Data Science Model Deployments and Cloud Computing on GCP - Introduction to Airflow

The video provides a refresher on Cloud Composer, a managed Apache Airflow service on GCP. It explains how to set up an Airflow cluster by selecting nodes and their capacities. The video also covers interaction methods with Airflow, including the Cloud Console and gcloud command line tool. It introduces DAGs and discusses Composer 1 and Composer 2 environments, highlighting their features. Finally, it demonstrates creating a Composer environment for orchestrating PySpark jobs on Dataproc Serverless.

What is Cloud Composer primarily used for?

• Running Apache Airflow as a managed service on GCP

• Managing virtual machines on GCP

• Developing mobile applications on GCP

• Storing large datasets on GCP

Which of the following is NOT a method to interact with Cloud Composer?

• API client libraries

• gcloud command line tool

• Cloud Console

• Google Sheets

What does a DAG in Airflow represent?

• A single task

• A collection of tasks with dependencies

• A network configuration

• A database schema

Which Composer environment supports auto-scaling?

• Neither Composer 1 nor 2

• Both Composer 1 and 2

• Composer 2

• Composer 1

What is the recommended machine type for creating a Cloud Composer environment for demonstration purposes?

• N1 standard 16

• N1 highcpu 8

• N1 highmem 4

• N1 standard 1