**Implementation**: Use `when`/`otherwise` with modulo—each row gets non-null in one column.
```python
from pyspark.sql.functions import when, col, lit
df = df.withColumn("even", when(col("num") % 2 == 0, col("num")).otherwise(lit(None)))
.withColumn("odd", when(col("num") % 2 != 0, col("num")).otherwise(lit(None)))
```
**Why This Approach**: Single pass; no shuffle; Catalyst optimizes the expressions....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like KPMG. The answer also includes follow-up discussion points that interviewers commonly explore.
Continue Reading the Full Answer
Unlock the complete expert answer with code examples, trade-offs, and pro tips - plus 1,863+ more.
According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.