为什么Spark无法识别这种时间格式？

from pyspark.sql import SparkSession
from pyspark.sql.functions import to_timestamp

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

# 假设你的数据在一个 DataFrame 中，列名为 "timestamp_col"
df = spark.read.csv("path_to_your_file.csv", header=True)

# 指定时间格式并转换
df = df.withColumn("timestamp_col", to_timestamp(df["timestamp_col"], "yyyy-MM-dd HH:mm:ss"))

df.show()

from pyspark.sql.functions import regexp_replace

# 假设不规范的时间格式是 "yyyy/MM/dd HH:mm:ss"
df = df.withColumn("timestamp_col", regexp_replace(df["timestamp_col"], "\\/", "-"))

df = df.withColumn("timestamp_col", to_timestamp(df["timestamp_col"], "yyyy-MM-dd HH:mm:ss"))

df.show()

from pyspark.sql.functions import udf
from pyspark.sql.types import TimestampType
from datetime import datetime

def custom_parser(date_str):
    return datetime.strptime(date_str, "your_custom_format")

custom_parser_udf = udf(custom_parser, TimestampType())

df = df.withColumn("timestamp_col", custom_parser_udf(df["timestamp_col"]))

df.show()