Mtds,Func,Trns,Wnd/Functions(Oprt at Column Level)/explode()

data = [
    (1, "Alice,Bob"),
    (2, "Charlie,Diana,Chris"),
    (3, "Edward,Francesca"),
    (4,"Harley")
]
schema = ["id", "name"]

df = spark.createDataFrame(data,schema)

df.show()

exploded_df = df.select(col("id"),explode(split(col("name"),",")).alias("Name"))

exploded_df.show()

+---+-------------------+
| id|               name|
+---+-------------------+
|  1|          Alice,Bob|
|  2|Charlie,Diana,Chris|
|  3|   Edward,Francesca|
|  4|             Harley|
+---+-------------------+

+---+---------+
| id|     Name|
+---+---------+
|  1|    Alice|
|  1|      Bob|
|  2|  Charlie|
|  2|    Diana|
|  2|    Chris|
|  3|   Edward|
|  3|Francesca|
|  4|   Harley|
+---+---------+

Spark SQL Solution: -

df.createOrReplaceTempView("names")

sql_query ="""
SELECT 
    id,
    EXPLODE(SPLIT(name, ',')) AS Name
FROM names
"""
result = spark.sql(sql_query)
result.show()