Add alias support to UC Model Registry REST Store #8307
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@arpitjasa-db Thank you for the contribution! Could you fix the following issue(s)? ⚠ DCO checkThe DCO check failed. Please sign off your commit(s) by following the instructions here. See https://github.com/mlflow/mlflow/blob/master/CONTRIBUTING.md#sign-your-work for more details. |
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Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
harupy
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Apr 24, 2023
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LGTM! |
smurching
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Apr 24, 2023
smurching
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Apr 24, 2023
lobrien
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May 10, 2023
* Add alias support to UC Model Registry REST Store Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com> * Add protos Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com> --------- Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com> Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
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Related Issues/PRs
#8001
#8055
#8094
#8164
What changes are proposed in this pull request?
Add support for UC Model Registry alias endpoints to the UC Model Registry REST Store, so they can be used with the MLflow client in this setting.
How is this patch tested?
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
Add support for UC Model Registry alias endpoints to the UC Model Registry REST Store, so they can be used with the MLflow client in this setting.
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes