If you’ve worked with Apache Spark, you’ve likely written transformations like filter(), map(), or select() and wondered, “How does Spark actually execute this under the hood?” The answer lies in logical and physical plans — two key steps Spark uses to turn your code into distributed computation efficiently. Understanding this will help you optimize performance... Continue Reading →
Pandas DataFrame vs. Spark DataFrame: Which One Should You Use & When?
Ever felt like your laptop’s about to take off while processing that “innocent” CSV file with 1 million rows? 😂Yep. You’re probably using Pandas, and it’s starting to sweat. That’s where Spark DataFrames come in — but wait, don’t ditch Pandas just yet!Let’s break it down. Think of it like this: Pandas is your reliable... Continue Reading →
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