, all the way to understanding how Spark handles memory, optimises performance, and processes data at scale — the concepts that actually come up in interviews and on the job.
This isn't a recorded video or a group class. It's a private, 1:1 live session — meaning we go at your pace, you can ask anything without hesitation, and the session adapts to your background on the spot, whether you're from a Java background, a Python developer, or completely new to data engineering.
What you'll learn in 2 hours:
- How data was processed before Spark — and why Spark changed everything
- Distributed computing demystified — Hadoop MapReduce vs Spark, explained simply
- Spark internals — memory architecture, components, and how the engine actually works
- PySpark and Spark SQL fundamentals — writing your first transformations
- Jobs, Stages, Tasks, Shuffle — understanding what happens under the hood
- Narrow vs wide transformations — and why it matters for performance
- Cluster configuration basics — what the settings mean and how to choose them
Prerequisites:
Basic familiarity with Python is helpful but not mandatory. No prior Spark or data engineering experience needed.
Why this session is over YouTube or Udemy;
- You're not alone in a crowd — it's just you and me for 2 full hours. Ask anything.
- Live coding, not slides — we write and run real code together during the session
- Interview-articulation focus — I won't just explain concepts, I'll help you say them the way interviewers want to hear them
- Hands-on instructor — I use Apache Spark daily in production at one of the top MNCs. What I teach is what actually works.
What you get (beyond the session):
25- 40 questions quiz sent immediately after the session to test and cement your understanding.