Deduplicate records, keep only the latest one

Same customer, two rows, two different timestamps.

Beginner to intermediateRead 6 minDoing: an hour7 steps

What you'll have at the end

One row per customer, verified by comparing row counts before and after

Before you start

You need

A raw PySpark DataFrame where the same real-world record appears more than once, each copy stamped with when it was captured or last changed.

Not covered

Stopping duplicates at the source system; here you only clean up what already landed in the table.

Leans on

7 steps

Implement a Type 2 slowly changing dimension as a PySpark job

When the business wants every past version of a record kept, build a Type 2 dimension there instead of dropping the older rows here.

Checked 25 Aug 2026