Your company is using Spark on transient EMR clusters to perform complex transformations as series of steps on data in S3. The development team has observed that there are high network costs and slow performance for spark jobs. Which of the following technique will help us to improve the performance and optimize network cost?

Answer options:

A.Use memory-optimized instance type for Master Node
B.Use EMRFs consistent view
C.Use EMR security configuration
D.Use HDFS as a temporary data store for processing

Answer - Option D
Option A is incorrect: Using memory-optimized instance type for EMR master nodes will not help us 
improve performance and network cost in reading/writing data stored on S3 using spark
Option B is incorrect: Consistent view allows EMR clusters to check for a list and read-after-write consistency for Amazon S3 objects written by or synced with EMRFS. 
Consistent view addresses an issue that can arise due to the Amazon S3 Data Consistency Model.
https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-consistent-view.html
Option C is incorrect: SecurityConfiguration resource is used to configure data encryption, Kerberos 
authentication, and Amazon S3 authorization for EMRFS
Option D is correct: Use s3distcp to copy data from S3 to HDFS, apply complex transformations on HDFS data using 
spark and then copy the processed dataset back to S3