Related Issues/PRs

What changes are proposed in this pull request?

Motivation: The job backend uses function full name module.func_name as a unique identifier for the job function. This blocks us from moving function module in the future, because it will cause inconsistency between client and server in different versions. Each job function should have its own unique name and MLflow should maintain the mapping

In this PR, I updated the job decorator to add a name param, like:

@job(name="the_static_name")
def my_job_function():
    ...

then, the job function is associated with the decorated static name, in newer MLflow versions, the job function can be renamed or moved to other module, we only need to keep the job static name unchanged, then the job function can work across different Mlflow versions.

For REST API request, user should set the static job name in the payload, and in the REST response, the job static name is returned. The real job function name is no longer exposed to front-end.

For job backend SQL table storage, it only saves the job static name, instead of the full function name. So that the unfinished job resumption can work across different MLFlow versions, and it can guarantee to query out all history jobs (submitted via different MLFlow versions) via the static job name.

How is this PR tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests

Does this PR require documentation update?

• No. You can skip the rest of this section.
• Yes. I've updated:
  • Examples
  • API references
  • Instructions

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

job decorator provides a name param, for marking the static name of the job function.

What component(s), interfaces, languages, and integrations does this PR affect?

Components

• area/tracking: Tracking Service, tracking client APIs, autologging
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
• area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
• area/prompts: MLflow prompt engineering features, prompt templates, and prompt management
• area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
• area/projects: MLproject format, project running backends
• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages

How should the PR be classified in the release notes? Choose one:

• rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
• rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
• rn/documentation - A user-facing documentation change worth mentioning in the release notes

Should this PR be included in the next patch release?

Yes should be selected for bug fixes, documentation updates, and other small changes. No should be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.

• Yes (this PR will be cherry-picked and included in the next patch release)
• No (this PR will be included in the next minor release)