如何从PySpark中一个DataFrames的每一行生成大量的DataFrame集合，然后将其缩减？

from pyspark.sql import SparkSession, Row
from pyspark.sql.functions import explode

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

data = [("Alice", 25), ("Bob", 30), ("Charlie", 35)]
df = spark.createDataFrame(data, ["Name", "Age"])

df_exploded = df.select("Name", explode("Age").alias("Exploded_Age"))

from pyspark.sql import SparkSession, Row
from pyspark.sql.functions import explode

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

data = [("Alice", 25), ("Bob", 30), ("Charlie", 35)]
df = spark.createDataFrame(data, ["Name", "Age"])

df_exploded = df.select("Name", explode("Age").alias("Exploded_Age"))

# 缩减生成的DataFrame集合，例如筛选Name为"Alice"的行
df_reduced = df_exploded.filter(df_exploded.Name == "Alice")

df_reduced.show()