
* change deprecationwarning * fix format python * fix replace module * change : java function name
2.4 KiB
title | slug | collate |
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Upgrade 1.3.x to 1.4.x | /deployment/upgrade/versions/130-to-140 | false |
Upgrade from 1.3.x to 1.4.x
Upgrading from 1.3.x to 1.4.x can be done directly on your instances. This page will list few general details you should take into consideration when running the upgrade.
Deprecation Notice
Breaking Changes for 1.4.x Stable Release
Dashboard & Pipeline Source Config Changes
We have restructured how we input the dbServiceNames field, used for creating lineage between pipeline(spline) and tables & dashboard data models and tables. This change was done in order to highlight the field on UI and improve user experience.
Please make note of changes in your yaml.
Before:
sourceConfig:
config:
type: DashboardMetadata # or PipelineMetadata
.....
dbServiceNames:
- redshift_prod
.....
After 1.4.0 Upgrade:
sourceConfig:
config:
type: DashboardMetadata # or PipelineMetadata
.....
lineageInformation:
dbServiceNames:
- redshift_prod
.....
Custom severity classifier config
We have updated openmetadata.yaml
config file and removed the below setting option. If you were previously using it reach out to our team on #support channel in slack.
dataQualityConfiguration:
severityIncidentClassifier: ${DATA_QUALITY_SEVERITY_INCIDENT_CLASSIFIER:-"org.openmetadata.service.util.incidentSeverityClassifier.LogisticRegressionIncidentSeverityClassifier"}
Custom Connectors: Updates to the Initialization Method for Source Class
We have introduced a new parameter, pipeline_name
to the initialization method of source python classes. This change will also apply to the initialization of custom connectors.
Please ensure to update your initialization methods accordingly, as demonstrated below.
Before:
@classmethod
def create(
cls,
config_dict: dict,
metadata_config: OpenMetadataConnection
):
config: WorkflowSource = WorkflowSource.model_validate(config_dict)
.....
.....
return cls(config, metadata_config)
After 1.4.0 Upgrade:
@classmethod
def create(
cls,
config_dict: dict,
metadata_config: OpenMetadataConnection,
pipeline_name: Optional[str] = None
):
config: WorkflowSource = WorkflowSource.model_validate(config_dict)
.....
.....
return cls(config, metadata_config)