Answer: storesDF.orderBy(col("division").desc())

Alphabetical order means **ascending** order (A → Z, default string sorting in Spark). **A: storesDF.sort(asc("division"))** This is **correct**. `sort()` accepts Column expressions. `asc("division")` explicitly creates an ascending sort order on the `division` column → alphabetical (A to Z) order. **B: storesDF.orderBy(["division"], ascending = [1])** This is **correct**. `orderBy()` (and `sort()`) accepts the `ascending` parameter as a list when sorting by multiple columns (or even one). In PySpark, `ascending=[1]` or `ascending=[True]` both mean **ascending** order (1 / True = ascending, 0 / False = descending). So this sorts `division` in ascending → alphabetical order. **C: storesDF.orderBy(col("division").desc())** This is **incorrect** (this is the one that does NOT give alphabetical/ascending order). `col("division").desc()` creates a **descending** sort order (Z → A). Therefore this returns the DataFrame sorted in **reverse alphabetical** order, not alphabetical (ascending) order. **D: storesDF.orderBy("division")** This is **correct**. When you pass column name(s) as string(s) to `orderBy()` without any other arguments, it sorts in **ascending** order by default. So `division` is sorted alphabetically (A to Z). **E: storesDF.sort("division")** This is **correct**. `sort()` behaves the same way as `orderBy()` (they are aliases). Passing a string column name without extra arguments → **ascending** order by default → alphabetical order. **Summary – which one does NOT sort alphabetically (ascending)?** Only option **C** uses `.desc()`, which forces **descending** order (reverse alphabetical). **Answer: C** `storesDF.orderBy(col("division").desc())` is the only option that sorts in **descending** (Z → A) instead of ascending (A → Z) order. This is a classic exam trap: knowing the **default sort direction** (ascending) and recognizing when `.desc()` or `ascending=False`/`0`/`[False]` is used to reverse it. Good luck with your Databricks Certified Associate Developer for Apache Spark preparation! Keep practicing these small but important API details.

Author: LeetQuiz Editorial Team