如何在Scala中从S3文件创建动态数据框？

import org.apache.spark.sql.{DataFrame, SparkSession}
import org.apache.hadoop.fs.{FileSystem, Path}
import com.amazonaws.auth.{AWSStaticCredentialsProvider, BasicAWSCredentials}
import com.amazonaws.services.s3.AmazonS3ClientBuilder

val accessKey = "Your_AWS_Access_Key"
val secretKey = "Your_AWS_Secret_Key"
val region = "Your_AWS_Region"
val credentials = new BasicAWSCredentials(accessKey, secretKey)
val s3Client = AmazonS3ClientBuilder.standard()
  .withCredentials(new AWSStaticCredentialsProvider(credentials))
  .withRegion(region)
  .build()

val s3Bucket = "Your_S3_Bucket_Name"
val s3FilePath = "Your_S3_File_Path"
val localTempDir = "Your_Local_Temp_Directory_Path"
val localFilePath = localTempDir + "/temp_file.csv"

val fs = FileSystem.get(sparkSession.sparkContext.hadoopConfiguration)
fs.copyToLocalFile(new Path(s"s3a://$s3Bucket/$s3FilePath"), new Path(localFilePath))

val spark = SparkSession.builder().getOrCreate()
val dynamicDataFrame = spark.read
  .format("csv")
  .option("header", "true")
  .option("inferSchema", "true")
  .load(localFilePath)