How to Use approxQuantile() in PySpark | Quick Guide to Percentiles & Median #pysparktutorial

How to Use approxQuantile() in PySpark | Quick Guide to Percentiles & Median
📊 Learn how to use the approxQuantile() function in PySpark to calculate percentiles, medians, and other quantile statistics efficiently on large datasets. This function is ideal for big data scenarios where performance matters and full data scans are costly.

✅ What You’ll Learn:

How approxQuantile() works in PySpark

Calculate median and percentiles (25th, 50th, 75th, etc.) from large DataFrames

Understand the relativeError parameter for performance vs. accuracy

Real-world examples for data analysis and performance tuning

💡 Perfect for data engineers and analysts who want fast, memory-efficient quantile calculations on massive data.

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