How to Remove Duplicate Records in PySpark | Window Function | row num function | Real-World Example
In this video, you’ll learn how to remove duplicate records in PySpark using Databricks, explained with a real-world transaction dataset.
Duplicate data is one of the most common problems in data engineering projects, especially when dealing with transactional systems, payment data, and order processing pipelines.
✅ What you will learn in this video:
How dropDuplicates() works in PySpark
Removing duplicates using single and multiple key columns
Using window functions to keep the latest record
Applying business logic deduplication using status priority
Real-world use cases from e-commerce & finance
PySpark deduplication interview tips
This tutorial is perfect for:
Data Engineers
PySpark & Databricks learners
Azure Databricks professionals
Interview preparation
📌 Dataset Used: Transaction data with duplicate order records
📌 Platform: Databricks + PySpark
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resource source -
https://github.com/dataworldsolution/...
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#PySparkTutorial #RemoveDuplicates #WindowFunctions