[FR] support compressing model artifact in log_model

[mathiasottenbreit]

Willingness to contribute

No. I cannot contribute this feature at this time.

Proposal Summary

In log_model(), enable the option to compress the model artifact (for example by using joblib.dump and specifying the compression level). Sometimes model artifacts can get very large without compression but can be compressed to a much smaller size, reducing storage costs.

Motivation

What is the use case for this feature?

Reducing storage costs.

Why is this use case valuable to support for MLflow users in general?

Users can reduce storage costs.

Why is this use case valuable to support for your project(s) or organization?

Reducing storage costs.

Why is it currently difficult to achieve this use case?

Even when creating a custom PythonModel, an uncompressed python_model.pkl is still created by log_model().

Details

No response

What component(s) does this bug affect?

• [ ] area/artifacts: Artifact stores and artifact logging
• [ ] area/build: Build and test infrastructure for MLflow
• [ ] area/docs: MLflow documentation pages
• [ ] area/examples: Example code
• [ ] area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• [x] area/models: MLmodel format, model serialization/deserialization, flavors
• [ ] area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• [ ] area/projects: MLproject format, project running backends
• [ ] area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• [ ] area/server-infra: MLflow Tracking server backend
• [ ] area/tracking: Tracking Service, tracking client APIs, autologging

What interface(s) does this bug affect?

• [ ] area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• [ ] area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• [ ] area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• [ ] area/windows: Windows support

What language(s) does this bug affect?

• [ ] language/r: R APIs and clients
• [ ] language/java: Java APIs and clients
• [ ] language/new: Proposals for new client languages

What integration(s) does this bug affect?

• [ ] integrations/azure: Azure and Azure ML integrations
• [ ] integrations/sagemaker: SageMaker integrations
• [ ] integrations/databricks: Databricks integrations