[EPIC] Support model versioning metadata

[SteNicholas]

Describe the feature

Model versioning indicates the version control of ML models. It describes the practice of storing, tracking, and managing the changes in an ML model. It's recommended support metadata management of model versioning in Gravitino.

Subtasks:

• [Subtask]Investigate and design the model management in Gravitino #5589
• [Subtask]Design and implement the Java API for model and model operation #5600
• [Subtask]Implement the model entity and model catalog dispatcher in core #5601
• [Subtask]Design and implement the storage schema for model #5602
• [Subtask] Add the basic module for model catalog #5744
• [Subtask]Implement the core logic for model catalog operation. #5739
• [Subtask]Implement the model catalog dispatcher logic #5794
• [Subtask]Implement the server rest endpoint for model catalog. #5817
• [Subtask]Implement the Java client API for model catalog. #5872
• [Subtask] Implement the Python client API for model catalog. #5889
• [Subtask]Add integration test for both Python and Java APIs #5950
• [Subtask] Add docs for model management #5933
• [Subtask] ML model support for web UI #5965
• [Subtask]Add tag support for model #6222
• [Subtask] Add privilege support for model #6346
• [EPIC] Add model relative event to event system. #6074
• [Subtask]Add metadata alteration support for the model. #6226

Motivation

No response

Describe the solution

No response

Additional context

No response

[FANNG1]

@SteNicholas Thank you for proposing this. I have two questions:

1. How are users currently managing model versions?
2. how would Gravitino integrate with the existing ML ecosystem if it supports model metadata?

[jerryshao]

I will do this ML model management feature in the next release cadence (0.8).