spark cassandra intelliJ scala - scala

Question

Environment:
My Laptop:
IntelliJ IDEA 2017.1.4
JRE: 1.8.0_112-release-736-b21 x86_64
JVM: OpenJDK 64-Bit Server VM by JetBrains s.r.o
Mac OS X 10.12.2
IP Address: 192.168.3.203
AWS Environment:
Linux ip-172-31-16-45 x86_64 x86_64 GNU/Linux
DSE Version : 5.1.0
IP Address: 172.31.16.45
PUBLIC IP: 35.35.42.42
Ecexuted the following commands:
[ec2-user#ip-172-31-16-45 ~]$ dse cassandra -k
and then
[ec2-user#ip-172-31-16-45 ~]$ dse spark
The log file is at /home/ec2-user/.spark-shell.log
warning: there was one deprecation warning; re-run with -deprecation for details
New Spark Session
WARN 2017-09-13 13:18:26,907 org.apache.spark.SparkContext: Use an existing SparkContext, some configuration may not take effect.
Extracting Spark Context
Extracting SqlContext
Spark context Web UI available at http://172.31.16.45:4040
Spark context available as 'sc' (master = dse://?, app id = app-20170913131826-0001).
Spark session available as 'spark'.
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_112)
Type in expressions to have them evaluated.
Type :help for more information.
scala>
Spark Version: 2.0.2.6 ( One I see on Web Browser when I open http://35.35.42.42:4040/executors/)
Both Spark and Cassandra database are running on 35.35.42.42(public IP) or (Local IP: 172.31.16.45)
When I continue coding from scala env on AWS my code is running fine. What I need is to run the same code from intelliJ . Is it possible. If not what is the process.
Now I opened IntelliJ on my laptop and tried running below code:
// In .setMaster I tried all - .setMaster ("all combinations of local IP, public IP, spark, dse etc")
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
import com.datastax.spark.connector._
object helloworld {
def main(args: Array[String]) {
val conf = new SparkConf().setAppName("Simple Application").setMaster("dse://35.35.42.42:4040")
// val conf = new SparkConf().setAppName("Simple Application").setMaster("spark://172.31.16.45:4040")
// val conf = new SparkConf().setAppName("Simple Application").setMaster("spark://35.35.42.42:7077")
val conf = new SparkConf().setAppName("Simple Application").setMaster("spark://172.31.16.45:7077")
val sc = new SparkContext(conf)
// val rdd = sc.cassandraTable("tdata", "map")
}
}
Error:
org.apache.spark.SparkException: Could not parse Master URL: 'dse://35.35.42.42:4040'