Why it matters

PySpark performance often overlooked. Understanding shapes fast PySpark.

Advertisement

The architecture

Row UDF: slow (Python per row).

Pandas UDF: vectorized (batch of pandas).

Prefer SQL/DataFrame ops over UDF.

PySpark perf tiersRow UDFslow per-row PythonPandas UDFvectorized batchesSQL / DataFrameno Python overheadArrow-based Python ↔ JVM data transfer critical
PySpark performance.
Advertisement

How it works end to end

Arrow: efficient Python ↔ JVM serialization.

Pandas UDFs: available since Spark 2.3; improved in 3.x.

Native ops preferred: filter, select, groupBy, join.