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AWS Glue Data Sink

5 minutes 5 Questions

AWS Glue Data Sink represents the destination of your processed data in your AWS Glue ETL jobs. Data Sink configuration defines where and how the output data should be written. This can be set to various AWS services such as Amazon S3, Amazon Redshift, or Amazon RDS, depending on where you would li…

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AWS Certified Solutions Architect - AWS Glue Data Sink Example Questions

Test your knowledge of AWS Glue Data Sink

Question 1

You are using AWS Glue to process data and plan to emit insights generated using Amazon QuickSight. Your data set size is around 2 TB. What should be the format of the data ingested into Amazon QuickSight for best performance?

Correct Answer: Apache Parquet

For large datasets, Apache Parquet provides an optimized columnar storage format with high compression and encoding schemes. Therefore, using Parquet as the data format ingested into Amazon QuickSight will provide better performance for larger datasets.

Question 2

You are designing a data processing system using AWS Glue as the ETL engine. You need to store the processed data in an optimal and cost-effective storage service. Which AWS data sink should you choose for the processed data?

Correct Answer: Amazon S3

Amazon S3 is a cost-effective storage service for processed and raw data. Choosing S3 as a data sink will not only lower the storage costs but also provide flexibility in data storage formats such as Parquet, CSV, etc.

Question 3

You are creating a new AWS Glue ETL job to process large amounts of raw streaming data. Your processing requirements dictate using Amazon Glue DataBrew. Which data sink can you directly use as output in this scenario?

Correct Answer: Amazon S3

Amazon Glue DataBrew directly supports Amazon S3 as an output data sink. Other data sinks require additional processing or configurations to be either directly or indirectly used.

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