Imagine you are tasked with deploying a machine learning model trained using Spark ML to a production environment. Describe the steps you would take to ensure the model is production-ready and what considerations you need to make regarding model serialization and deployment.

Simulated

Convert the model to a JSON format for easy deployment; considerations include data schema compatibility.

7.4%

Use Spark ML's model persistence functions to save and load the model; considerations include version control and backward compatibility.

85.2%

Deploy the model directly from the Spark cluster without any modifications; considerations include network latency.

3.7%

Export the model to a standalone scikit-learn model for deployment; considerations include performance degradation.

3.7%

Databricks Certified Machine Learning - Associate