Back to AWS Glue

AWS Glue ETL Jobs

5 minutes 5 Questions

An AWS Glue ETL Job is the code that runs in the managed Apache Spark environment to perform the necessary data transformations. You can write the ETL code in Python or Scala, and AWS Glue takes care of managing the underlying Spark infrastructure for you. Based on the metadata stored in the Data C…

Test mode:
Start practice test
AWS Certified Solutions Architect - AWS Glue ETL Jobs Example Questions

Test your knowledge of AWS Glue ETL Jobs

Question 1

You have an ETL pipeline that processes online gaming data stored in Amazon S3 using AWS Glue jobs. The games are popular worldwide, and data is continuously ingested via Kinesis Data Firehose. You want to reduce gaming event processing delays. What can you do to optimize your ETL pipeline?

Correct Answer: Enable job bookmarks in AWS Glue jobs

Enabling job bookmarks in AWS Glue jobs tracks job state, allowing jobs to process only new or incremental data. This reduces gaming event processing delays. The other options may either not impact performance or negatively impact performance.

Question 2

As a Solutions Architect, you are building an ETL pipeline that processes customer data in JSON format stored in Amazon S3. Each day, you receive about 10 GB of new data. You need to cleanse and store this data in Amazon Redshift for immediate querying. Which is the most cost-effective solution?

Correct Answer: Use AWS Glue to convert JSON data to Apache Parquet format, and then insert transformed data into Redshift

Using AWS Glue to convert JSON data to columnar formats like Apache Parquet greatly improves query performance and storage efficiency. Then, loading the transformed data into Redshift is cost-effective. Directly inserting JSON data or using another format besides Parquet may increase costs due to reduced performance or storage efficiency.

Question 3

You are using AWS Glue to process a large dataset stored in Amazon S3. The dataset is primarily composed of small files. The ETL job is taking longer than expected. How would you optimize the ETL job performance?

Correct Answer: Consolidate the small files into larger files before running the ETL job

AWS Glue processes larger files more efficiently. Consolidating smaller files into larger ones before running the ETL job improves performance. Decreasing MaxConcurrentRuns will lower the processing capability of the ETL job. The other wrong answers are not relevant optimizations for this scenario.

More AWS Glue ETL Jobs questions
18 questions (total)
Start 18 question test