DAS-C01 · Question #57
A company is planning to create a data lake in Amazon S3. The company wants to create tiered storage based on access patterns and cost objectives. The solution must include support for JDBC…
The correct answer is A. AWS Glue Data Catalog for metadata management C. AWS Glue for Scala-based ETL E. Amazon Athena for querying data in Amazon S3 using JDBC drivers. The three requirements map directly to three services: (A) AWS Glue Data Catalog provides centralized metadata management and supports federation for access control via Lake Formation and IAM - fully managed with no servers to run. (C) AWS Glue natively supports both PySpark…
Question
A company is planning to create a data lake in Amazon S3. The company wants to create tiered storage based on access patterns and cost objectives. The solution must include support for JDBC connections from legacy clients, metadata management that allows federation for access control, and batch-based ETL using PySpark and Scala Operational management should be limited. Which combination of components can meet these requirements? (Choose three.)
Options
- AAWS Glue Data Catalog for metadata management
- BAmazon EMR with Apache Spark for ETL
- CAWS Glue for Scala-based ETL
- DAmazon EMR with Apache Hive for JDBC clients
- EAmazon Athena for querying data in Amazon S3 using JDBC drivers
- FAmazon EMR with Apache Hive, using an Amazon RDS with MySQL-compatible backed
How the community answered
(34 responses)- A59% (20)
- B24% (8)
- D6% (2)
- F12% (4)
Explanation
The three requirements map directly to three services: (A) AWS Glue Data Catalog provides centralized metadata management and supports federation for access control via Lake Formation and IAM - fully managed with no servers to run. (C) AWS Glue natively supports both PySpark and Scala for batch ETL and is fully serverless, satisfying the 'limited operational management' constraint. (E) Amazon Athena supports JDBC drivers (via the Athena JDBC driver), enabling legacy clients to connect using standard SQL over JDBC to query S3 data. Options B, D, and F all involve Amazon EMR, which requires cluster provisioning and operational management, violating the 'limited operational management' requirement.
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