text: import sys
  import boto3
  from awsglue.transforms import *
  from awsglue.utils import getResolvedOptions
  from pyspark.context import SparkContext
  from awsglue.context import GlueContext
  from awsglue.job import Job
  
  glue_client = boto3.client('glue', region_name='sa-east-1')
  
  # @params: [JOB_NAME]
  args = getResolvedOptions(sys.argv, ['WORKFLOW_NAME', 'WORKFLOW_RUN_ID', 'JOB_NAME'])
  workflow_name = args['WORKFLOW_NAME']
  workflow_run_id = args['WORKFLOW_RUN_ID']
  
  workflow_params = glue_client.get_workflow_run_properties(
      Name=workflow_name,
      RunId=workflow_run_id
  )["RunProperties"]
  
  print("Params= ", workflow_params)
  
  sc = SparkContext()
  glueContext = GlueContext(sc)
  spark = glueContext.spark_session
  job = Job(glueContext)
  job.init(args['JOB_NAME'], args)
  
  df = spark.sql("show databases")
  df.show()
  
  path_in = "s3://bucket-raw-training-2021/staging/" + workflow_params['fileName']
  df = spark.read.format("csv").option("delimiter",",").option("header","true").load(path_in)
  df.show()
  
  path_out = "s3://bucket-datas-training-2021/raw/" + workflow_params['fileName'].split(".")[0] + "/"
  df.write.format("parquet").mode("overwrite").save(path_out)
  
  job.commit()
  