如何在PySpark中合并两个数据帧，其中输出数据帧具有来自每个输入数据帧的交替行？

from pyspark.sql import SparkSession
from pyspark.sql.functions import monotonically_increasing_id

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 创建两个示例数据帧
df1 = spark.createDataFrame([(1, 'A'), (2, 'B'), (3, 'C')], ['id', 'value'])
df2 = spark.createDataFrame([(4, 'D'), (5, 'E'), (6, 'F')], ['id', 'value'])

# 给每个数据帧添加一个自增列
df1 = df1.withColumn("index", monotonically_increasing_id())
df2 = df2.withColumn("index", monotonically_increasing_id())

# 合并数据帧，并按照自增列排序
merged_df = df1.unionAll(df2).orderBy("index")

# 移除自增列
merged_df = merged_df.drop("index")

# 打印结果
merged_df.show()