Snowflake - Build and Architect Data Pipelines Using AWS - Lab - Deploy and Execute Python Script to AWS Glue

What is the primary function of AWS Glue?

• To provide a user interface for AWS services

• To execute Python and PySpark jobs in a serverless manner

• To store large datasets

• To manage AWS billing and costs

How does AWS Glue handle external dependencies for Python scripts?

• By automatically installing all available libraries

• By requiring users to manually install dependencies on the VM

• By using WHL files to manage specific dependencies

• By using a built-in package manager

What is the recommended Python version for building a WHL file in AWS Glue?

• Python 2.7

• Python 3.5

• Python 3.6

• Python 3.7 or above

Which role should be selected when setting up an AWS Glue job for the first time?

• AWS EC2 instance role

• AWS S3 access role

• AWS Glue service role

• AWS Lambda execution role

What is the default maximum capacity for an AWS Glue job?

• 0.125

• 0.5

• 0.0625

• 1.0

What is the purpose of parameterizing a Glue job?

• To simplify the job setup process

• To reduce the cost of execution

• To allow dynamic input values for the job

• To increase the execution speed

Which AWS services can benefit from parameterized Glue jobs?

• AWS CloudWatch and AWS IAM

• AWS Lambda and Airflow

• AWS RDS and AWS DynamoDB

• AWS S3 and AWS EC2