Fix bug: = and != operators are not case-sensitive in run search
#6900
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Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
github-actions
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area/tracking
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
BenWilson2
approved these changes
Sep 27, 2022
harupy
commented
Sep 27, 2022
Comment on lines
-48
to
-52
| CASE_INSENSITIVE_STRING_COMPARISON_OPERATORS = {LIKE_OPERATOR, ILIKE_OPERATOR} | ||
| VALID_REGISTERED_MODEL_SEARCH_COMPARATORS = CASE_INSENSITIVE_STRING_COMPARISON_OPERATORS.union( | ||
| {"="} | ||
| ) | ||
| VALID_MODEL_VERSIONS_SEARCH_COMPARATORS = {"=", "IN"} |
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Removed unused class members.
harupy
commented
Sep 27, 2022
Comment on lines
+116
to
+117
| if not isinstance(column.type, sa.types.String): | ||
| return comparison_func(column, value) |
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We don't need to worry about case sensitivity if the column type is non-string.
harupy
commented
Sep 27, 2022
| ) | ||
| else: | ||
| return None | ||
| key_filter = SearchUtils.get_sql_comparison_func("=", dialect)(entity.key, key_name) |
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This line makes key search case-sensitive.
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Signed-off-by: harupy <hkawamura0130@gmail.com>
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Signed-off-by: harupy hkawamura0130@gmail.com
Related Issues/PRs
#xxx
What changes are proposed in this pull request?
=and!=operators are not case-sensitive in run search. This PR fixes it.How is this patch tested?
Does this PR change the documentation?
Detailslink on thePreview docscheck.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/pipelines: Pipelines, Pipeline APIs, Pipeline configs, Pipeline 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