Q43 — AWS SAA-C03 第3章

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Q173.一家公司正在准备一个新的数据平台，该平台将从多个来源获取实时流数据.公司需要在将数据写入 Amazon S3 之前转换数据.公司需要能够使用 SQL 来查询转换后的数据.哪些解决方案将满足这些要求? （选择两个.）

正确答案: A. 使用 Amazon Kinesis Data Streams 流式传输数据.使用 Amazon Kinesis Data Analytics 转换数据.使用 Amazon Kinesis Data Firehose 将数据写入 Amazon S3.使用 Amazon Athena 从 Amazon S3 查询转换后的数据, B. 使用 Amazon Managed Streaming for Apache Kafka (Amazon MSK) 流式传输数据.使用 AWS Glue 转换数据并将数据写入 Amazon S3.使用 Amazon Athena 从 Amazon S3 查询转换后的数据

解析

To meet the requirement of ingesting real-time streaming data from multiple sources, transforming the data before writing it to Amazon S3, and querying the transformed data with SQL, a solutions architect should use Amazon Kinesis Data Streams or Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. AWS Glue or Amazon Kinesis Data Analytics can be used to transform the data, and then Amazon Kinesis Data Firehose can be used to write the data to Amazon S3. Finally, Amazon Athena can be used to query the transformed data from Amazon S3. Therefore, options A and B are correct.Option C suggests using AWS Database Migration Service (AWS DMS) to ingest the data, which is not designed for real-time streaming data ingestion. Amazon EMR is suggested for transforming the data and writing it to Amazon S3, but this approach is more complex than necessary and may not provide the same level of scalability and cost-effectiveness as using AWS Glue or Amazon Kinesis Data Analytics.Option D suggests using Amazon Kinesis Data Analytics to transform the data and Amazon RDS query editor to query the transformed data from Amazon S3. While this approach could work, using Amazon RDS would add an unnecessary layer of complexity to the solution and may not provide the same level of scalability and cost-effectiveness as using Amazon Athena.Option E suggests using AWS Glue to transform the data and the Amazon RDS query editor to query the transformed data from Amazon S3. Again, using Amazon RDS would add an unnecessary layer of complexity to the solution and may not provide the same level of scalability and cost-effectiveness as using Amazon Athena.Using Amazon Kinesis Data Streams or Amazon MSK provides a highly scalable and durable solution for ingesting real-time streaming data. AWS Glue or Amazon Kinesis Data Analytics can be used to transform the data before writing it to Amazon S3 with Amazon Kinesis Data Firehose. Finally, Amazon Athena can be used to query the transformed data with SQL, providing a cost-effe为了满足从多个来源摄取实时流数据的需求，在将数据写入Amazon S3之前对其进行转换，并用SQL查询转换后的数据，解决方案架构师应该使用Amazon Kinesis data Streams或Amazon Managed streaming for Apache Kafka (Amazon MSK)来对数据进行流处理。可以使用AWS Glue或Amazon Kinesis Data Analytics对数据进行转换，然后使用Amazon Kinesis Data Firehose将数据写入Amazon S3。最后，可以使用Amazon Athena查询来自Amazon S3的转换后的数据。因此选项A和B是正确的。选项C建议使用AWS数据库迁移服务(AWS DMS)来摄取数据，该服务不是为实时流数据摄取而设计的。建议使用Amazon EMR转换数据并将其写入Amazon S3，但这种方法过于复杂，可能无法提供与使用AWS Glue或Amazon Kinesis data Analytics相同的可伸缩性和成本效益。选项D建议使用Amazon Kinesis Data Analytics转换数据，并使用Amazon RDS查询编辑器从Amazon S3查询转换后的数据。虽然这种方法可以工作，但使用Amazon RDS会给解决方案增加不必要的复杂性，并且可能无法提供与使用Amazon Athena相同级别的可伸缩性和成本效益。选项E建议使用AWS Glue转换数据，并使用Amazon RDS查询编辑器从Amazon S3查询转换后的数据。同样，使用Amazon RDS会给解决方案增加不必要的复杂性，并且可能无法提供与使用Amazon Athena相同级别的可伸缩性和成本效益。使用Amazon Kinesis Data Streams或Amazon MSK为摄取实时流数据提供了高度可扩展和持久的解决方案。在将数据写入Amazon S3之前，可以使用AWS Glue或Amazon Kinesis Data Analytics对数据进行转换。最后，Amazon Athena可用于用SQL查询转换后的数据，从而降低了成本