How do we compute total row volume and column count in a distributed DataFrame?
Combining the count() distributed action with the len(df.columns) metadata property to audit table dimensions.
Validating data completeness after ingestion and logging pipeline metrics before downstream publishing.
total_rows = df.count()
total_cols = len(df.columns)
print(f"Rows: {total_rows}, Columns: {total_cols}")Practice typing production-grade PySpark code for DataFrame Dimensions & Structure Inspection.