您可以在导入数据时使用aws_glue.Template.athena_cleanup函数删除无效的时间戳格式。以下是示例代码：

import datetime
import boto3
import json
import awswrangler as wr

# create a Glue job and define the data source and target
def glue_job():
    s3_paths = ["s3:///.csv"]
    catalogid = boto3.client("sts").get_caller_identity()["Account"]
    database = ""
    table_name = ""
    connect_options = {
        "dbtable": table_name,
        "database": database,
        "instance": "",
        "port": ,
        "user": "",
        "password": "",
        "ssl": "require",
    }
    redshift_options = {
        "database": "",
        "host": "",
        "port": ,
        "user": "",
        "password": "",
    }

    # read data from RDS to GlueDynamicFrame
    dyf_rds = wr.rds.read_sql_table(
        table=connect_options["dbtable"],
        database=connect_options["database"],
        instance=connect_options["instance"],
        port=connect_options["port"],
        secret_id="",
    )

    # prepare data for write to Redshift
    dyf_redshift = wr.sanitize_dataframe(
        dyf_rds.toDF(), remove_newline=True, remove_return=True
    )
    dyf_redshift = wr.cast_dataframe(
        dyf=dyf_redshift,
        column_type_mapping={
            "timestamp_column_name": "timestamp",  # replace with your timestamp column name
        },
    )

    # write data to Redshift using Glue
    wr.redshift.load(
        dataframe=dyf_redshift,
        table="",
        schema="",
        iam_role="",
        redshift_options=redshift_options,
        num_files=1,
        mode="overwrite