通过Glue将CSV文件按非引号方式注入RDS

【以下的问题经过翻译处理】 我有一个由我的Glue Job生成的pyspark脚本，旨在从S3存储桶中的CSV文件中读取数据并将其写入我的SQL RDS表中。 在我的CSV文件中，我有多行字符串。 如果解析后字符串中引号被正常解析，则作业通过，但在我的情况下，多行字符串中的引号未被正确解析，因此作业无法将数据插入我的表中； 我尝试过：

spark.read.option("multiLine", "true").option("quoteChar", -1).option("header","true")

但它没有起作用。 我还尝试过：

 datasink5 = glueContext.write_dynamic_frame.from_options(
    frame = dynamic_frame_write,
    connection_type = "s3", 
    connection_options = {
        "path": "s3://mycsvFile"
        }, 
    format = "csv", 
    format_options={
        "quoteChar": -1, 
        "separator": ","
        }, 
    transformation_ctx = "datasink5")

但这将数据写回S3而不是我的RDS表。

这是我的Glue工作：

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.dynamicframe import DynamicFrame
from awsglue.job import Job
import pyspark.sql.functions as f

## @params: [JOB_NAME]
args = getResolvedOptions(sys.argv, ['JOB_NAME'])

sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
## spark.read.option("multiLine", "true").option("quoteChar", -1).option("header","true").option("escape","\'")
    
job = Job(glueContext)
job.init(args['JOB_NAME'], args)

def otherTreatment(dfa):
...
   return dfa

datasource0 = glueContext.create_dynamic_frame.from_catalog(database = "db_rds", table_name = "tbl_csv_extract", transformation_ctx = "datasource0")

applymapping1 = ApplyMapping.apply(frame = datasource0, mappings = [("id", "string", "id", "string"), ("created", "string", "created", "timestamp"), ("name", "string", "name", "string"), ("high", "string", "high", "decimal(22,7)")], transformation_ctx = "applymapping1")

selectfields2 = SelectFields.apply(frame = applymapping1, paths = ["created", "name", "high", "id"], transformation_ctx = "selectfields2")

resolvechoice3 = ResolveChoice.apply(frame = selectfields2, choice = "MATCH_CATALOG", database = "db_rds_sql", table_name = "tbl_teststring", transformation_ctx = "resolvechoice3")

resolvechoice4 = ResolveChoice.apply(frame = resolvechoice3, choice = "make_cols", transformation_ctx = "resolvechoice4")

data_frame = resolvechoice4.toDF()



data_frame = otherTreatment(data_frame)
dynamic_frame_write = DynamicFrame.fromDF(data_frame, glueContext, "dynamic_frame_write")
datasink5 = glueContext.write_dynamic_frame.from_catalog(frame = dynamic_frame_write, database = "db_rds_sql", table_name = "tbl_teststring", transformation_ctx = "datasink5")

## with the flowing script write output back to s3 not in my sql table
datasink5 = glueContext.write_dynamic_frame.from_options(
    frame = dynamic_frame_write,
    connection_type = "s3", 
    connection_options = {
        "path": "s3://mycsvFile"
        }, 
    format = "csv", 
    format_options={
        "quoteChar": -1, 
        "separator": ","
        }, 
    transformation_ctx = "datasink5")
    
job.commit()

请教大家：如何使用 Glue Pyspark 写入我的不带引号的多行 CSV 文件？