How to Store Historical Data Much More Efficiently
A hands-on tutorial using PySpark to store up to only 0.01% of a DataFrame’s rows without losing any information.
Published in
10 min readSep 10, 2023
In an era where companies and organizations are collecting more data than ever before, datasets tend to accumulate millions of unnecessary rows that don’t contain any new or valuable…
