AWS Certified Data Analytics Specialty 2021 – Hands-On - Elastic MapReduce (EMR) Architecture and Usage

The video tutorial provides an in-depth look at Amazon EMR, a managed Hadoop framework on AWS. It covers the components of an EMR cluster, including master, core, and task nodes, and explains how to use task nodes and spot instances for cost efficiency. The tutorial also compares transient and long-running clusters, highlighting their use cases. Finally, it discusses how to interact with EMR using the AWS console and command line, offering flexibility in data processing and management.

What does EMR stand for in the context of AWS?

• Elastic Managed Resource

• Elastic MapReduce

• Elastic Machine Resource

• Efficient Map Resource

Which node type in an EMR cluster is responsible for managing the cluster and coordinating tasks?

• Master Node

• Task Node

• Data Node

• Core Node

What is a key advantage of using task nodes in an EMR cluster?

• They reduce the need for master nodes

• They are mandatory for all clusters

• They provide additional processing capacity without extra storage

• They store large amounts of data

What is a transient cluster in EMR?

• A cluster that runs indefinitely

• A cluster that automatically terminates after completing its tasks

• A cluster that requires manual shutdown

• A cluster that stores data permanently

How can you save costs when running a long-running EMR cluster?

• By using reserved instances

• By using on-demand instances

• By increasing storage capacity

• By using more master nodes

Which method allows you to interact with an EMR cluster using a graphical interface?

• Using the AWS console

• Using a third-party tool

• Direct connection to the master node

• SSH into the core node

What is the benefit of using the AWS console to submit steps to an EMR cluster?

• It provides more storage options

• It is faster than command line methods

• It allows for graphical step definition

• It requires no internet connection