2025-04-03 10:39:47 +05:30

115 lines
3.6 KiB
Python

# Copyright 2025 Collate
# Licensed under the Collate Community License, Version 1.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Main ingestion entrypoint to run OM workflows
"""
import os
import yaml
from metadata.generated.schema.entity.services.ingestionPipelines.ingestionPipeline import (
PipelineType,
)
from metadata.generated.schema.metadataIngestion.workflow import LogLevels
from metadata.utils.logger import set_loggers_level
from metadata.workflow.data_quality import TestSuiteWorkflow
from metadata.workflow.metadata import MetadataWorkflow
from metadata.workflow.profiler import ProfilerWorkflow
from metadata.workflow.usage import UsageWorkflow
WORKFLOW_MAP = {
PipelineType.metadata.value: MetadataWorkflow,
PipelineType.usage.value: UsageWorkflow,
PipelineType.lineage.value: MetadataWorkflow,
PipelineType.profiler.value: ProfilerWorkflow,
PipelineType.TestSuite.value: TestSuiteWorkflow,
PipelineType.elasticSearchReindex.value: MetadataWorkflow,
PipelineType.dbt.value: MetadataWorkflow,
}
def main():
"""
Ingestion entrypoint. Get the right Workflow class
and execute the ingestion.
This image is expected to be used and run in environments
such as Airflow's KubernetesPodOperator:
```
config = '''
source:
type: ...
serviceName: ...
serviceConnection:
...
sourceConfig:
...
sink:
...
workflowConfig:
...
'''
KubernetesPodOperator(
task_id="ingest",
name="ingest",
cmds=["python", "main.py"],
image="openmetadata/ingestion-base:0.13.2",
namespace='default',
env_vars={"config": config, "pipelineType": "metadata"},
dag=dag,
)
```
Note how we are expecting the env variables to be sent, with the `config` being the str
representation of the ingestion YAML.
We will also set the `pipelineRunId` value if it comes from the environment.
"""
# DockerOperator expects an env var called config
config = os.getenv("config")
if not config:
raise RuntimeError(
"Missing environment variable `config`. This is needed to configure the Workflow."
)
pipeline_type = os.getenv("pipelineType")
if not pipeline_type:
raise RuntimeError(
"Missing environment variable `pipelineType`. This is needed to load the Workflow class."
)
pipeline_run_id = os.getenv("pipelineRunId")
workflow_class = WORKFLOW_MAP.get(pipeline_type)
if workflow_class is None:
raise ValueError(f"Missing workflow_class loaded from {pipeline_type}")
# Load the config string representation
workflow_config = yaml.safe_load(config)
if pipeline_run_id:
workflow_config["pipelineRunId"] = pipeline_run_id
logger_level = workflow_config.get("workflowConfig", {}).get("loggerLevel")
set_loggers_level(logger_level or LogLevels.INFO.value)
workflow = workflow_class.create(workflow_config)
workflow.execute()
workflow.raise_from_status()
workflow.print_status()
workflow.stop()
if __name__ == "__main__":
main()