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Added mechanism to delete artifacts from GCS repository using MLFlow garbage collection #5811

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merged 2 commits into from May 5, 2022

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@ghost ghost commented May 2, 2022

What changes are proposed in this pull request?

To delete artifacts from Google Cloud Storage, and tests to check if the function to delete the artifacts executes.

How is this patch tested?

  1. By having the backend store as a SQLite database - I have tested it by having a backend store as SQLite, by creating an experiment and few runs, while storing the artifacts in GCS. Then, I would delete the runs, and execute MLFlow garbage collection (gc).
  2. In a production environment - I have tested it on a production environment, as well. An MLFlow instance was installed and running on a Kubernetes cluster. The backend store was MySQL database. I created an experiment and few runs, while storing the artifacts in GCS. Then, I would delete the runs, and execute MLFlow garbage collection (gc) in the cluster environment.

Does this PR change the documentation?

  • No. You can skip the rest of this section.
  • Yes. Make sure the changed pages / sections render correctly by following the steps below.
  1. Check the status of the ci/circleci: build_doc check. If it's successful, proceed to the
    next step, otherwise fix it.
  2. Click Details on the right to open the job page of CircleCI.
  3. Click the Artifacts tab.
  4. Click docs/build/html/index.html.
  5. Find the changed pages / sections and make sure they render correctly.

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.

The user can delete artifacts from GCS with MLFlow garbage collection.

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

Components

  • 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
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • 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

Interface

  • 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

Language

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

Integrations

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

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

  • rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
  • 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/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

…d with the deleted runs using MLFlow garbage collector (mlflow gc). 2. Added a test to check if the associated function to delete the artifacts executes.

Signed-off-by: Aditya Iyengar <aditya.iyengar@rtl.de>
@github-actions github-actions bot added area/artifacts Artifact stores and artifact logging rn/feature Mention under Features in Changelogs. labels May 2, 2022
Comment on lines 152 to 153
except Exception:
raise MlflowException("Run not found")
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@aditya-iyengar-rtl-de Can we remove the generic exception hander and instead let the underlying exception throw / propagate? This should make it easier for users to debug issues.

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@dbczumar : I have removed the exception handler.

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@aditya-iyengar-rtl-de Thanks so much for filing this PR! I've approved it with one small suggestion - https://github.com/mlflow/mlflow/pull/5811/files#r864033151. Happy to merge once that's addressed!

Signed-off-by: Aditya Iyengar <aditya.iyengar@rtl.de>
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dbczumar commented May 5, 2022

Thanks @aditya-iyengar-rtl-de ! Merging!

@dbczumar dbczumar merged commit 1539d9e into mlflow:master May 5, 2022
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ghost commented May 10, 2022

Thanks @dbczumar :)

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