MCQs on ETL Basics | AWS Glue MCQs Question

Dive into these AWS Glue MCQ questions and answers to strengthen your understanding of ETL concepts, Glue Studio, and data transformations. Chapter 4 covers creating ETL jobs, scripting transformations, and leveraging AWS Glue Studio. This set is perfect for enhancing your skills in AWS Glue and data processing workflows.

MCQs on Creating ETL Jobs in AWS Glue

1. AWS Glue is primarily designed for:
   a) Data storage
   b) Extracting, transforming, and loading data
   c) Running machine learning models
   d) Managing EC2 instances
2. What is the main component of an AWS Glue ETL process?
   a) Glue Catalog
   b) Glue Job
   c) Glue Crawler
   d) Glue API
3. Glue jobs are executed using:
   a) AWS Lambda functions
   b) Spark runtime environment
   c) EC2 instances
   d) Step Functions
4. AWS Glue supports which programming languages for ETL scripts?
   a) Java and Ruby
   b) Python and Scala
   c) C++ and PHP
   d) Node.js and Go
5. What is the purpose of an AWS Glue Crawler?
   a) To store ETL scripts
   b) To create metadata tables in the Glue Data Catalog
   c) To monitor Glue Jobs
   d) To manage IAM roles
6. Which of the following AWS services integrates with AWS Glue for storing ETL results?
   a) S3
   b) DynamoDB
   c) RDS
   d) CloudWatch
7. AWS Glue ETL jobs can be triggered by:
   a) Manually invoking them only
   b) Scheduled triggers or event-based triggers
   c) EC2 instance startups
   d) VPC flow logs
8. To handle large datasets in AWS Glue, which job parameter is commonly configured?
   a) Timeout
   b) Worker type and number
   c) IAM role
   d) Glue version

MCQs on Working with Glue Studio

9. AWS Glue Studio provides a graphical interface for:
   a) Managing Glue Catalogs
   b) Building and monitoring ETL workflows
   c) Running Lambda functions
   d) Configuring EC2 instances
10. What feature of AWS Glue Studio simplifies ETL job creation?
    a) Pre-built connectors for data sources
    b) Automated database indexing
    c) Machine learning integration
    d) Workflow testing
11. Glue Studio allows users to create jobs using:
    a) SQL Queries
    b) Drag-and-drop interface or custom code
    c) CloudFormation templates
    d) AWS CLI commands
12. In AWS Glue Studio, transformations can be added using:
    a) SparkSQL
    b) Visual nodes in the job graph
    c) DataSync policies
    d) API Gateway integrations
13. Glue Studio can preview data transformations using:
    a) Sample datasets
    b) Real-time logs
    c) Test EC2 instances
    d) RDS snapshots
14. Glue Studio provides a visual representation of:
    a) ETL workflows and transformations
    b) IAM policy usage
    c) CloudWatch metrics
    d) EC2 instance metrics
15. Which type of job does Glue Studio support creating?
    a) Batch processing jobs only
    b) Both batch and streaming jobs
    c) Machine learning inference jobs
    d) Event-driven Lambda jobs
16. Glue Studio jobs can be monitored via:
    a) CloudWatch dashboards
    b) The Glue Console’s job run history
    c) Step Function workflows
    d) DynamoDB streams

MCQs on Data Transformations and Scripts

17. In AWS Glue, a data transformation is:
    a) A process of modifying, filtering, or enriching data
    b) Storing data in a database
    c) Encrypting data at rest
    d) Setting IAM policies
18. What is a common transformation in AWS Glue?
    a) Filtering rows based on conditions
    b) Launching EC2 instances
    c) Updating IAM roles
    d) Archiving logs
19. AWS Glue provides dynamic frame APIs for:
    a) Data transformation and schema management
    b) Visualizing data on dashboards
    c) Creating IAM policies
    d) Encrypting data
20. Which library is used by Glue to simplify data transformation in Python?
    a) Pandas
    b) PySpark
    c) Numpy
    d) Scikit-learn
21. To handle schema evolution during transformations, Glue uses:
    a) DynamicFrames
    b) StaticTables
    c) SparkSQL queries
    d) Lambda functions
22. What is the main advantage of writing custom scripts in AWS Glue?
    a) Enables fine-grained control over ETL processes
    b) Improves IAM security
    c) Reduces data storage costs
    d) Simplifies workflow deployment
23. AWS Glue scripts can be developed in:
    a) AWS Lambda console
    b) Jupyter notebooks or Glue Console
    c) EC2 instances only
    d) CloudTrail dashboard
24. A PySpark script in AWS Glue typically starts by creating:
    a) A DataFrame
    b) A DynamicFrame
    c) An EC2 instance
    d) An S3 bucket

MCQs on Advanced ETL Techniques

25. What is a bookmark in AWS Glue?
    a) A marker to track processed data in incremental loads
    b) A log entry for failed jobs
    c) A tag for identifying workflows
    d) An IAM role assigned to the job
26. Glue bookmarks are useful for:
    a) Avoiding reprocessing of already processed data
    b) Optimizing job execution time
    c) Managing IAM policies
    d) Setting up CloudWatch alarms
27. Which transformation is used for data aggregation in Glue?
    a) GroupBy
    b) Flatten
    c) Join
    d) Map
28. What is the best practice for handling errors in Glue scripts?
    a) Add error-handling logic in the script
    b) Disable error logging
    c) Use IAM roles to resolve errors
    d) Restart the job
29. Glue supports joining datasets by using:
    a) SQL-style joins in scripts
    b) Predefined CloudFormation templates
    c) IAM roles
    d) S3 bucket configurations
30. To process streaming data with AWS Glue, you must use:
    a) Glue Streaming Jobs
    b) Glue Batch Jobs
    c) EC2 Data Processors
    d) RDS triggers

Answer Key