Q28 — AWS DEA-C01 Ch.1

Question 28 of 100 | ← Chapter 1

A data engineer must manage the ingestion of real-time streaming data into AWS. The data engineer wants to perform real-time analytics on The incoming streaming data by using time-based aggregations over a window of up to 30 minutes. The data engineer needs a solution that is Highly fault tolerant. Which solution will meet these requirements with the LEAST operational overhead?

• A. Use an AWS Lambda function that includes both the business and the analytics logic to perform time-based aggregations over a Window of up to 30 minutes for the data in Amazon Kinesis Data Streams.
• B. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data that might Occasionally contain duplicates by using multiple types of aggregations.
• C. Use an AWS Lambda function that includes both the business and the analytics logic to perform aggregations for a tumbling window of Up to 30 minutes, based on the event timestamp.
• D. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data by using Multiple types of aggregations to perform time-based analytics over a window of up to 30 minutes. ✓

Correct Answer: D. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data by using Multiple types of aggregations to perform time-based analytics over a window of up to 30 minutes.

Explanation

AmazonManagedServiceforApacheFlink（之前称为AmazonKinesisDataAnalytics）专为处理实时流数据的分析而设计，具有高度的容错性和可扩展性。对于需要在长达30分钟的窗口内进行基于时间的聚合以执行实时分析的需求，它能够很好地满足，并且相较于AWSLambda函数，ManagedServiceforApacheFlink在处理大规模实时流数据时具有更低的运营开销和更高的效率。因此，选项D是正确的答案。