如何实现自定义的Pyspark分解(用于结构数组)，1个分解中有4列？

from pyspark.sql import SparkSession
from pyspark.sql.functions import col, explode
from pyspark.sql.types import StructType, StructField, StringType, IntegerType

spark = SparkSession.builder.appName("Custom Pyspark Decompose").getOrCreate()

data = [("A", [("a1", 1), ("a2", 2), ("a3", 3)]),
        ("B", [("b1", 4), ("b2", 5), ("b3", 6)])]
df = spark.createDataFrame(data, ["col1", "col2"])

def custom_decompose(array_col):
    result = []
    for item in array_col:
        result.append((item[0], item[1]))
    return result

spark.udf.register("custom_decompose", custom_decompose, ArrayType(StructType([
    StructField("col3", StringType()),
    StructField("col4", IntegerType())
]))))

df = df.withColumn("decomposed_col", explode(expr("custom_decompose(col2)")))

df = df.select("col1", "decomposed_col.col3", "decomposed_col.col4")