Table of Contents
Question
A company is collecting a large amount of data from a fleet of IoT devices. Data is stored as Optimized Row Columnar (ORC) files in the Hadoop Distributed File System (HDFS) on a persistent Amazon EMR cluster. The company’s data analytics team queries the data by using SQL in Apache Presto deployed on the same EMR cluster. Queries scan large amounts of data, always run for less than 15 minutes, and run only between 5 PM and 10 PM.
The company is concerned about the high cost associated with the current solution. A solutions architect must propose the most cost-effective solution that will allow SQL data queries. Which solution will meet these requirements?
A. Store data in Amazon S3. Use Amazon Redshift Spectrum to query data.
B. Store data in Amazon S3. Use the AWS Glue Data Catalog and Amazon Athena to query data.
C. Store data in EMR File System (EMRFS). Use Presto in Amazon EMR to query data.
D. Store data in Amazon Redshift. Use Amazon Redshift to query data.
Answer
B. Store data in Amazon S3. Use the AWS Glue Data Catalog and Amazon Athena to query data.
Explanation
The correct answer is B. Store data in Amazon S3. Use the AWS Glue Data Catalog and Amazon Athena to query data.
The reason is that Amazon S3 is a cost-effective and durable storage service that can store large amounts of data in any format. AWS Glue Data Catalog is a managed service that creates and maintains a metadata repository for data stored in S3. Amazon Athena is a serverless interactive query service that allows users to analyze data in S3 using standard SQL. By using these services, the company can reduce the cost of running a persistent EMR cluster and Presto, and only pay for the queries they run. Additionally, Athena can read ORC files natively, which improves performance and reduces data scanned.
Option A is incorrect because Amazon Redshift Spectrum is a feature of Amazon Redshift that allows users to query data in S3 using the Redshift query engine. However, this option requires the company to have a Redshift cluster, which is more expensive than Athena.
Option C is incorrect because EMRFS is a file system implementation for EMR clusters that allows them to access data in S3 as if it were a local file system. However, this option still requires the company to have a persistent EMR cluster and Presto, which is not cost-effective.
Option D is incorrect because Amazon Redshift is a data warehouse service that allows users to store and query structured and semi-structured data using SQL. However, this option requires the company to load the data from S3 into Redshift, which adds complexity and cost. Moreover, Redshift does not support ORC files natively, which means the company would have to convert the data to a different format.
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