Data Science Model Deployments and Cloud Computing on GCP - Persistent History Cluster

This video tutorial covers the prerequisite steps for deploying a PySpark batch job on Dataproc Serverless. It includes setting up necessary variables, enabling BigQuery and Dataproc APIs, creating a subnet for private IP access, defining cluster and bucket variables, and creating a storage bucket. The tutorial also guides on creating a Dataproc cluster with a component gateway for persistent history storage.

What are the prerequisite steps before deploying a Pyspark batch job on Dataproc serverless?

What variables are defined in the bash file for the Pyspark job?

Why is it necessary to enable the Big Query API and Dataproc API?

What is the significance of creating a subnet for Pyspark jobs on Dataproc serverless?

What command is used to create a Dataproc cluster for persistent history storage?

What is the purpose of the component Gateway in the Dataproc cluster?

What should you do after the Dataproc single node cluster has been provisioned?