在PySpark中使用日期滚动连接？

from pyspark.sql import SparkSession
from pyspark.sql.functions import lag
from pyspark.sql.window import Window

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

# 创建示例数据集
data = [(1, '2022-01-01', 10),
        (2, '2022-01-02', 20),
        (3, '2022-01-03', 30),
        (4, '2022-01-04', 40),
        (5, '2022-01-05', 50)]

df = spark.createDataFrame(data, ['id', 'date', 'value'])

# 将日期列转换为日期类型
df = df.withColumn('date', df['date'].cast('date'))

# 定义滚动窗口
window = Window.orderBy('date')

# 使用lag函数进行日期滚动连接
df = df.withColumn('previous_value', lag(df['value']).over(window))

# 显示结果
df.show()