PySpark Mock Interview for Data Engineers | 7 Real Production Scenarios #bigdata #dataengineering

PySpark interview questions for data engineers explained in a mock interview style.

In this video, we cover 7 production-level PySpark scenarios that every data engineer should understand. These are not just syntax-based questions. These are real production problems around duplicate events, bad files, slow joins, schema changes, retries, incremental processing, and wrong outputs.

In this PySpark mock interview, we cover:

1. How to handle duplicate events after retry
2. How to process bad JSON records in production
3. How to optimize a slow join between a large fact table and small dimension table
4. When to use cache() or persist() for reused DataFrames
5. How to make a PySpark pipeline retry-safe and idempotent
6. How to handle schema changes in incoming data
7. How to avoid full reloads and build incremental processing

Main takeaway:

PySpark interviews are not only about syntax anymore.
Interviewers want to know whether you can think through real data engineering problems.

This video is useful for:
- Data engineering interviews
- PySpark interview preparation
- Spark interview preparation
- Databricks interview preparation
- Production data pipeline concepts
- Big data engineering scenarios

Watch One Data Engineering Project you need for real experience next :- https://youtu.be/VXb4x0vb1zo

Watch Real Data Engineering Interview Experiences here :- https://www.youtube.com/playlist?list=PLaN45q3P4DYQJVlMea8E4jZKmJKG0uycP

Comment PYSPARK if you want Part 2 with more production-level PySpark mock interview questions.

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Chapters:-

00:00 Why PySpark interviews are different now

00:27 Welcome to BigData Factory

00:47 Q1: Duplicate events after retry

01:48 Q2: Bad JSON records in production

02:49 Q3: Slow join with large fact and small dimension table

03:55 Q4: Same DataFrame used multiple times

05:03 Q5: Retry-safe PySpark pipeline

06:13 Q6: Schema change in incoming data

07:22 Q7: Incremental processing instead of full reload

08:31 Recap: 7 production PySpark scenarios

09:17 Outro and next PySpark mock interview

Видео PySpark Mock Interview for Data Engineers | 7 Real Production Scenarios #bigdata #dataengineering канала BigData Factory