Read a table from "Snowflake on AWS" using Spark in Windows PC

TestSnowflakeConnection.scala

package com.vvgsrk.data

import org.apache.spark.sql.SparkSession
import net.snowflake.spark.snowflake.Utils.SNOWFLAKE_SOURCE_NAME

/** This object test "snowflake on AWS" connection using spark
 *  from Eclipse, Windows PC.
 *
 * It uses Hadoop 2.7, Spark 2.3.2
 *
 *  @author  vvgsrk  
 *  
 */
object TestSnowflakeConnection extends App {
  
  // Frankfurt only have v4 authentication
  System.setProperty("com.amazonaws.services.s3.enableV4", "true")  
  
  // SparkSession and configurations
  val spark = SparkSession.builder()
     .master("local[*]")
     .appName("TestSnowflakeConnection")  
     .config("spark.ui.enabled", "false")
     .getOrCreate()
     
     // Set AWS S3 configurations
     spark.sparkContext.hadoopConfiguration.set("fs.s3a.access.key", "YOUR_KEY")
     spark.sparkContext.hadoopConfiguration.set("fs.s3a.secret.key", "YOUR_SECRET_KEY")
     spark.sparkContext.hadoopConfiguration.set("fs.s3a.endpoint", "s3-eu-central-1.amazonaws.com") 
     spark.sparkContext.hadoopConfiguration.set("spark.hadoop.fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
    
    // Snowflake Settings
    val sfOptions = Map(
      "sfURL" -> "vvgsrk.eu-central-1.snowflakecomputing.com",
      "sfAccount" -> "vvgsrk",
      "sfUser" -> "vvgsrk",
      "sfPassword" -> "YOUR_PWD",
      "sfDatabase" -> "HR_DEV",
      "sfSchema" -> "HR",
      "sfWarehouse" -> "HR_WH_DEV",
      "sfRole" -> "DEVELOPERS",
      "region_id"-> "eu-central-1",
      "tempdir" -> "s3a://vvgsrk-snowflake-data-temp"  // Make sure the tempdir option uses s3a:// 
    )
    
    // Read data as dataframe
    val df = spark.read
      .format(SNOWFLAKE_SOURCE_NAME)
      .options(sfOptions)
      .option("dbtable", "EMP")
      .load()
  
    df.printSchema()
  
    df.show(false)
  
}