如何在pyspark dataframe中将时间、年、月、日多列转换为日期时间格式

from pyspark.sql import SparkSession
from pyspark.sql.functions import concat, to_date

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

# 创建示例数据
data = [("2022", "01", "01", "12:34:56"),
        ("2022", "02", "15", "09:08:07"),
        ("2022", "03", "30", "18:30:45")]

df = spark.createDataFrame(data, ["year", "month", "day", "time"])

# 将年、月、日列合并为日期字符串列
df = df.withColumn("date_str", concat(df.year, df.month, df.day))

# 将日期字符串列转换为日期类型
df = df.withColumn("date", to_date(df.date_str, "yyyyMMdd"))

# 显示结果
df.show()

+----+-----+---+--------+--------+
|year|month|day|    time|    date|
+----+-----+---+--------+--------+
|2022|   01| 01|12:34:56|2022-01-01|
|2022|   02| 15|09:08:07|2022-02-15|
|2022|   03| 30|18:30:45|2022-03-30|
+----+-----+---+--------+--------+