Google Professional Data Engineer
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You are working for an advertising company that has developed a Spark ML model to predict click-through rates for advertisement blocks. With the company migrating from an on-premises data center to Google Cloud, and data being moved to BigQuery, you need to ensure the periodic retraining of your Spark ML models continues seamlessly. What is the most efficient way to migrate your existing training pipelines to Google Cloud?
A
Rewrite your models in TensorFlow and transition to using Vertex AI for training.
B
Utilize Vertex AI for training your existing Spark ML models directly.
C
Employ Dataproc to train your existing Spark ML models, sourcing data directly from BigQuery.
D
Create a Spark cluster on Compute Engine and train your models using data exported from BigQuery.