如何使用udf将空列添加到Spark中的复杂数组结构

from pyspark.sql import SparkSession
from pyspark.sql.functions import udf
from pyspark.sql.types import ArrayType, StringType

spark = SparkSession.builder.appName("AddEmptyColumn").getOrCreate()

def add_empty_column(arr):
    arr.append(None)
    return arr

add_empty_column_udf = udf(add_empty_column, ArrayType(StringType()))

data = [("Alice", [1, 2, 3]), ("Bob", [4, 5])]
df = spark.createDataFrame(data, ["name", "numbers"])
df.show()

+-----+---------+
| name|  numbers|
+-----+---------+
|Alice|[1, 2, 3]|
|  Bob|   [4, 5]|
+-----+---------+

df_with_empty_column = df.withColumn("numbers_with_empty", add_empty_column_udf(df["numbers"]))
df_with_empty_column.show()

+-----+---------+------------------+
| name|  numbers|numbers_with_empty|
+-----+---------+------------------+
|Alice|[1, 2, 3]|     [1, 2, 3, null]|
|  Bob|   [4, 5]|        [4, 5, null]|
+-----+---------+------------------+