Add SPARK_LOCAL_IP in cross version tests config#4237
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harupy merged 5 commits intomlflow:masterfrom Apr 12, 2021
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Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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Apr 11, 2021
| @@ -1,3 +1,4 @@ | |||
| # Revert this | |||
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Added this line to trigger the keras tests. I'll revert this once I confrim setting SPARK_LOCAL_IP make them stable.
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Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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* Add SPARK_LOCAL_IP in cross version tests config Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * add dummy change to trigger test Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * attempt2 Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * attempt3 Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * revert dummy change Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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Signed-off-by: harupy 17039389+harupy@users.noreply.github.com
What changes are proposed in this pull request?
Add
SPARK_LOCAL_IPin the cross version tests config.The cross version tests for keras have been failing:
https://github.com/mlflow/mlflow/actions/runs/737661908
How is this patch tested?
Existing unit tests
Release Notes
Is this a user-facing change?
(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 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/projects: MLproject format, project running backendsarea/scoring: Local serving, model deployment tools, spark UDFsarea/server-infra: MLflow server, JavaScript dev serverarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, JavaScript, plottingarea/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