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Avoid setting MLFLOW_TRACKING_URI in test_examples.py #5453

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merged 1 commit into from
Mar 5, 2022

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@harupy harupy commented Mar 4, 2022

Signed-off-by: harupy 17039389+harupy@users.noreply.github.com

What changes are proposed in this pull request?

Avoid setting MLFLOW_TRACKING_URI in test_examples.py to fix the following error:

https://github.com/mlflow/mlflow/runs/5420042030?check_suite_focus=true#step:7:354

Traceback (most recent call last):
  File "/tmp/pytest-of-runner/pytest-0/test_mlflow_run_example_supply0/supply_chain_security/train.py", line 14, in <module>
    with mlflow.start_run() as run:
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/fluent.py", line 194, in start_run
    client = MlflowClient()
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/client.py", line 70, in __init__
    self._tracking_client = TrackingServiceClient(final_tracking_uri)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/client.py", line 44, in __init__
    self.store
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/client.py", line 48, in store
    return utils._get_store(self.tracking_uri)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/utils.py", line 155, in _get_store
    return _tracking_store_registry.get_store(store_uri, artifact_uri)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/registry.py", line 39, in get_store
    return self._get_store_with_resolved_uri(resolved_store_uri, artifact_uri)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/registry.py", line 49, in _get_store_with_resolved_uri
    return builder(store_uri=resolved_store_uri, artifact_uri=artifact_uri)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/utils.py", line 117, in _get_sqlalchemy_store
    return SqlAlchemyStore(store_uri, artifact_uri)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/store/tracking/sqlalchemy_store.py", line 140, in __init__
    mlflow.store.db.utils._verify_schema(self.engine)
  File "/usr/share/miniconda/envs/mlflow-2db1ebf9ea6f978512f24e8516507b38fb7ad1fc/lib/python3.9/site-packages/mlflow/store/db/utils.py", line 53, in _verify_schema
    raise MlflowException(
mlflow.exceptions.MlflowException: Detected out-of-date database schema (found version bd07f7e963c5, but expected c48cb773bb87). Take a backup of your database, then run 'mlflow db upgrade <database_uri>' to migrate your database to the latest schema. NOTE: schema migration may result in database downtime - please consult your database's documentation for more detail.

How did the error above occur?

  • test_mlflow_run_example calls the tracking_uri_mock fixture.
  • tracking_uri_mock set MLFLOW_TRACKING_URI.
  • test_mlflow_run_example runs the supply_chain_security example using mlflow run
  • mlflow run initializes the SQLite database points MLFLOW_TRACKING_URI using the dev version of MLflow.
  • mlflow run creates a conda environment for running the supply_chain_security example which pins mlflow to 1.20.2.
  • train.py in the supply_chain_security example calls mlflow.start_run which verifies the MLflow DB has a valid schema and throws an error because the DB was initialized using the dev version of MLflow.

How is this patch tested?

Existing tests

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.

(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)

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

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@github-actions github-actions bot added the rn/none List under Small Changes in Changelogs. label Mar 4, 2022
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LGTM

@harupy harupy merged commit 72bbf2f into mlflow:master Mar 5, 2022
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