Replace Window shell-escaping of databricks run command with bash escaping

[wolpl]

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pip install git+https://github.com/mlflow/mlflow.git@refs/pull/10811/merge

Checkout with GitHub CLI

gh pr checkout 10811

Related Issues/PRs

#8981 MLflow Project Runs Failing on Azure Databricks with "Invalid backend config JSON" Error

What changes are proposed in this pull request?

Launching an MLflow projects run on databricks from Windows currently results in the run failing with a JSONDecodeError, as mentioned in the Issue linked above.
The reason for the crash is that when constructing the MLflow run command, that is later executed on databricks, a shell escaping is applied to the parameters. For this, the quote() function from mlflow.utils.string_utils is used, which applies a Windows command line escaping on Windows machines:

def quote(s):
    return mslex_quote(s) if os.name == "nt" else shlex.quote(s)

Because the command is then sent to databricks and executed on a Linux machine, the parameters cannot be parsed and the run fails.

Consequently, when assembling the mlflow run command for databricks, the bash escaping should always be used, regardless of the current OS.

How is this PR tested?

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

The mlflow_run_cmd variable in

mlflow/mlflow/projects/databricks.py

Line 359 in 17dd903

mlflow_run_cmd = " ".join([quote(elem) for elem in mlflow_run_arr])

as of prior to this change is e.g. set to (when running on Windows):

mlflow run /databricks/mlflow/projects/d0500... -c ^"{\^"_mlflow_local_backend_run_id\^": \^"af4...\^"}^"

Now it is:

mlflow run /databricks/mlflow/projects/d0500.... -c '{"_mlflow_local_backend_run_id": "4d0..."}'

In both commands I omitted the entrypoint and shortened the run ID and project ID. It is clear, that the upper command cannot be parsed by the bash on databricks. It is formatted for a Windows command line,

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.

Fix MLflow projects runs on databricks, that are launched from Windows, crashing with a JSONDecodeError

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/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
• 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/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• 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/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

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[BenWilson2]

@wolpl great catch! Triggered CI for the change :)

[harupy]

@mlflow-automation autoformat

[harupy]

LGTM!