MLA-C01 Question 8
Select 2You are working on a machine learning project for a retail company that processes large volumes of transactional data in near real-time. The data needs to be ingested and stored in a way that supports both streaming and batch processing for training your machine learning models. Which of the following services or configurations would best meet these requirements?
- A
Use Amazon Kinesis Data Streams to ingest streaming data and store it in Amazon S3 for batch processing.
- B
Ingest the data directly into an Amazon RDS database for both real-time and batch processing.
- C
Use AWS Glue to continuously transform and load streaming data into Amazon Redshift for analytics queries.
- D
Leverage Amazon Managed Streaming for Apache Kafka (Amazon MSK) for real-time ingestion and periodic storage in Amazon S3.
- E
Use Amazon Elasticsearch Service to ingest and store the data for both real-time and batch processing.
Show answer and explanation
Correct answers: A, D
Explanation
For a machine learning use case that requires both real-time ingestion and batch processing, using Amazon Kinesis Data Streams or Amazon MSK for ingestion provides robust and scalable solutions. Storing the data in Amazon S3 enables cost-effective batch processing, which is commonly used for training machine learning models. These services are purpose-built for handling high-volume streaming data and complement each other well in this scenario.
- A. Correct.
Amazon Kinesis Data Streams is designed for real-time ingestion of streaming data. By storing this data in Amazon S3, you enable cost-effective batch processing for machine learning workflows.
- B. Incorrect.
Amazon RDS is not an optimal solution for ingesting high-velocity streaming data. It is better suited for structured data and transactional workloads, not for large-scale real-time ingestion.
- C. Incorrect.
AWS Glue is primarily used for ETL processes and does not natively support real-time ingestion of streaming data. It is better suited for batch data transformations.
- D. Correct.
Amazon MSK is a managed service for Apache Kafka, which is designed for processing streaming data in real-time. Periodically storing the data in Amazon S3 allows for batch processing, making it an excellent solution for this use case.
- E. Incorrect.
Amazon Elasticsearch Service is designed for search and log analytics, not for storing large-scale streaming data or supporting batch processing for machine learning workflows.