DEA-C01 Question 283
Select 2You are designing a data pipeline using Amazon S3 and AWS Glue. The schema of your data stored in S3 is expected to change over time, such as new columns being added or existing columns being removed. Which of the following schema evolution techniques would allow you to handle these changes with minimal interruption to your pipeline?
- A
Enable AWS Glue's schema compatibility feature to automatically handle schema changes.
- B
Use AWS Glue's DynamicFrame, which can handle schema changes flexibly during ETL jobs.
- C
Store schema versions in the AWS Glue Data Catalog and update downstream applications when schema changes occur.
- D
Leverage Apache Parquet format for your S3 files to support schema evolution efficiently.
- E
Use AWS Glue's built-in schema enforcement to reject any records that do not match the existing schema.
Show answer and explanation
Correct answers: B, D
Explanation
To handle schema evolution with minimal interruption, you can use AWS Glue's DynamicFrame, which is designed to accommodate schema changes during ETL jobs. Additionally, using schema-aware file formats like Apache Parquet allows your data storage to adapt to schema changes efficiently, such as adding or removing columns, without breaking your pipeline. Combining these techniques ensures a robust and flexible pipeline design.
- A. Incorrect.
AWS Glue does not have a specific 'schema compatibility' feature that automatically handles all schema changes. Schema compatibility must be handled through proper design and tools like DynamicFrames or schema-aware file formats.
- B. Correct.
AWS Glue's DynamicFrame is designed to handle schema changes flexibly during ETL processes, making it a good choice for evolving schemas.
- C. Incorrect.
While storing schema versions in the AWS Glue Data Catalog can help track changes, it does not inherently handle schema evolution or ensure compatibility during ETL processes.
- D. Correct.
Apache Parquet is a columnar storage file format that supports schema evolution, such as adding or removing columns, making it efficient for evolving schemas.
- E. Incorrect.
AWS Glue does not enforce schema rejection by default. Rejecting records based on schema mismatches would require custom logic and is not a built-in capability for handling schema evolution.