Amazon EMR (ACUS): Cluster Types

Which ACUS EMR cluster type is most suitable for scenarios requiring continuous data processing and long-term ETL pipelines?

In ACUS EMR, which storage option is ideal for storing temporary data that only needs to be accessed within the cluster?

When deploying ACUS EMR in an on-premises environment for hybrid cloud setups, which deployment option is most appropriate?

Which ACUS EMR feature allows you to automatically adjust the number of instances in a cluster based on the current workload demand?

Which storage component in ACUS EMR extends HDFS capabilities by utilizing Amazon S3 for durable and cost-effective external storage?

Which of the following ACUS EMR deployment options eliminates the need for cluster management by automatically provisioning resources as needed?

If cost savings are a top priority for your ACUS EMR workload and you can tolerate interruptions, which cluster type should you use?

What is the primary purpose of the Glue Data Catalog in an ACUS EMR environment?

Which ACUS EMR scaling option provides the most flexibility in terms of cost optimization by allowing you to use multiple instance types?

In ACUS EMR, if you require full customization and control over your cluster environment, which deployment option should you choose?

Which of these services serves as durable and cost-effective external storage for ACUS EMR?

For an ACUS EMR setup that involves running workloads in a containerized Kubernetes environment, which deployment option is most suitable?

What is a key advantage of using Auto-Scaling clusters in ACUS EMR?

In ACUS EMR deployments, when would you typically opt for 'Manual Scaling' over 'Auto-Scaling'?

Which deployment option would you choose if you needed to run ACUS EMR in a hybrid cloud setup, specifically on your own hardware located on-premises?

An organization wants to use ACUS EMR to process data with minimal operational overhead. Which deployment option is BEST suited for this?

Which storage option in ACUS EMR should be used for storing large datasets that need to be processed in parallel across many nodes?

Your ACUS EMR cluster needs additional storage that persists even when the cluster terminates. Which storage option should you implement?

In ACUS EMR, you need to optimize costs by using a mix of different EC2 instance types. Which option can allow you to achieve this?

For ACUS EMR, which cluster configuration is designed for short-term, ad-hoc queries like data exploration or proof-of-concept projects?