A team is building an EMR Cluster in AWS. They have their own implementations of the Mapper and Reducer functions developed in python that must be used for the Input data. How would you use this in the EMR Cluster?

Answer options:

A.Create a step for the EMR Cluster
B.Use a custom AMI for the cluster
C.Submit the code to AWS Lambda
D.Submit a job via AWS Data Pipeline

Answer – A
This is mentioned in the AWS Documentation
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Submit a Streaming Step
This section covers the basics of submitting a Streaming step to a cluster. A Streaming application reads input from standard input and then runs a script or executable (called a mapper) against each input. The result from each of the inputs is saved locally, typically on a Hadoop Distributed File System (HDFS) partition. After all the input is processed by the mapper, a second script or executable (called a reducer) processes the mapper results. The results from the reducer are sent to standard output. You can chain together a series of Streaming steps, where the output of one step becomes the input of another step.
The mapper and the reducer can each be referenced as a file or you can supply a Java class. You can implement the mapper and reducer in any of the supported languages, including Ruby, Perl, Python, PHP, or Bash.
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Option B is incorrect since this is used if you want a custom image for the nodes in your cluster
Options C and D are incorrect since the ideal approach is to use the inbuilt step functionality
For more information on creating a streaming step, please refer to the below URL
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/CLI_CreateStreaming.html