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MINOR: Pydantic fixes for redshift & kafka (#16638)
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@ -328,6 +328,8 @@ test = {
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"minio==7.2.5",
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"minio==7.2.5",
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*plugins["mlflow"],
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*plugins["mlflow"],
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*plugins["datalake-s3"],
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*plugins["datalake-s3"],
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*plugins["kafka"],
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"kafka-python==2.0.2",
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*plugins["pii-processor"],
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*plugins["pii-processor"],
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"requests==2.31.0",
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"requests==2.31.0",
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}
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}
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@ -33,7 +33,7 @@ from metadata.generated.schema.entity.services.ingestionPipelines.status import
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from metadata.generated.schema.metadataIngestion.workflow import (
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from metadata.generated.schema.metadataIngestion.workflow import (
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Source as WorkflowSource,
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Source as WorkflowSource,
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)
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)
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from metadata.generated.schema.type.basic import EntityName
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from metadata.generated.schema.type.basic import EntityName, FullyQualifiedEntityName
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from metadata.generated.schema.type.schema import SchemaType, Topic
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from metadata.generated.schema.type.schema import SchemaType, Topic
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from metadata.ingestion.api.models import Either
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from metadata.ingestion.api.models import Either
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from metadata.ingestion.models.ometa_topic_data import OMetaTopicSampleData
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from metadata.ingestion.models.ometa_topic_data import OMetaTopicSampleData
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@ -95,7 +95,7 @@ def get_connection(
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schema_registry_client = None
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schema_registry_client = None
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consumer_client = None
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consumer_client = None
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if connection.schemaRegistryURL:
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if connection.schemaRegistryURL:
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schema_registry_config["url"] = connection.schemaRegistryURL
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schema_registry_config["url"] = str(connection.schemaRegistryURL)
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schema_registry_client = SchemaRegistryClient(schema_registry_config)
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schema_registry_client = SchemaRegistryClient(schema_registry_config)
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consumer_config["bootstrap.servers"] = connection.bootstrapServers
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consumer_config["bootstrap.servers"] = connection.bootstrapServers
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if "group.id" not in consumer_config:
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if "group.id" not in consumer_config:
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109
ingestion/tests/integration/kafka/test_kafka.py
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109
ingestion/tests/integration/kafka/test_kafka.py
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@ -0,0 +1,109 @@
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# Copyright 2021 Collate
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Test Kafka using the topology
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"""
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from unittest import TestCase
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from confluent_kafka import Producer
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from testcontainers.kafka import KafkaContainer
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from metadata.generated.schema.entity.data.topic import Topic
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from metadata.generated.schema.entity.services.connections.metadata.openMetadataConnection import (
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AuthProvider,
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OpenMetadataConnection,
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)
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from metadata.generated.schema.security.client.openMetadataJWTClientConfig import (
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OpenMetadataJWTClientConfig,
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)
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from metadata.ingestion.models.custom_pydantic import CustomSecretStr
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from metadata.ingestion.ometa.ometa_api import OpenMetadata
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from metadata.workflow.metadata import MetadataWorkflow
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def produce_and_consume_kafka_message(container):
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topic = "test-topic"
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bootstrap_server = container.get_bootstrap_server()
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producer = Producer({"bootstrap.servers": bootstrap_server})
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producer.produce(topic, b"verification message")
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producer.flush()
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OM_JWT = "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
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def get_ingestion_config(port: str):
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return {
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"source": {
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"type": "kafka",
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"serviceName": "TEST_KAFKA",
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"serviceConnection": {
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"config": {
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"type": "Kafka",
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"bootstrapServers": f"localhost:{port}",
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}
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},
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"sourceConfig": {"config": {"type": "MessagingMetadata"}},
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},
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"sink": {"type": "metadata-rest", "config": {}},
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"workflowConfig": {
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"loggerLevel": "DEBUG",
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"openMetadataServerConfig": {
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"hostPort": "http://localhost:8585/api",
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"authProvider": "openmetadata",
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"securityConfig": {
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"jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
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},
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},
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},
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}
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def int_admin_ometa(url: str = "http://localhost:8585/api") -> OpenMetadata:
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"""Initialize the ometa connection with default admin:admin creds"""
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server_config = OpenMetadataConnection(
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hostPort=url,
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authProvider=AuthProvider.openmetadata,
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securityConfig=OpenMetadataJWTClientConfig(jwtToken=CustomSecretStr(OM_JWT)),
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)
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metadata = OpenMetadata(server_config)
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assert metadata.health_check()
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return metadata
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class KafkaUnitTest(TestCase):
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@classmethod
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def setUpClass(cls) -> None:
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cls.metadata = int_admin_ometa()
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cls.kafka_container = KafkaContainer()
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cls.kafka_container.start()
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cls.ingestion_config = get_ingestion_config(
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cls.kafka_container.get_exposed_port(9093)
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)
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produce_and_consume_kafka_message(cls.kafka_container)
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ingestion_workflow = MetadataWorkflow.create(
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cls.ingestion_config,
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)
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ingestion_workflow.execute()
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ingestion_workflow.raise_from_status()
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ingestion_workflow.stop()
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def test_topic(self):
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topic = self.metadata.get_by_name(
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entity=Topic,
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fqn="TEST_KAFKA.test-topic",
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)
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self.assertIsNotNone(topic)
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@ -202,7 +202,7 @@ def metadata_ingestion_workflow(workflow_config: OpenMetadataWorkflowConfig):
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set_operator_logger(workflow_config)
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set_operator_logger(workflow_config)
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config = json.loads(workflow_config.model_dump_json())
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config = json.loads(workflow_config.model_dump_json(exclude_defaults=False))
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workflow = MetadataWorkflow.create(config)
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workflow = MetadataWorkflow.create(config)
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workflow.execute()
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workflow.execute()
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@ -313,7 +313,8 @@ def send_failed_status_callback(workflow_config: OpenMetadataWorkflowConfig, *_,
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)
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)
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pipeline_status = metadata.get_pipeline_status(
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pipeline_status = metadata.get_pipeline_status(
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workflow_config.ingestionPipelineFQN, str(workflow_config.pipelineRunId)
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workflow_config.ingestionPipelineFQN,
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str(workflow_config.pipelineRunId.root),
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)
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)
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pipeline_status.endDate = Timestamp(int(datetime.now().timestamp() * 1000))
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pipeline_status.endDate = Timestamp(int(datetime.now().timestamp() * 1000))
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pipeline_status.pipelineState = PipelineState.failed
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pipeline_status.pipelineState = PipelineState.failed
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