Q22 — AWS DEA-C01 Ch.1

Question 22 of 100 | ← Chapter 1

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time Insights by using existing business intelligence (BI) and analytics tools. Which solution will meet these requirements with the LEAST operational overhead?

• A. Use Kinesis Data Streams to stage data in Amazon S3. Use the COPY command to load data from Amazon S3 directly into Amazon Redshift to make the data immediately available for real-time analysis.
• B. Access the data from Kinesis Data Streams by using SQL queries. Create materialized views directly on top of the stream. Refresh the Materialized views regularly to query the most recent stream data.
• C. Create an external schema in Amazon Redshift to map the data from Kinesis Data Streams to an Amazon Redshift object. Create a Materialized view to read data from the stream. Set the materialized view to auto refresh. ✓
• D. Connect Kinesis Data Streams to Amazon Kinesis Data Firehose. Use Kinesis Data Firehose to stage the data in Amazon S3. Use the COPY command to load the data from Amazon S3 to a table in Amazon Redshift.

Correct Answer: C. Create an external schema in Amazon Redshift to map the data from Kinesis Data Streams to an Amazon Redshift object. Create a Materialized view to read data from the stream. Set the materialized view to auto refresh.

Explanation

答案C是较优选择。创建AmazonRedshift的外部模式将KinesisDataStreams数据映射为对象，并创建自动刷新的物化视图，能以相对低的操作开销实现实时分析需求。A选项将数据暂存于S3再加载到Redshift增加了额外步骤和复杂性。B选项直接对KinesisDataStreams使用SQL查询并创建物化视图并定期刷新，可能在处理每秒数吉字节的大量流数据时存在性能和管理问题。D选项通过KinesisDataFirehose暂存数据到S3再加载到Redshift，流程较为繁琐。综上所述，C选项能以最少的操作开销满足需求，所以答案选C。