DEA-C01 Question 133
Select 3You are working as a Data Engineer for a company that processes large-scale sensor data from IoT devices. Your team wants to implement a distributed computing solution to handle this data efficiently. Which of the following AWS services are best suited for distributed computing and processing large-scale data workloads?
- A
AWS EMR (Elastic MapReduce)
- B
AWS Lambda
- C
Amazon Redshift
- D
AWS Glue
- E
Amazon Elasticsearch Service (Amazon OpenSearch Service)
Show answer and explanation
Correct answers: A, B, D
Explanation
AWS EMR, AWS Lambda, and AWS Glue are all services that can be leveraged for distributed computing in different capacities. AWS EMR provides a robust Hadoop/Spark-based platform for heavy distributed data processing. AWS Lambda can process data in parallel and is suitable for event-driven distributed architectures. AWS Glue uses Apache Spark for distributed data integration and ETL tasks. In contrast, Amazon Redshift is a data warehousing solution optimized for analytics, and Amazon Elasticsearch Service (OpenSearch Service) is designed for search and analytics use cases rather than distributed computing.
- A. Correct.
AWS EMR is a managed Hadoop framework that is designed for distributed computing tasks, making it ideal for processing large-scale data workloads.
- B. Correct.
AWS Lambda can be used to process data in parallel and is often part of a distributed computing architecture, especially for event-driven workloads.
- C. Incorrect.
Amazon Redshift is a data warehouse service optimized for analytics, not for distributed computing tasks focused on processing raw data at scale.
- D. Correct.
AWS Glue is a serverless data integration service that supports distributed data processing using Apache Spark under the hood.
- E. Incorrect.
Amazon Elasticsearch Service (OpenSearch Service) is primarily used for search and analytics, not for distributed computing workloads like processing large-scale sensor data.