mirror of
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* Fix #1604: Add Spline Connector * Add tests & grammer validation * Spline UI Changes & Docs * fix pipeline workflow doc * chore: use common field for dbService name * chore: use const for beta services * chore: add service icon * Update ingestion/src/metadata/ingestion/source/pipeline/spline/metadata.py Co-authored-by: Onkar Ravgan <onkar.10r@gmail.com> --------- Co-authored-by: Sachin Chaurasiya <sachinchaurasiyachotey87@gmail.com> Co-authored-by: Sriharsha Chintalapani <harshach@users.noreply.github.com> Co-authored-by: Onkar Ravgan <onkar.10r@gmail.com>
This commit is contained in:
Mayur Singal
GitHub
parent
fde1139764
commit
e9992a52a8
29
ingestion/src/metadata/examples/workflows/spline.yaml
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29
ingestion/src/metadata/examples/workflows/spline.yaml
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@ -0,0 +1,29 @@
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source:
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type: spline
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serviceName: local_spline
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serviceConnection:
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config:
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type: Spline
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hostPort: http://localhost:8081/
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uiHostPort: http://localhost:9090
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sourceConfig:
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config:
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type: PipelineMetadata
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dbServiceNames:
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- local_databricks
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- local_postgres_empty1
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pipelineFilterPattern:
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includes:
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- .*jdbc.*
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- .*databricks.*
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sink:
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type: metadata-rest
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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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@ -0,0 +1,94 @@
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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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Client to interact with Spline consumer apis
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"""
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import traceback
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from typing import List
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from metadata.generated.schema.entity.services.connections.pipeline.splineConnection import (
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SplineConnection,
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)
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from metadata.ingestion.ometa.client import REST, APIError, ClientConfig
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from metadata.ingestion.source.pipeline.spline.models import (
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ExecutionDetail,
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ExecutionEvents,
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)
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from metadata.utils.constants import AUTHORIZATION_HEADER, NO_ACCESS_TOKEN
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from metadata.utils.logger import ingestion_logger
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logger = ingestion_logger()
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from metadata.utils.helpers import clean_uri
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class SplineClient:
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"""
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Wrapper on top of Spline REST API
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"""
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# pylint: disable=too-many-arguments
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def __init__(self, config: SplineConnection):
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self.config = config
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client_config: ClientConfig = ClientConfig(
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base_url=clean_uri(self.config.hostPort),
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api_version="consumer",
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auth_header=AUTHORIZATION_HEADER,
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auth_token=lambda: (NO_ACCESS_TOKEN, 0),
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)
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self.client = REST(client_config)
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def _paginate_pipelines(self, pipelines: ExecutionEvents):
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while pipelines.pageNum * pipelines.pageSize < pipelines.totalCount:
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try:
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response = self.client.get(
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f"/execution-events?pageNum={pipelines.pageNum+1}"
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)
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pipelines = ExecutionEvents(**response)
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yield pipelines
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except Exception as exe:
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pipelines.pageNum += 1
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logger.debug(traceback.format_exc())
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logger.error(f"failed to fetch pipeline list due to: {exe}")
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def get_pipelines(self) -> List[dict]:
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"""
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Method returns the executions events as pipelines
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"""
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try:
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response = self.client.get("/execution-events")
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if response:
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pipelines = ExecutionEvents(**response)
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yield pipelines
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yield from self._paginate_pipelines(pipelines)
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except Exception as exe:
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logger.debug(traceback.format_exc())
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logger.error(f"failed to fetch pipeline list due to: {exe}")
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def get_pipelines_test_connection(self) -> List[dict]:
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"""
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Method returns the executions events as pipelines
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"""
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response = self.client.get("/execution-events")
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return ExecutionEvents(**response)
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def get_lineage_details(self, pipeline_id: str) -> List[dict]:
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"""
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Method returns the executions events as pipelines
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"""
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try:
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response = self.client.get(f"/lineage-detailed?execId={pipeline_id}")
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if response:
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return ExecutionDetail(**response)
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except Exception as exe:
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logger.debug(traceback.format_exc())
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logger.error(f"failed to fetch pipeline list due to: {exe}")
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return None
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@ -0,0 +1,54 @@
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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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Source connection handler
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"""
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from typing import Optional
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from metadata.generated.schema.entity.automations.workflow import (
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Workflow as AutomationWorkflow,
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)
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from metadata.generated.schema.entity.services.connections.pipeline.splineConnection import (
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SplineConnection,
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)
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from metadata.ingestion.connections.test_connections import test_connection_steps
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from metadata.ingestion.ometa.ometa_api import OpenMetadata
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from metadata.ingestion.source.pipeline.spline.client import SplineClient
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def get_connection(connection: SplineConnection) -> SplineClient:
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"""
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Create connection
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"""
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return SplineClient(config=connection)
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def test_connection(
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metadata: OpenMetadata,
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client: SplineClient,
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service_connection: SplineConnection,
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automation_workflow: Optional[AutomationWorkflow] = None,
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) -> None:
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"""
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Test connection. This can be executed either as part
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of a metadata workflow or during an Automation Workflow
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"""
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test_fn = {"GetPipelines": client.get_pipelines_test_connection}
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test_connection_steps(
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metadata=metadata,
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test_fn=test_fn,
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service_fqn=service_connection.type.value,
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automation_workflow=automation_workflow,
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)
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@ -0,0 +1,213 @@
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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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Spline source to extract metadata
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"""
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import traceback
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from typing import Iterable, Optional
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from metadata.generated.schema.api.data.createPipeline import CreatePipelineRequest
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from metadata.generated.schema.api.lineage.addLineage import AddLineageRequest
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from metadata.generated.schema.entity.data.pipeline import Task
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from metadata.generated.schema.entity.data.table import Table
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from metadata.generated.schema.entity.services.connections.metadata.openMetadataConnection import (
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OpenMetadataConnection,
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)
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from metadata.generated.schema.entity.services.connections.pipeline.splineConnection import (
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SplineConnection,
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)
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from metadata.generated.schema.metadataIngestion.workflow import (
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Source as WorkflowSource,
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)
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from metadata.generated.schema.type.entityLineage import EntitiesEdge, LineageDetails
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from metadata.generated.schema.type.entityReference import EntityReference
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from metadata.ingestion.api.source import InvalidSourceException
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from metadata.ingestion.models.pipeline_status import OMetaPipelineStatus
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from metadata.ingestion.source.pipeline.pipeline_service import PipelineServiceSource
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from metadata.ingestion.source.pipeline.spline.models import ExecutionEvent
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from metadata.ingestion.source.pipeline.spline.utils import (
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parse_dbfs_path,
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parse_jdbc_url,
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)
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from metadata.utils import fqn
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from metadata.utils.helpers import clean_uri
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from metadata.utils.logger import ingestion_logger
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logger = ingestion_logger()
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class SplineSource(PipelineServiceSource):
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"""
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Implements the necessary methods ot extract
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Pipeline metadata from Airflow's metadata db
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"""
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@classmethod
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def create(cls, config_dict, metadata_config: OpenMetadataConnection):
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config: WorkflowSource = WorkflowSource.parse_obj(config_dict)
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connection: SplineConnection = config.serviceConnection.__root__.config
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if not isinstance(connection, SplineConnection):
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raise InvalidSourceException(
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f"Expected SplineConnection, but got {connection}"
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)
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return cls(config, metadata_config)
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def get_connections_jobs(
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self, pipeline_details: ExecutionEvent, connection_url: str
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):
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"""
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Returns the list of tasks linked to connection
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"""
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return [
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Task(
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name=pipeline_details.executionEventId,
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displayName=pipeline_details.applicationName,
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description="",
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taskUrl=connection_url,
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)
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]
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def yield_pipeline(
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self, pipeline_details: ExecutionEvent
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) -> Iterable[CreatePipelineRequest]:
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"""
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Convert a Connection into a Pipeline Entity
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:param pipeline_details: pipeline_details object from airbyte
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:return: Create Pipeline request with tasks
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"""
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connection_url = None
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if self.service_connection.uiHostPort:
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connection_url = (
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f"{clean_uri(self.service_connection.uiHostPort)}/app/events/"
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f"overview/{pipeline_details.executionEventId}"
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)
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pipeline_request = CreatePipelineRequest(
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name=pipeline_details.executionEventId,
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displayName=pipeline_details.applicationName,
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description="",
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pipelineUrl=connection_url,
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tasks=self.get_connections_jobs(pipeline_details, connection_url),
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service=self.context.pipeline_service.fullyQualifiedName.__root__,
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)
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yield pipeline_request
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self.register_record(pipeline_request=pipeline_request)
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def yield_pipeline_status(
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self, pipeline_details: ExecutionEvent
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) -> Optional[OMetaPipelineStatus]:
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"""
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pipeline status not supported for spline connector
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"""
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def _get_table_entity(
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self, database_name: str, schema_name: str, table_name: str
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) -> Table:
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if not table_name:
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return
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for service_name in self.source_config.dbServiceNames:
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table_fqn = fqn.build(
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metadata=self.metadata,
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entity_type=Table,
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table_name=table_name,
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service_name=service_name,
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schema_name=schema_name,
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database_name=database_name,
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)
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if table_fqn:
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table_entity = self.metadata.get_by_name(entity=Table, fqn=table_fqn)
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if table_entity:
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return table_entity
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return None
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def _get_table_from_datasource_name(self, datasource: str):
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if (
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not datasource
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and not datasource.startswith("dbfs")
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and not datasource.startswith("jdbc")
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):
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return
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try:
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schema_name = None
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database_name = None
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table_name = None
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if datasource.startswith("dbfs") and "/" in datasource:
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table_name = parse_dbfs_path(datasource)
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if datasource.startswith("jdbc"):
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database_name, schema_name, table_name = parse_jdbc_url(datasource)
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|
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return self._get_table_entity(database_name, schema_name, table_name)
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||||
|
||||
except Exception as exc:
|
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logger.debug(traceback.format_exc())
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logger.warning(f"failed to parse datasource details due to: {exc}")
|
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|
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def yield_pipeline_lineage_details(
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self, pipeline_details: ExecutionEvent
|
||||
) -> Optional[Iterable[AddLineageRequest]]:
|
||||
"""
|
||||
Parse all the executions available and create lineage
|
||||
"""
|
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if not self.source_config.dbServiceNames:
|
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return
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lineage_details = self.client.get_lineage_details(
|
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pipeline_details.executionPlanId
|
||||
)
|
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if (
|
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lineage_details
|
||||
and lineage_details.executionPlan
|
||||
and lineage_details.executionPlan.inputs
|
||||
and lineage_details.executionPlan.output
|
||||
):
|
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from_entities = lineage_details.executionPlan.inputs
|
||||
to_entity = lineage_details.executionPlan.output
|
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|
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for from_entity in from_entities:
|
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from_table = (
|
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self._get_table_from_datasource_name(from_entity.source)
|
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if from_entity
|
||||
else None
|
||||
)
|
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to_table = (
|
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self._get_table_from_datasource_name(to_entity.source)
|
||||
if to_entity
|
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else None
|
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)
|
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if from_table and to_table:
|
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yield AddLineageRequest(
|
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edge=EntitiesEdge(
|
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lineageDetails=LineageDetails(
|
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pipeline=EntityReference(
|
||||
id=self.context.pipeline.id.__root__,
|
||||
type="pipeline",
|
||||
)
|
||||
),
|
||||
fromEntity=EntityReference(id=from_table.id, type="table"),
|
||||
toEntity=EntityReference(id=to_table.id, type="table"),
|
||||
)
|
||||
)
|
||||
|
||||
def get_pipelines_list(self) -> Iterable[ExecutionEvent]:
|
||||
"""
|
||||
Get List of all pipelines
|
||||
"""
|
||||
for pipelines in self.client.get_pipelines() or []:
|
||||
for pipeline in pipelines.items or []:
|
||||
yield pipeline
|
||||
|
||||
def get_pipeline_name(self, pipeline_details: ExecutionEvent) -> str:
|
||||
"""
|
||||
Get Pipeline Name for filtering
|
||||
"""
|
||||
return pipeline_details.applicationName
|
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@ -0,0 +1,46 @@
|
||||
# Copyright 2021 Collate
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
# 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.
|
||||
|
||||
from typing import List, Optional
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
class ExecutionEvent(BaseModel):
|
||||
executionEventId: Optional[str]
|
||||
executionPlanId: Optional[str]
|
||||
applicationName: Optional[str]
|
||||
|
||||
|
||||
class ExecutionEvents(BaseModel):
|
||||
items: Optional[List[ExecutionEvent]] = []
|
||||
totalCount: Optional[int] = 0
|
||||
pageNum: Optional[int] = 0
|
||||
pageSize: Optional[int] = 0
|
||||
|
||||
|
||||
class Inputs(BaseModel):
|
||||
source: Optional[str]
|
||||
|
||||
|
||||
class Output(BaseModel):
|
||||
source: Optional[str]
|
||||
|
||||
|
||||
class ExecutionPlan(BaseModel):
|
||||
_id: Optional[str]
|
||||
name: Optional[str]
|
||||
inputs: Optional[List[Inputs]] = []
|
||||
output: Optional[Output]
|
||||
|
||||
|
||||
class ExecutionDetail(BaseModel):
|
||||
executionPlan: Optional[ExecutionPlan]
|
||||
@ -0,0 +1,82 @@
|
||||
# Copyright 2021 Collate
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
# 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.
|
||||
|
||||
import traceback
|
||||
from typing import Optional, Tuple
|
||||
|
||||
from antlr4.CommonTokenStream import CommonTokenStream
|
||||
from antlr4.error.ErrorStrategy import BailErrorStrategy
|
||||
from antlr4.InputStream import InputStream
|
||||
|
||||
from metadata.generated.antlr.JdbcUriLexer import JdbcUriLexer
|
||||
from metadata.generated.antlr.JdbcUriParser import JdbcUriParser
|
||||
from metadata.utils.constants import DEFAULT_DATABASE
|
||||
from metadata.utils.logger import ingestion_logger
|
||||
|
||||
logger = ingestion_logger()
|
||||
|
||||
|
||||
MULTI_DB_SOURCE = {"postgresql", "oracle:thin", "vertica", "redshift"}
|
||||
|
||||
|
||||
def parse_dbfs_path(path: str) -> Optional[str]:
|
||||
try:
|
||||
return path.split("/")[-1]
|
||||
except Exception as exc:
|
||||
logger.warning(f"Failed to parse dbfs: {exc}")
|
||||
logger.error(traceback.format_exc())
|
||||
return None
|
||||
|
||||
|
||||
def clean_name(name: str) -> str:
|
||||
"""
|
||||
replace empty string with None
|
||||
"""
|
||||
if name:
|
||||
return name
|
||||
|
||||
|
||||
def parse_jdbc_url(url: str) -> Tuple[Optional[str], Optional[str], Optional[str]]:
|
||||
"""
|
||||
Handle parsing of jdbc url to extract table, schema and database name
|
||||
"""
|
||||
try:
|
||||
lexer = JdbcUriLexer(InputStream(url))
|
||||
stream = CommonTokenStream(lexer)
|
||||
parser = JdbcUriParser(stream)
|
||||
parser._errHandler = BailErrorStrategy() # pylint: disable=protected-acc ess
|
||||
tree = parser.jdbcUrl()
|
||||
schema_table = tree.schemaTable()
|
||||
if schema_table:
|
||||
table = (
|
||||
clean_name(schema_table.tableName().getText())
|
||||
if schema_table.tableName()
|
||||
else None
|
||||
)
|
||||
schema = (
|
||||
clean_name(schema_table.schemaName().getText())
|
||||
if schema_table.schemaName()
|
||||
else None
|
||||
)
|
||||
else:
|
||||
table, schema = None, None
|
||||
database = (
|
||||
clean_name(tree.databaseName().getText()) if tree.databaseName() else None
|
||||
)
|
||||
if tree.DATABASE_TYPE() and tree.DATABASE_TYPE().getText() in MULTI_DB_SOURCE:
|
||||
return database, schema, table
|
||||
|
||||
return DEFAULT_DATABASE, database, table
|
||||
except Exception as exc:
|
||||
logger.warning(f"Failed to parse jdbc url: {exc}")
|
||||
logger.error(traceback.format_exc())
|
||||
|
||||
return None, None, None
|
||||
187
ingestion/tests/unit/resources/datasets/spline_dataset.json
Normal file
187
ingestion/tests/unit/resources/datasets/spline_dataset.json
Normal file
@ -0,0 +1,187 @@
|
||||
{
|
||||
"execution-events": {
|
||||
"items": [
|
||||
{
|
||||
"executionEventId": "3f784e72-5bf7-5704-8828-ae8464fe915b:lhq160w0",
|
||||
"executionPlanId": "3f784e72-5bf7-5704-8828-ae8464fe915b",
|
||||
"frameworkName": "spark 3.3.2",
|
||||
"applicationName": "jdbc postgres ssl app",
|
||||
"applicationId": "local-1684226801003",
|
||||
"timestamp": 1684226827008,
|
||||
"durationNs": 8.101352417E9,
|
||||
"dataSourceName": "postgres?sslmode=disable:spline_test.filter",
|
||||
"dataSourceUri": "jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_test.filter",
|
||||
"dataSourceType": "jdbc",
|
||||
"append": true
|
||||
},
|
||||
{
|
||||
"executionEventId": "96976f56-9fe3-5bcc-a3e7-ac28781842c9:lhpygcji",
|
||||
"executionPlanId": "96976f56-9fe3-5bcc-a3e7-ac28781842c9",
|
||||
"frameworkName": "spark 3.3.2",
|
||||
"applicationName": "databricks shell",
|
||||
"applicationId": "local-1684222240845",
|
||||
"timestamp": 1684222269822,
|
||||
"durationNs": 1.0835231042E10,
|
||||
"dataSourceName": "table3",
|
||||
"dataSourceUri": "dbfs:/user/hive/warehouse/table3",
|
||||
"dataSourceType": "jdbc",
|
||||
"append": true
|
||||
}
|
||||
],
|
||||
"totalCount": 2,
|
||||
"pageNum": 1,
|
||||
"pageSize": 10,
|
||||
"totalDateRange": []
|
||||
},
|
||||
"lineage-detailed": {
|
||||
"executionPlan": {
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b",
|
||||
"name": "jdbc postgres ssl app",
|
||||
"systemInfo": {
|
||||
"name": "spark",
|
||||
"version": "3.3.2"
|
||||
},
|
||||
"agentInfo": {
|
||||
"name": "spline",
|
||||
"version": "1.1.0"
|
||||
},
|
||||
"extra": {
|
||||
"appName": "jdbc postgres ssl app",
|
||||
"attributes": [
|
||||
{
|
||||
"id": "3f784e72-5bf7-5704-8828-ae8464fe915b:attr-1",
|
||||
"name": "sample",
|
||||
"dataTypeId": "75fe27b9-9a00-5c7d-966f-33ba32333133"
|
||||
},
|
||||
{
|
||||
"id": "3f784e72-5bf7-5704-8828-ae8464fe915b:attr-0",
|
||||
"name": "id",
|
||||
"dataTypeId": "e63adadc-648a-56a0-9424-3289858cf0bb"
|
||||
},
|
||||
{
|
||||
"id": "3f784e72-5bf7-5704-8828-ae8464fe915b:attr-3",
|
||||
"name": "sample",
|
||||
"dataTypeId": "75fe27b9-9a00-5c7d-966f-33ba32333133"
|
||||
},
|
||||
{
|
||||
"id": "3f784e72-5bf7-5704-8828-ae8464fe915b:attr-2",
|
||||
"name": "id",
|
||||
"dataTypeId": "e63adadc-648a-56a0-9424-3289858cf0bb"
|
||||
},
|
||||
{
|
||||
"id": "3f784e72-5bf7-5704-8828-ae8464fe915b:attr-5",
|
||||
"name": "sample",
|
||||
"dataTypeId": "75fe27b9-9a00-5c7d-966f-33ba32333133"
|
||||
},
|
||||
{
|
||||
"id": "3f784e72-5bf7-5704-8828-ae8464fe915b:attr-4",
|
||||
"name": "id",
|
||||
"dataTypeId": "e63adadc-648a-56a0-9424-3289858cf0bb"
|
||||
}
|
||||
],
|
||||
"dataTypes": [
|
||||
{
|
||||
"_typeHint": "dt.Simple",
|
||||
"id": "e63adadc-648a-56a0-9424-3289858cf0bb",
|
||||
"name": "int",
|
||||
"nullable": true
|
||||
},
|
||||
{
|
||||
"_typeHint": "dt.Simple",
|
||||
"id": "75fe27b9-9a00-5c7d-966f-33ba32333133",
|
||||
"name": "string",
|
||||
"nullable": true
|
||||
},
|
||||
{
|
||||
"_typeHint": "dt.Simple",
|
||||
"id": "a155e715-56ab-59c4-a94b-ed1851a6984a",
|
||||
"name": "boolean",
|
||||
"nullable": true
|
||||
},
|
||||
{
|
||||
"_typeHint": "dt.Simple",
|
||||
"id": "ab4da308-91fb-550a-a5e4-beddecff2a2b",
|
||||
"name": "int",
|
||||
"nullable": false
|
||||
}
|
||||
]
|
||||
},
|
||||
"inputs": [
|
||||
{
|
||||
"sourceType": "jdbc",
|
||||
"source": "jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_demo.start"
|
||||
},
|
||||
{
|
||||
"sourceType": "jdbc",
|
||||
"source": "jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_demo.destination"
|
||||
}
|
||||
],
|
||||
"output": {
|
||||
"sourceType": "jdbc",
|
||||
"source": "jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_test.filter"
|
||||
}
|
||||
},
|
||||
"graph": {
|
||||
"nodes": [
|
||||
{
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-4",
|
||||
"_type": "Read",
|
||||
"name": "LogicalRelation",
|
||||
"properties": null
|
||||
},
|
||||
{
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-5",
|
||||
"_type": "Read",
|
||||
"name": "LogicalRelation",
|
||||
"properties": null
|
||||
},
|
||||
{
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-3",
|
||||
"_type": "Transformation",
|
||||
"name": "Union",
|
||||
"properties": null
|
||||
},
|
||||
{
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-2",
|
||||
"_type": "Transformation",
|
||||
"name": "Filter",
|
||||
"properties": null
|
||||
},
|
||||
{
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-1",
|
||||
"_type": "Transformation",
|
||||
"name": "Project",
|
||||
"properties": null
|
||||
},
|
||||
{
|
||||
"_id": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-0",
|
||||
"_type": "Write",
|
||||
"name": "SaveIntoDataSourceCommand",
|
||||
"properties": null
|
||||
}
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"source": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-4",
|
||||
"target": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-3"
|
||||
},
|
||||
{
|
||||
"source": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-5",
|
||||
"target": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-3"
|
||||
},
|
||||
{
|
||||
"source": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-3",
|
||||
"target": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-2"
|
||||
},
|
||||
{
|
||||
"source": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-2",
|
||||
"target": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-1"
|
||||
},
|
||||
{
|
||||
"source": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-1",
|
||||
"target": "3f784e72-5bf7-5704-8828-ae8464fe915b:op-0"
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
269
ingestion/tests/unit/topology/pipeline/test_spline.py
Normal file
269
ingestion/tests/unit/topology/pipeline/test_spline.py
Normal file
@ -0,0 +1,269 @@
|
||||
# Copyright 2021 Collate
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
# 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.
|
||||
"""
|
||||
Test Spline using the topology
|
||||
"""
|
||||
# pylint: disable=line-too-long
|
||||
import json
|
||||
from pathlib import Path
|
||||
from unittest import TestCase
|
||||
from unittest.mock import patch
|
||||
|
||||
from metadata.generated.schema.api.data.createPipeline import CreatePipelineRequest
|
||||
from metadata.generated.schema.entity.data.pipeline import Pipeline, Task
|
||||
from metadata.generated.schema.entity.services.pipelineService import (
|
||||
PipelineConnection,
|
||||
PipelineService,
|
||||
PipelineServiceType,
|
||||
)
|
||||
from metadata.generated.schema.metadataIngestion.workflow import (
|
||||
OpenMetadataWorkflowConfig,
|
||||
)
|
||||
from metadata.generated.schema.type.basic import FullyQualifiedEntityName
|
||||
from metadata.generated.schema.type.entityReference import EntityReference
|
||||
from metadata.ingestion.ometa.client import REST
|
||||
from metadata.ingestion.source.pipeline.spline.metadata import SplineSource
|
||||
from metadata.ingestion.source.pipeline.spline.models import (
|
||||
ExecutionDetail,
|
||||
ExecutionEvent,
|
||||
ExecutionEvents,
|
||||
ExecutionPlan,
|
||||
Inputs,
|
||||
Output,
|
||||
)
|
||||
from metadata.ingestion.source.pipeline.spline.utils import parse_jdbc_url
|
||||
from metadata.utils.constants import DEFAULT_DATABASE, UTF_8
|
||||
|
||||
mock_file_path = (
|
||||
Path(__file__).parent.parent.parent / "resources/datasets/spline_dataset.json"
|
||||
)
|
||||
with open(mock_file_path, encoding=UTF_8) as file:
|
||||
mock_data: dict = json.load(file)
|
||||
|
||||
MOCK_SPLINE_UI_URL = "http://localhost:9090"
|
||||
mock_spline_config = {
|
||||
"source": {
|
||||
"type": "spline",
|
||||
"serviceName": "spline_source",
|
||||
"serviceConnection": {
|
||||
"config": {
|
||||
"type": "Spline",
|
||||
"hostPort": "http://localhost:8080",
|
||||
"uiHostPort": MOCK_SPLINE_UI_URL,
|
||||
}
|
||||
},
|
||||
"sourceConfig": {"config": {"type": "PipelineMetadata"}},
|
||||
},
|
||||
"sink": {"type": "metadata-rest", "config": {}},
|
||||
"workflowConfig": {
|
||||
"openMetadataServerConfig": {
|
||||
"hostPort": "http://localhost:8585/api",
|
||||
"authProvider": "openmetadata",
|
||||
"securityConfig": {
|
||||
"jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
|
||||
},
|
||||
}
|
||||
},
|
||||
}
|
||||
PIPELINE_ID = "3f784e72-5bf7-5704-8828-ae8464fe915b:lhq160w0"
|
||||
MOCK_PIPELINE_URL = f"{MOCK_SPLINE_UI_URL}/app/events/overview/{PIPELINE_ID}"
|
||||
|
||||
|
||||
EXPECTED_CREATED_PIPELINES = CreatePipelineRequest(
|
||||
name=PIPELINE_ID,
|
||||
displayName="jdbc postgres ssl app",
|
||||
description="",
|
||||
pipelineUrl=MOCK_PIPELINE_URL,
|
||||
tasks=[
|
||||
Task(
|
||||
name=PIPELINE_ID,
|
||||
displayName="jdbc postgres ssl app",
|
||||
description="",
|
||||
taskUrl=MOCK_PIPELINE_URL,
|
||||
)
|
||||
],
|
||||
service=FullyQualifiedEntityName(__root__="spline_source"),
|
||||
)
|
||||
|
||||
MOCK_PIPELINE_SERVICE = PipelineService(
|
||||
id="85811038-099a-11ed-861d-0242ac120002",
|
||||
name="spline_source",
|
||||
fullyQualifiedName=FullyQualifiedEntityName(__root__="spline_source"),
|
||||
connection=PipelineConnection(),
|
||||
serviceType=PipelineServiceType.Airbyte,
|
||||
)
|
||||
|
||||
MOCK_PIPELINE = Pipeline(
|
||||
id="2aaa012e-099a-11ed-861d-0242ac120002",
|
||||
name=PIPELINE_ID,
|
||||
fullyQualifiedName=f"spline_source.{PIPELINE_ID}",
|
||||
displayName="MSSQL <> Postgres",
|
||||
description="",
|
||||
pipelineUrl=MOCK_PIPELINE_URL,
|
||||
tasks=[
|
||||
Task(
|
||||
name=PIPELINE_ID,
|
||||
displayName="jdbc postgres ssl app",
|
||||
description="",
|
||||
taskUrl=MOCK_PIPELINE_URL,
|
||||
)
|
||||
],
|
||||
service=EntityReference(
|
||||
id="85811038-099a-11ed-861d-0242ac120002", type="pipelineService"
|
||||
),
|
||||
)
|
||||
|
||||
EXPECTED_SPLINE_PIPELINES = ExecutionEvents(
|
||||
items=[
|
||||
ExecutionEvent(
|
||||
executionEventId="3f784e72-5bf7-5704-8828-ae8464fe915b:lhq160w0",
|
||||
executionPlanId="3f784e72-5bf7-5704-8828-ae8464fe915b",
|
||||
applicationName="jdbc postgres ssl app",
|
||||
),
|
||||
ExecutionEvent(
|
||||
executionEventId="96976f56-9fe3-5bcc-a3e7-ac28781842c9:lhpygcji",
|
||||
executionPlanId="96976f56-9fe3-5bcc-a3e7-ac28781842c9",
|
||||
applicationName="databricks shell",
|
||||
),
|
||||
],
|
||||
totalCount=2,
|
||||
pageNum=1,
|
||||
pageSize=10,
|
||||
)
|
||||
|
||||
EXPECTED_LINEAGE_DETAILS = ExecutionDetail(
|
||||
executionPlan=ExecutionPlan(
|
||||
_id="3f784e72-5bf7-5704-8828-ae8464fe915b",
|
||||
name="jdbc postgres ssl app",
|
||||
inputs=[
|
||||
Inputs(
|
||||
source="jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_demo.start"
|
||||
),
|
||||
Inputs(
|
||||
source="jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_demo.destination"
|
||||
),
|
||||
],
|
||||
output=Output(
|
||||
source="jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_test.filter"
|
||||
),
|
||||
)
|
||||
)
|
||||
|
||||
JDBC_PARSING_EXAMPLES = [
|
||||
(
|
||||
"jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_demo.start",
|
||||
"postgres",
|
||||
"spline_demo",
|
||||
"start",
|
||||
),
|
||||
(
|
||||
"jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_demo.destination",
|
||||
"postgres",
|
||||
"spline_demo",
|
||||
"destination",
|
||||
),
|
||||
(
|
||||
"jdbc:postgresql://localhost:5432/postgres?sslmode=disable:spline_test.filter",
|
||||
"postgres",
|
||||
"spline_test",
|
||||
"filter",
|
||||
),
|
||||
(
|
||||
"jdbc:postgresql://localhost:5432/postgres?sslmode=disable:filter",
|
||||
"postgres",
|
||||
None,
|
||||
"filter",
|
||||
),
|
||||
("jdbc:oracle:thin:@localhost:1521:test_table", None, None, "test_table"),
|
||||
(
|
||||
"jdbc:oracle:thin:@localhost:1521:test_schema.test_table",
|
||||
None,
|
||||
"test_schema",
|
||||
"test_table",
|
||||
),
|
||||
(
|
||||
"jdbc:oracle:thin:@localhost:1521/TESTDB:test_schema.test_table",
|
||||
"TESTDB",
|
||||
"test_schema",
|
||||
"test_table",
|
||||
),
|
||||
(
|
||||
"jdbc:mysql://localhost:3306/openmetadata_db?allowPublicKeyRetrieval=true&useSSL=false&serverTimezone=UTC",
|
||||
DEFAULT_DATABASE,
|
||||
"openmetadata_db",
|
||||
None,
|
||||
),
|
||||
(
|
||||
"jdbc:mysql://localhost:3306/openmetadata_db?allowPublicKeyRetrieval=true&useSSL=false&serverTimezone=UTC:filter",
|
||||
DEFAULT_DATABASE,
|
||||
"openmetadata_db",
|
||||
"filter",
|
||||
),
|
||||
("jdbc:hive2://localhost:10000/:test_tbl", DEFAULT_DATABASE, None, "test_tbl"),
|
||||
("jdbc:vertica://localhost:5432/custom_db:test_tbl", "custom_db", None, "test_tbl"),
|
||||
(
|
||||
"jdbc:vertica://localhost:5432/custom_db:schem.test_tbl",
|
||||
"custom_db",
|
||||
"schem",
|
||||
"test_tbl",
|
||||
),
|
||||
(
|
||||
"jdbc:redshift://ec2-192-168-29-1.us-east-2.compute.amazonaws.com:5432/custom_db:test_tbl",
|
||||
"custom_db",
|
||||
None,
|
||||
"test_tbl",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
class SplineUnitTest(TestCase):
|
||||
@patch(
|
||||
"metadata.ingestion.source.pipeline.pipeline_service.PipelineServiceSource.test_connection"
|
||||
)
|
||||
def __init__(self, methodName, test_connection) -> None:
|
||||
super().__init__(methodName)
|
||||
test_connection.return_value = False
|
||||
config = OpenMetadataWorkflowConfig.parse_obj(mock_spline_config)
|
||||
self.spline = SplineSource.create(
|
||||
mock_spline_config["source"],
|
||||
config.workflowConfig.openMetadataServerConfig,
|
||||
)
|
||||
self.spline.context.__dict__["pipeline"] = MOCK_PIPELINE
|
||||
self.spline.context.__dict__["pipeline_service"] = MOCK_PIPELINE_SERVICE
|
||||
|
||||
def test_client(self):
|
||||
with patch.object(REST, "get", return_value=mock_data.get("execution-events")):
|
||||
self.assertEqual(
|
||||
list(self.spline.client.get_pipelines()), [EXPECTED_SPLINE_PIPELINES]
|
||||
)
|
||||
|
||||
with patch.object(REST, "get", return_value=mock_data.get("lineage-detailed")):
|
||||
self.assertEqual(
|
||||
self.spline.client.get_lineage_details(PIPELINE_ID),
|
||||
EXPECTED_LINEAGE_DETAILS,
|
||||
)
|
||||
|
||||
def test_pipeline_name(self):
|
||||
assert (
|
||||
self.spline.get_pipeline_name(EXPECTED_SPLINE_PIPELINES.items[0])
|
||||
== EXPECTED_SPLINE_PIPELINES.items[0].applicationName
|
||||
)
|
||||
|
||||
def test_pipelines(self):
|
||||
pipline = list(self.spline.yield_pipeline(EXPECTED_SPLINE_PIPELINES.items[0]))[
|
||||
0
|
||||
]
|
||||
assert pipline == EXPECTED_CREATED_PIPELINES
|
||||
|
||||
def test_jdbc_parsing(self):
|
||||
for example in JDBC_PARSING_EXAMPLES:
|
||||
result = parse_jdbc_url(example[0])
|
||||
self.assertEqual(result, example[1:])
|
||||
@ -0,0 +1,296 @@
|
||||
---
|
||||
title: Run Spline Connector using Airflow SDK
|
||||
slug: /connectors/pipeline/spline/airflow
|
||||
---
|
||||
|
||||
# Run Spline using the Airflow SDK
|
||||
|
||||
In this section, we provide guides and references to use the Spline connector.
|
||||
|
||||
Configure and schedule Spline metadata and profiler workflows from the OpenMetadata UI:
|
||||
|
||||
- [Requirements](#requirements)
|
||||
- [Metadata Ingestion](#metadata-ingestion)
|
||||
|
||||
## Requirements
|
||||
|
||||
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
|
||||
To deploy OpenMetadata, check the Deployment guides.
|
||||
{% /inlineCallout %}
|
||||
|
||||
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
|
||||
custom Airflow plugins to handle the workflow deployment.
|
||||
|
||||
### Python Requirements
|
||||
|
||||
To run the Spline ingestion, you will need to install:
|
||||
|
||||
```bash
|
||||
pip3 install "openmetadata-ingestion"
|
||||
```
|
||||
|
||||
## Metadata Ingestion
|
||||
|
||||
All connectors are defined as JSON Schemas.
|
||||
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/pipeline/splineConnection.json)
|
||||
you can find the structure to create a connection to Spline.
|
||||
|
||||
In order to create and run a Metadata Ingestion workflow, we will follow
|
||||
the steps to create a YAML configuration able to connect to the source,
|
||||
process the Entities if needed, and reach the OpenMetadata server.
|
||||
|
||||
The workflow is modeled around the following
|
||||
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)
|
||||
|
||||
### 1. Define the YAML Config
|
||||
|
||||
This is a sample config for Spline:
|
||||
|
||||
{% codePreview %}
|
||||
|
||||
{% codeInfoContainer %}
|
||||
|
||||
#### Source Configuration - Service Connection
|
||||
|
||||
{% codeInfo srNumber=1 %}
|
||||
|
||||
**hostPort**: Spline REST Server API Host & Port, OpenMetadata uses Spline REST Server APIs to extract the execution details from spline to generate lineage. This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:8080`, `http://host.docker.internal:8080`.
|
||||
**uiHostPort**: Spline UI Host & Port is an optional field which is used for generating redirection URL from OpenMetadata to Spline Portal. This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:9090`, `http://host.docker.internal:9090`.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
|
||||
#### Source Configuration - Source Config
|
||||
|
||||
{% codeInfo srNumber=2 %}
|
||||
|
||||
The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/pipelineServiceMetadataPipeline.json):
|
||||
|
||||
**dbServiceNames**: Database Service Name for the creation of lineage, if the source supports it.
|
||||
|
||||
**includeTags**: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.
|
||||
|
||||
**markDeletedPipelines**: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.
|
||||
|
||||
**pipelineFilterPattern** and **chartFilterPattern**: Note that the `pipelineFilterPattern` and `chartFilterPattern` both support regex as include or exclude.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
|
||||
#### Sink Configuration
|
||||
|
||||
{% codeInfo srNumber=3 %}
|
||||
|
||||
To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
#### Workflow Configuration
|
||||
|
||||
{% codeInfo srNumber=4 %}
|
||||
|
||||
The main property here is the `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation.
|
||||
|
||||
For a simple, local installation using our docker containers, this looks like:
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
{% /codeInfoContainer %}
|
||||
|
||||
{% codeBlock fileName="filename.yaml" %}
|
||||
|
||||
|
||||
```yaml
|
||||
source:
|
||||
type: spline
|
||||
serviceName: spline_source
|
||||
serviceConnection:
|
||||
config:
|
||||
type: Spline
|
||||
```
|
||||
```yaml {% srNumber=1 %}
|
||||
hostPort: http://localhost:8080
|
||||
uiHostPort: http://localhost:9090
|
||||
```
|
||||
```yaml {% srNumber=2 %}
|
||||
sourceConfig:
|
||||
config:
|
||||
type: PipelineMetadata
|
||||
# markDeletedPipelines: True
|
||||
# includeTags: True
|
||||
# includeLineage: true
|
||||
# dbServiceNames:
|
||||
# - local_hive
|
||||
# pipelineFilterPattern:
|
||||
# includes:
|
||||
# - pipeline1
|
||||
# - pipeline2
|
||||
# excludes:
|
||||
# - pipeline3
|
||||
# - pipeline4
|
||||
```
|
||||
```yaml {% srNumber=3 %}
|
||||
sink:
|
||||
type: metadata-rest
|
||||
config: {}
|
||||
```
|
||||
|
||||
```yaml {% srNumber=4 %}
|
||||
workflowConfig:
|
||||
openMetadataServerConfig:
|
||||
hostPort: "http://localhost:8585/api"
|
||||
authProvider: openmetadata
|
||||
securityConfig:
|
||||
jwtToken: "{bot_jwt_token}"
|
||||
```
|
||||
|
||||
{% /codeBlock %}
|
||||
|
||||
{% /codePreview %}
|
||||
|
||||
### Workflow Configs for Security Provider
|
||||
|
||||
We support different security providers. You can find their definitions [here](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client).
|
||||
|
||||
## Openmetadata JWT Auth
|
||||
|
||||
- JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details [here](/deployment/security/enable-jwt-tokens).
|
||||
|
||||
```yaml
|
||||
workflowConfig:
|
||||
openMetadataServerConfig:
|
||||
hostPort: "http://localhost:8585/api"
|
||||
authProvider: openmetadata
|
||||
securityConfig:
|
||||
jwtToken: "{bot_jwt_token}"
|
||||
```
|
||||
|
||||
- You can refer to the JWT Troubleshooting section [link](/deployment/security/jwt-troubleshooting) for any issues in your JWT configuration. If you need information on configuring the ingestion with other security providers in your bots, you can follow this doc [link](/deployment/security/workflow-config-auth).
|
||||
|
||||
|
||||
### 2. Prepare the Ingestion DAG
|
||||
|
||||
Create a Python file in your Airflow DAGs directory with the following contents:
|
||||
|
||||
{% codePreview %}
|
||||
|
||||
{% codeInfoContainer %}
|
||||
|
||||
|
||||
{% codeInfo srNumber=5 %}
|
||||
|
||||
#### Import necessary modules
|
||||
|
||||
The `Workflow` class that is being imported is a part of a metadata ingestion framework, which defines a process of getting data from different sources and ingesting it into a central metadata repository.
|
||||
|
||||
Here we are also importing all the basic requirements to parse YAMLs, handle dates and build our DAG.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
{% codeInfo srNumber=6 %}
|
||||
|
||||
**Default arguments for all tasks in the Airflow DAG.**
|
||||
|
||||
- Default arguments dictionary contains default arguments for tasks in the DAG, including the owner's name, email address, number of retries, retry delay, and execution timeout.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
{% codeInfo srNumber=7 %}
|
||||
|
||||
- **config**: Specifies config for the metadata ingestion as we prepare above.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
{% codeInfo srNumber=8 %}
|
||||
|
||||
- **metadata_ingestion_workflow()**: This code defines a function `metadata_ingestion_workflow()` that loads a YAML configuration, creates a `Workflow` object, executes the workflow, checks its status, prints the status to the console, and stops the workflow.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
{% codeInfo srNumber=9 %}
|
||||
|
||||
- **DAG**: creates a DAG using the Airflow framework, and tune the DAG configurations to whatever fits with your requirements
|
||||
- For more Airflow DAGs creation details visit [here](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#declaring-a-dag).
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
Note that from connector to connector, this recipe will always be the same.
|
||||
By updating the `YAML configuration`, you will be able to extract metadata from different sources.
|
||||
|
||||
{% /codeInfoContainer %}
|
||||
|
||||
{% codeBlock fileName="filename.py" %}
|
||||
|
||||
```python {% srNumber=5 %}
|
||||
import pathlib
|
||||
import yaml
|
||||
from datetime import timedelta
|
||||
from airflow import DAG
|
||||
from metadata.config.common import load_config_file
|
||||
from metadata.ingestion.api.workflow import Workflow
|
||||
from airflow.utils.dates import days_ago
|
||||
|
||||
try:
|
||||
from airflow.operators.python import PythonOperator
|
||||
except ModuleNotFoundError:
|
||||
from airflow.operators.python_operator import PythonOperator
|
||||
|
||||
|
||||
```
|
||||
|
||||
```python {% srNumber=6 %}
|
||||
default_args = {
|
||||
"owner": "user_name",
|
||||
"email": ["username@org.com"],
|
||||
"email_on_failure": False,
|
||||
"retries": 3,
|
||||
"retry_delay": timedelta(minutes=5),
|
||||
"execution_timeout": timedelta(minutes=60)
|
||||
}
|
||||
|
||||
|
||||
```
|
||||
|
||||
```python {% srNumber=7 %}
|
||||
config = """
|
||||
<your YAML configuration>
|
||||
"""
|
||||
|
||||
|
||||
```
|
||||
|
||||
```python {% srNumber=8 %}
|
||||
def metadata_ingestion_workflow():
|
||||
workflow_config = yaml.safe_load(config)
|
||||
workflow = Workflow.create(workflow_config)
|
||||
workflow.execute()
|
||||
workflow.raise_from_status()
|
||||
workflow.print_status()
|
||||
workflow.stop()
|
||||
|
||||
|
||||
```
|
||||
|
||||
```python {% srNumber=9 %}
|
||||
with DAG(
|
||||
"sample_data",
|
||||
default_args=default_args,
|
||||
description="An example DAG which runs a OpenMetadata ingestion workflow",
|
||||
start_date=days_ago(1),
|
||||
is_paused_upon_creation=False,
|
||||
schedule_interval='*/5 * * * *',
|
||||
catchup=False,
|
||||
) as dag:
|
||||
ingest_task = PythonOperator(
|
||||
task_id="ingest_using_recipe",
|
||||
python_callable=metadata_ingestion_workflow,
|
||||
)
|
||||
|
||||
|
||||
```
|
||||
|
||||
{% /codeBlock %}
|
||||
|
||||
{% /codePreview %}
|
||||
|
||||
|
||||
@ -0,0 +1,182 @@
|
||||
---
|
||||
title: Run Spline Connector using the CLI
|
||||
slug: /connectors/pipeline/spline/cli
|
||||
---
|
||||
|
||||
# Run Spline using the metadata CLI
|
||||
|
||||
In this section, we provide guides and references to use the Spline connector.
|
||||
|
||||
Configure and schedule Spline metadata and profiler workflows from the OpenMetadata UI:
|
||||
|
||||
- [Requirements](#requirements)
|
||||
- [Metadata Ingestion](#metadata-ingestion)
|
||||
|
||||
## Requirements
|
||||
|
||||
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
|
||||
To deploy OpenMetadata, check the Deployment guides.
|
||||
{% /inlineCallout %}
|
||||
|
||||
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
|
||||
custom Airflow plugins to handle the workflow deployment.
|
||||
|
||||
### Python Requirements
|
||||
|
||||
To run the Spline ingestion, you will need to install:
|
||||
|
||||
```bash
|
||||
pip3 install "openmetadata-ingestion"
|
||||
```
|
||||
|
||||
## Metadata Ingestion
|
||||
|
||||
All connectors are defined as JSON Schemas.
|
||||
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/pipeline/splineConnection.json)
|
||||
you can find the structure to create a connection to Spline.
|
||||
|
||||
In order to create and run a Metadata Ingestion workflow, we will follow
|
||||
the steps to create a YAML configuration able to connect to the source,
|
||||
process the Entities if needed, and reach the OpenMetadata server.
|
||||
|
||||
The workflow is modeled around the following
|
||||
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)
|
||||
|
||||
### 1. Define the YAML Config
|
||||
|
||||
This is a sample config for Spline:
|
||||
|
||||
{% codePreview %}
|
||||
|
||||
{% codeInfoContainer %}
|
||||
|
||||
#### Source Configuration - Service Connection
|
||||
|
||||
{% codeInfo srNumber=1 %}
|
||||
|
||||
**hostPort**: Spline REST Server API Host & Port, OpenMetadata uses Spline REST Server APIs to extract the execution details from spline to generate lineage. This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:8080`, `http://host.docker.internal:8080`.
|
||||
|
||||
**uiHostPort**: Spline UI Host & Port is an optional field which is used for generating redirection URL from OpenMetadata to Spline Portal. This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:9090`, `http://host.docker.internal:9090`.
|
||||
|
||||
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
|
||||
#### Source Configuration - Source Config
|
||||
|
||||
{% codeInfo srNumber=2 %}
|
||||
|
||||
The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/pipelineServiceMetadataPipeline.json):
|
||||
|
||||
**dbServiceNames**: Database Service Name for the creation of lineage, if the source supports it.
|
||||
|
||||
**includeTags**: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.
|
||||
|
||||
**markDeletedPipelines**: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.
|
||||
|
||||
**pipelineFilterPattern** and **chartFilterPattern**: Note that the `pipelineFilterPattern` and `chartFilterPattern` both support regex as include or exclude.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
|
||||
#### Sink Configuration
|
||||
|
||||
{% codeInfo srNumber=3 %}
|
||||
|
||||
To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
#### Workflow Configuration
|
||||
|
||||
{% codeInfo srNumber=4 %}
|
||||
|
||||
The main property here is the `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation.
|
||||
|
||||
For a simple, local installation using our docker containers, this looks like:
|
||||
|
||||
{% /codeInfo %}
|
||||
|
||||
{% /codeInfoContainer %}
|
||||
|
||||
{% codeBlock fileName="filename.yaml" %}
|
||||
|
||||
|
||||
```yaml
|
||||
source:
|
||||
type: spline
|
||||
serviceName: spline_source
|
||||
serviceConnection:
|
||||
config:
|
||||
type: Spline
|
||||
```
|
||||
```yaml {% srNumber=1 %}
|
||||
hostPort: http://localhost:8080
|
||||
uiHostPort: http://localhost:9090
|
||||
```
|
||||
```yaml {% srNumber=2 %}
|
||||
sourceConfig:
|
||||
config:
|
||||
type: PipelineMetadata
|
||||
# markDeletedPipelines: True
|
||||
# includeTags: True
|
||||
# includeLineage: true
|
||||
# dbServiceNames:
|
||||
# - local_hive
|
||||
# pipelineFilterPattern:
|
||||
# includes:
|
||||
# - pipeline1
|
||||
# - pipeline2
|
||||
# excludes:
|
||||
# - pipeline3
|
||||
# - pipeline4
|
||||
```
|
||||
```yaml {% srNumber=3 %}
|
||||
sink:
|
||||
type: metadata-rest
|
||||
config: {}
|
||||
```
|
||||
|
||||
```yaml {% srNumber=4 %}
|
||||
workflowConfig:
|
||||
openMetadataServerConfig:
|
||||
hostPort: "http://localhost:8585/api"
|
||||
authProvider: openmetadata
|
||||
securityConfig:
|
||||
jwtToken: "{bot_jwt_token}"
|
||||
```
|
||||
|
||||
{% /codeBlock %}
|
||||
|
||||
{% /codePreview %}
|
||||
|
||||
### Workflow Configs for Security Provider
|
||||
|
||||
We support different security providers. You can find their definitions [here](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client).
|
||||
|
||||
## Openmetadata JWT Auth
|
||||
|
||||
- JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details [here](/deployment/security/enable-jwt-tokens).
|
||||
|
||||
```yaml
|
||||
workflowConfig:
|
||||
openMetadataServerConfig:
|
||||
hostPort: "http://localhost:8585/api"
|
||||
authProvider: openmetadata
|
||||
securityConfig:
|
||||
jwtToken: "{bot_jwt_token}"
|
||||
```
|
||||
|
||||
- You can refer to the JWT Troubleshooting section [link](/deployment/security/jwt-troubleshooting) for any issues in your JWT configuration. If you need information on configuring the ingestion with other security providers in your bots, you can follow this doc [link](/deployment/security/workflow-config-auth).
|
||||
|
||||
### 2. Run with the CLI
|
||||
|
||||
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
|
||||
|
||||
```bash
|
||||
metadata ingest -c <path-to-yaml>
|
||||
```
|
||||
|
||||
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
|
||||
you will be able to extract metadata from different sources.
|
||||
@ -0,0 +1,291 @@
|
||||
---
|
||||
title: Spline
|
||||
slug: /connectors/pipeline/spline
|
||||
---
|
||||
|
||||
# Spline
|
||||
|
||||
In this section, we provide guides and references to use the Spline connector.
|
||||
|
||||
Configure and schedule Spline metadata and profiler workflows from the OpenMetadata UI:
|
||||
|
||||
- [Requirements](#requirements)
|
||||
- [Metadata Ingestion](#metadata-ingestion)
|
||||
|
||||
If you don't want to use the OpenMetadata Ingestion container to configure the workflows via the UI, then you can check
|
||||
the following docs to connect using Airflow SDK or with the CLI.
|
||||
|
||||
{% tilesContainer %}
|
||||
{% tile
|
||||
title="Ingest with Airflow"
|
||||
description="Configure the ingestion using Airflow SDK"
|
||||
link="/connectors/pipeline/spline/airflow"
|
||||
/ %}
|
||||
{% tile
|
||||
title="Ingest with the CLI"
|
||||
description="Run a one-time ingestion using the metadata CLI"
|
||||
link="/connectors/pipeline/spline/cli"
|
||||
/ %}
|
||||
|
||||
{% /tilesContainer %}
|
||||
|
||||
## Requirements
|
||||
|
||||
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
|
||||
To deploy OpenMetadata, check the Deployment guides.
|
||||
{% /inlineCallout %}
|
||||
|
||||
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
|
||||
custom Airflow plugins to handle the workflow deployment.
|
||||
|
||||
## Metadata Ingestion
|
||||
|
||||
{% stepsContainer %}
|
||||
|
||||
{% step srNumber=1 %}
|
||||
|
||||
{% stepDescription title="1. Visit the Services Page" %}
|
||||
|
||||
The first step is ingesting the metadata from your sources. Under
|
||||
Settings, you will find a Services link an external source system to
|
||||
OpenMetadata. Once a service is created, it can be used to configure
|
||||
metadata, usage, and profiler workflows.
|
||||
|
||||
To visit the Services page, select Services from the Settings menu.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.0.0/connectors/visit-services.png"
|
||||
alt="Visit Services Page"
|
||||
caption="Find Dashboard option on left panel of the settings page" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% step srNumber=2 %}
|
||||
|
||||
{% stepDescription title="2. Create a New Service" %}
|
||||
|
||||
Click on the 'Add New Service' button to start the Service creation.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.0.0/connectors/create-service.png"
|
||||
alt="Create a new service"
|
||||
caption="Add a new Service from the Dashboard Services page" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
|
||||
|
||||
{% step srNumber=3 %}
|
||||
|
||||
{% stepDescription title="3. Select the Service Type" %}
|
||||
|
||||
Select Spline as the service type and click Next.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.1.0/connectors/spline/select-service.png"
|
||||
alt="Select Service"
|
||||
caption="Select your service from the list" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% step srNumber=4 %}
|
||||
|
||||
{% stepDescription title="4. Name and Describe your Service" %}
|
||||
|
||||
Provide a name and description for your service as illustrated below.
|
||||
|
||||
#### Service Name
|
||||
|
||||
OpenMetadata uniquely identifies services by their Service Name. Provide
|
||||
a name that distinguishes your deployment from other services, including
|
||||
the other {connector} services that you might be ingesting metadata
|
||||
from.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.1.0/connectors/spline/add-new-service.png"
|
||||
alt="Add New Service"
|
||||
caption="Provide a Name and description for your Service" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% step srNumber=5 %}
|
||||
|
||||
{% stepDescription title="5. Configure the Service Connection" %}
|
||||
|
||||
In this step, we will configure the connection settings required for
|
||||
this connector. Please follow the instructions below to ensure that
|
||||
you've configured the connector to read from your spline service as
|
||||
desired.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.1.0/connectors/spline/service-connection.png"
|
||||
alt="Configure service connection"
|
||||
caption="Configure the service connection by filling the form" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% extraContent parentTagName="stepsContainer" %}
|
||||
|
||||
#### Connection Options
|
||||
|
||||
- **Spline REST Server Host & Port**: OpenMetadata uses Spline REST Server APIs to extract the execution details from spline to generate lineage. This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:8080`, `http://host.docker.internal:8080`.
|
||||
|
||||
- **Spline UI Host & Port**: Spline UI Host & Port is an optional field which is used for generating redirection URL from OpenMetadata to Spline Portal. This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:9090`, `http://host.docker.internal:9090`.
|
||||
|
||||
{% /extraContent %}
|
||||
|
||||
{% step srNumber=6 %}
|
||||
|
||||
{% stepDescription title="6. Test the Connection" %}
|
||||
|
||||
Once the credentials have been added, click on `Test Connection` and Save
|
||||
the changes.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.0.0/connectors/test-connection.png"
|
||||
alt="Test Connection"
|
||||
caption="Test the connection and save the Service" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% step srNumber=7 %}
|
||||
|
||||
{% stepDescription title="7. Configure Metadata Ingestion" %}
|
||||
|
||||
In this step we will configure the metadata ingestion pipeline,
|
||||
Please follow the instructions below
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.1.0/connectors/configure-metadata-ingestion-pipeline.png"
|
||||
alt="Configure Metadata Ingestion"
|
||||
caption="Configure Metadata Ingestion Page" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% extraContent parentTagName="stepsContainer" %}
|
||||
|
||||
#### Metadata Ingestion Options
|
||||
|
||||
- **Name**: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.
|
||||
- **Pipeline Filter Pattern (Optional)**: Use to pipeline filter patterns to control whether or not to include pipeline as part of metadata ingestion.
|
||||
- **Include**: Explicitly include pipeline by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all pipeline with names matching one or more of the supplied regular expressions. All other schemas will be excluded.
|
||||
- **Exclude**: Explicitly exclude pipeline by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all pipeline with names matching one or more of the supplied regular expressions. All other schemas will be included.
|
||||
- **Database Service Name (Optional)**: Enter the name of Database Service which is already ingested in OpenMetadata to create lineage between dashboards and database tables.
|
||||
- **Include lineage (toggle)**: Set the Include lineage toggle to control whether or not to include lineage between pipelines and data sources as part of metadata ingestion.
|
||||
- **Enable Debug Log (toggle)**: Set the Enable Debug Log toggle to set the default log level to debug, these logs can be viewed later in Airflow.
|
||||
- **Mark Deleted Pipelines (toggle)**: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.
|
||||
|
||||
{% /extraContent %}
|
||||
|
||||
{% step srNumber=8 %}
|
||||
|
||||
{% stepDescription title="8. Schedule the Ingestion and Deploy" %}
|
||||
|
||||
Scheduling can be set up at an hourly, daily, weekly, or manual cadence. The
|
||||
timezone is in UTC. Select a Start Date to schedule for ingestion. It is
|
||||
optional to add an End Date.
|
||||
|
||||
Review your configuration settings. If they match what you intended,
|
||||
click Deploy to create the service and schedule metadata ingestion.
|
||||
|
||||
If something doesn't look right, click the Back button to return to the
|
||||
appropriate step and change the settings as needed.
|
||||
|
||||
After configuring the workflow, you can click on Deploy to create the
|
||||
pipeline.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.0.0/connectors/schedule.png"
|
||||
alt="Schedule the Workflow"
|
||||
caption="Schedule the Ingestion Pipeline and Deploy" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
|
||||
{% step srNumber=9 %}
|
||||
|
||||
{% stepDescription title="9. View the Ingestion Pipeline" %}
|
||||
|
||||
Once the workflow has been successfully deployed, you can view the
|
||||
Ingestion Pipeline running from the Service Page.
|
||||
|
||||
{% /stepDescription %}
|
||||
|
||||
{% stepVisualInfo %}
|
||||
|
||||
{% image
|
||||
src="/images/v1.0.0/connectors/view-ingestion-pipeline.png"
|
||||
alt="View Ingestion Pipeline"
|
||||
caption="View the Ingestion Pipeline from the Service Page" /%}
|
||||
|
||||
{% /stepVisualInfo %}
|
||||
|
||||
{% /step %}
|
||||
|
||||
{% /stepsContainer %}
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Workflow Deployment Error
|
||||
|
||||
If there were any errors during the workflow deployment process, the
|
||||
Ingestion Pipeline Entity will still be created, but no workflow will be
|
||||
present in the Ingestion container.
|
||||
|
||||
- You can then edit the Ingestion Pipeline and Deploy it again.
|
||||
|
||||
- From the Connection tab, you can also Edit the Service if needed.
|
||||
|
||||
{% image
|
||||
src="/images/v1.0.0/connectors/workflow-deployment-error.png"
|
||||
alt="Workflow Deployment Error"
|
||||
caption="Edit and Deploy the Ingestion Pipeline" /%}
|
||||
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 110 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 152 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 93 KiB |
@ -64,6 +64,7 @@ OpenMetadata can extract metadata from the following list of 55 connectors:
|
||||
- [Glue](/connectors/pipeline/glue-pipeline)
|
||||
- [Domo Pipeline](/connectors/pipeline/domo-pipeline)
|
||||
- [NiFi](/connectors/pipeline/nifi)
|
||||
- [Spline](/connectors/pipeline/spline)
|
||||
|
||||
## ML Model Services
|
||||
|
||||
|
||||
@ -15,6 +15,7 @@ This is the supported list of connectors for Pipeline Services:
|
||||
- [Domo Pipeline](/connectors/pipeline/domo-pipeline)
|
||||
- [Databricks Pipeline](/connectors/pipeline/databricks-pipeline)
|
||||
- [NiFi](/connectors/pipeline/nifi)
|
||||
- [Spline](/connectors/pipeline/spline)
|
||||
|
||||
If you have a request for a new connector, don't hesitate to reach out in [Slack](https://slack.open-metadata.org/) or
|
||||
open a [feature request](https://github.com/open-metadata/OpenMetadata/issues/new/choose) in our GitHub repo.
|
||||
|
||||
@ -525,6 +525,12 @@ site_menu:
|
||||
url: /connectors/pipeline/domo-pipeline/airflow
|
||||
- category: Connectors / Pipeline / Domo Pipeline / CLI
|
||||
url: /connectors/pipeline/domo-pipeline/cli
|
||||
- category: Connectors / Pipeline / Spline
|
||||
url: /connectors/pipeline/spline
|
||||
- category: Connectors / Pipeline / Spline / Airflow
|
||||
url: /connectors/pipeline/spline/airflow
|
||||
- category: Connectors / Pipeline / Spline / CLI
|
||||
url: /connectors/pipeline/spline/cli
|
||||
|
||||
- category: Connectors / ML Model
|
||||
url: /connectors/ml-model
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 161 KiB After Width: | Height: | Size: 117 KiB |
@ -0,0 +1,15 @@
|
||||
{
|
||||
"name": "Spline",
|
||||
"fullyQualifiedName": "Spline",
|
||||
"displayName": "Spline Test Connection",
|
||||
"description": "This Test Connection validates the access against the server and basic metadata extraction of pipelines.",
|
||||
"steps": [
|
||||
{
|
||||
"name": "GetPipelines",
|
||||
"description": "List all execution events",
|
||||
"errorMessage": "Failed to fetch pipelines, please validate the credentials",
|
||||
"shortCircuit": true,
|
||||
"mandatory": true
|
||||
}
|
||||
]
|
||||
}
|
||||
@ -0,0 +1,99 @@
|
||||
grammar JdbcUri;
|
||||
|
||||
jdbcUrl
|
||||
: 'jdbc:' DATABASE_TYPE serverName? PORT_NUMBER? ('/' databaseName)? (CONNECTION_ARG_INIT CONNECTION_ARG (AMP CONNECTION_ARG)*)? schemaTable?
|
||||
;
|
||||
|
||||
schemaTable
|
||||
: COLON (schemaName PERIOD)? tableName
|
||||
;
|
||||
|
||||
databaseName
|
||||
: IDENTIFIER?
|
||||
;
|
||||
|
||||
schemaName
|
||||
: IDENTIFIER
|
||||
;
|
||||
|
||||
tableName
|
||||
: IDENTIFIER
|
||||
;
|
||||
|
||||
|
||||
DATABASE_TYPE
|
||||
: 'mysql'
|
||||
| 'postgresql'
|
||||
| 'oracle:thin'
|
||||
| 'clickhouse'
|
||||
| 'trino'
|
||||
| 'presto'
|
||||
| 'vertica'
|
||||
| 'hive2'
|
||||
| 'redshift'
|
||||
;
|
||||
|
||||
URI_SEPARATOR
|
||||
: '://'
|
||||
| ':@//'
|
||||
| ':@'
|
||||
;
|
||||
|
||||
serverName
|
||||
: HOST_NAME
|
||||
| IPV4_ADDRESS
|
||||
| IPV6_ADDRESS
|
||||
| URI_SEPARATOR IDENTIFIER
|
||||
| URI_SEPARATOR
|
||||
;
|
||||
|
||||
PORT_NUMBER
|
||||
: COLON [0-9]+
|
||||
;
|
||||
|
||||
IDENTIFIER
|
||||
: [a-zA-Z][a-zA-Z0-9_]*
|
||||
;
|
||||
|
||||
|
||||
HOST_NAME
|
||||
: URI_SEPARATOR [a-zA-Z][a-zA-Z0-9.-]*[a-zA-Z0-9]
|
||||
;
|
||||
|
||||
|
||||
IPV4_ADDRESS
|
||||
: URI_SEPARATOR [0-9]+ PERIOD [0-9]+ PERIOD [0-9]+ PERIOD [0-9]+
|
||||
;
|
||||
|
||||
IPV6_ADDRESS
|
||||
: URI_SEPARATOR '[' HEXDIGIT+ (COLON HEXDIGIT+)* (COLON IPV4_ADDRESS)? ']'
|
||||
;
|
||||
|
||||
HEXDIGIT
|
||||
: [0-9a-fA-F]
|
||||
;
|
||||
|
||||
CONNECTION_ARG
|
||||
: IDENTIFIER '=' IDENTIFIER
|
||||
;
|
||||
|
||||
CONNECTION_ARG_INIT
|
||||
: '?'
|
||||
;
|
||||
|
||||
PERIOD
|
||||
: '.'
|
||||
;
|
||||
|
||||
COLON
|
||||
: ':'
|
||||
;
|
||||
|
||||
AMP
|
||||
: '&'
|
||||
;
|
||||
|
||||
WS
|
||||
: [ \t\r\n]+ -> skip
|
||||
;
|
||||
|
||||
@ -0,0 +1,45 @@
|
||||
{
|
||||
"$id": "https://open-metadata.org/schema/entity/services/connections/pipeline/splineConnection.json",
|
||||
"$schema": "http://json-schema.org/draft-07/schema#",
|
||||
"title": "SplineConnection",
|
||||
"description": "Spline Metadata Database Connection Config",
|
||||
"type": "object",
|
||||
"javaType": "org.openmetadata.schema.services.connections.pipeline.SplineConnection",
|
||||
"definitions": {
|
||||
"SplineType": {
|
||||
"description": "Service type.",
|
||||
"type": "string",
|
||||
"enum": ["Spline"],
|
||||
"default": "Spline"
|
||||
}
|
||||
},
|
||||
"properties": {
|
||||
"type": {
|
||||
"title": "Service Type",
|
||||
"description": "Service Type",
|
||||
"$ref": "#/definitions/SplineType",
|
||||
"default": "Spline"
|
||||
},
|
||||
"hostPort": {
|
||||
"title": "Spline REST Server Host & Port",
|
||||
"expose": true,
|
||||
"description": "Spline REST Server Host & Port.",
|
||||
"type": "string",
|
||||
"format": "uri"
|
||||
},
|
||||
"uiHostPort": {
|
||||
"title": "Spline UI Host & Port",
|
||||
"expose": true,
|
||||
"description": "Spline UI Host & Port.",
|
||||
"type": "string",
|
||||
"format": "uri"
|
||||
},
|
||||
"supportsMetadataExtraction": {
|
||||
"title": "Supports Metadata Extraction",
|
||||
"$ref": "../connectionBasicType.json#/definitions/supportsMetadataExtraction"
|
||||
}
|
||||
},
|
||||
"additionalProperties": false,
|
||||
"required": ["hostPort"]
|
||||
}
|
||||
|
||||
@ -25,7 +25,8 @@
|
||||
"Nifi",
|
||||
"DomoPipeline",
|
||||
"CustomPipeline",
|
||||
"DatabricksPipeline"
|
||||
"DatabricksPipeline",
|
||||
"Spline"
|
||||
],
|
||||
"javaEnums": [
|
||||
{
|
||||
@ -54,6 +55,9 @@
|
||||
},
|
||||
{
|
||||
"name": "DatabricksPipeline"
|
||||
},
|
||||
{
|
||||
"name": "Spline"
|
||||
}
|
||||
]
|
||||
},
|
||||
@ -94,6 +98,9 @@
|
||||
},
|
||||
{
|
||||
"$ref": "./connections/pipeline/databricksPipelineConnection.json"
|
||||
},
|
||||
{
|
||||
"$ref": "./connections/pipeline/splineConnection.json"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
@ -26,6 +26,11 @@
|
||||
"description": "Regex exclude pipelines.",
|
||||
"$ref": "../type/filterPattern.json#/definitions/filterPattern"
|
||||
},
|
||||
"dbServiceNames": {
|
||||
"title": "Database Service Names List",
|
||||
"description": "List of Database Service Names for creation of lineage",
|
||||
"type": "array"
|
||||
},
|
||||
"markDeletedPipelines": {
|
||||
"description": "Optional configuration to soft delete Pipelines in OpenMetadata if the source Pipelines are deleted. Also, if the Pipeline is deleted, all the associated entities like lineage, etc., with that Pipeline will be deleted",
|
||||
"type": "boolean",
|
||||
|
||||
@ -0,0 +1,27 @@
|
||||
# Spline
|
||||
|
||||
In this section, we provide guides and references to use the Spline connector. You can view the full documentation for Spline [here](https://docs.open-metadata.org/connectors/pipeline/spline).
|
||||
|
||||
## Requirements
|
||||
|
||||
We extract Spline's metadata by using its [API](https://absaoss.github.io/spline/).
|
||||
|
||||
## Connection Details
|
||||
|
||||
$$section
|
||||
### Spline REST Server Host & Port $(id="hostPort")
|
||||
|
||||
OpenMetadata uses Spline REST Server APIs to extract the execution details from spline to generate lineage.
|
||||
|
||||
This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:8080`, `http://host.docker.internal:8080`.
|
||||
|
||||
|
||||
$$
|
||||
|
||||
$$section
|
||||
### Spline UI Host & Port $(id="uiHostPort")
|
||||
|
||||
Spline UI Host & Port is an optional field which is used for generating redirection URL from OpenMetadata to Spline Portal.
|
||||
|
||||
This should be specified as a URI string in the format `scheme://hostname:port`. E.g., `http://localhost:9090`, `http://host.docker.internal:9090`.
|
||||
$$
|
||||
@ -21,6 +21,16 @@ For example, to exclude all Pipelines with the name containing the word `demo`,
|
||||
Checkout [this](https://docs.open-metadata.org/connectors/ingestion/workflows/metadata/filter-patterns/database#database-filter-pattern) document for further examples on filter patterns.
|
||||
$$
|
||||
|
||||
$$section
|
||||
### Database Service Name $(id="dbServiceNames")
|
||||
|
||||
When processing Pipelines we can extract information about the inlet and the outlet tables.
|
||||
|
||||
In order to create the lineage between the inlet and the outlet tables, we need to know where to look for such tables.
|
||||
|
||||
You can enter a list of Database Services that are hosting the inlet and the outlet tables.
|
||||
$$
|
||||
|
||||
$$section
|
||||
### Include Lineage $(id="includeLineage")
|
||||
|
||||
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 57 KiB |
@ -456,6 +456,7 @@ const AddIngestion = ({
|
||||
pipelineFilterPattern,
|
||||
showPipelineFilter
|
||||
),
|
||||
dbServiceNames: databaseServiceNames,
|
||||
type: ConfigType.PipelineMetadata,
|
||||
markDeletedPipelines,
|
||||
includeTags,
|
||||
|
||||
@ -429,6 +429,29 @@ const ConfigureIngestion = ({
|
||||
},
|
||||
};
|
||||
|
||||
const dbServiceNamesField: FieldProp = {
|
||||
name: 'dbServiceNames',
|
||||
label: t('label.database-service-name'),
|
||||
type: FieldTypes.SELECT,
|
||||
required: false,
|
||||
id: 'root/dbServiceNames',
|
||||
hasSeparator: true,
|
||||
props: {
|
||||
allowClear: true,
|
||||
'data-testid': 'name',
|
||||
mode: 'tags',
|
||||
placeholder: t('label.add-entity', {
|
||||
entity: t('label.database-service-name'),
|
||||
}),
|
||||
style: { width: '100%' },
|
||||
value: databaseServiceNames,
|
||||
onChange: handleDashBoardServiceNames,
|
||||
},
|
||||
formItemProps: {
|
||||
initialValue: databaseServiceNames,
|
||||
},
|
||||
};
|
||||
|
||||
const databaseMetadataFields: FieldProp[] = [
|
||||
...databaseServiceFilterPatternFields,
|
||||
{
|
||||
@ -569,28 +592,7 @@ const ConfigureIngestion = ({
|
||||
id: 'root/dataModelFilterPattern',
|
||||
hasSeparator: true,
|
||||
},
|
||||
{
|
||||
name: 'dbServiceNames',
|
||||
label: t('label.database-service-name'),
|
||||
type: FieldTypes.SELECT,
|
||||
required: false,
|
||||
id: 'root/dbServiceNames',
|
||||
hasSeparator: true,
|
||||
props: {
|
||||
allowClear: true,
|
||||
'data-testid': 'name',
|
||||
mode: 'tags',
|
||||
placeholder: t('label.add-entity', {
|
||||
entity: t('label.database-service-name'),
|
||||
}),
|
||||
style: { width: '100%' },
|
||||
value: databaseServiceNames,
|
||||
onChange: handleDashBoardServiceNames,
|
||||
},
|
||||
formItemProps: {
|
||||
initialValue: databaseServiceNames,
|
||||
},
|
||||
},
|
||||
dbServiceNamesField,
|
||||
loggerLevelField,
|
||||
{
|
||||
name: 'includeOwners',
|
||||
@ -705,6 +707,7 @@ const ConfigureIngestion = ({
|
||||
id: 'root/pipelineFilterPattern',
|
||||
hasSeparator: true,
|
||||
},
|
||||
dbServiceNamesField,
|
||||
{
|
||||
name: 'includeLineage',
|
||||
label: t('label.include-entity', {
|
||||
|
||||
@ -13,11 +13,13 @@
|
||||
|
||||
import { Badge, Button, Col, Row, Select, Space } from 'antd';
|
||||
import classNames from 'classnames';
|
||||
import { DatabaseServiceType } from 'generated/entity/data/table';
|
||||
import { DatabaseServiceType } from 'generated/entity/data/database';
|
||||
import { PipelineServiceType } from 'generated/entity/services/pipelineService';
|
||||
import { startCase } from 'lodash';
|
||||
import React, { useEffect, useMemo, useState } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import {
|
||||
BETA_SERVICES,
|
||||
excludedService,
|
||||
serviceTypes,
|
||||
SERVICE_CATEGORY_OPTIONS,
|
||||
@ -134,15 +136,15 @@ const SelectServiceType = ({
|
||||
</div>
|
||||
<p className="break-word text-center">
|
||||
{type.includes('Custom') ? startCase(type) : type}
|
||||
{type === DatabaseServiceType.Impala ? (
|
||||
{BETA_SERVICES.includes(
|
||||
type as DatabaseServiceType | PipelineServiceType
|
||||
) ? (
|
||||
<Badge
|
||||
className="service-beta-tag"
|
||||
color="#7147E8"
|
||||
count={t('label.beta')}
|
||||
/>
|
||||
) : (
|
||||
''
|
||||
)}
|
||||
) : null}
|
||||
</p>
|
||||
</Space>
|
||||
</Col>
|
||||
|
||||
@ -250,7 +250,9 @@ const ServiceConnectionDetails = ({
|
||||
<div
|
||||
className="d-flex flex-wrap p-xss"
|
||||
data-testid="service-connection-details">
|
||||
<Row gutter={[8, 8]}>{data}</Row>
|
||||
<Row className="w-full" gutter={[8, 8]}>
|
||||
{data}
|
||||
</Row>
|
||||
</div>
|
||||
</Card>
|
||||
);
|
||||
|
||||
@ -68,6 +68,7 @@ import salesforce from '../assets/img/service-icon-salesforce.png';
|
||||
import scikit from '../assets/img/service-icon-scikit.png';
|
||||
import singlestore from '../assets/img/service-icon-singlestore.png';
|
||||
import snowflakes from '../assets/img/service-icon-snowflakes.png';
|
||||
import spline from '../assets/img/service-icon-spline.png';
|
||||
import mysql from '../assets/img/service-icon-sql.png';
|
||||
import sqlite from '../assets/img/service-icon-sqlite.png';
|
||||
import superset from '../assets/img/service-icon-superset.png';
|
||||
@ -165,6 +166,7 @@ export const SAGEMAKER = sagemaker;
|
||||
export const AMAZON_S3 = amazonS3;
|
||||
export const GCS = gcs;
|
||||
export const MS_AZURE = msAzure;
|
||||
export const SPLINE = spline;
|
||||
|
||||
export const PLUS = plus;
|
||||
export const NOSERVICE = noService;
|
||||
@ -339,3 +341,8 @@ export const SERVICE_TYPE_MAP = {
|
||||
[ServiceCategory.STORAGE_SERVICES]: ServiceType.Storage,
|
||||
[ServiceCategory.PIPELINE_SERVICES]: ServiceType.Pipeline,
|
||||
};
|
||||
|
||||
export const BETA_SERVICES = [
|
||||
DatabaseServiceType.Impala,
|
||||
PipelineServiceType.Spline,
|
||||
];
|
||||
|
||||
@ -25,6 +25,7 @@ import domoPipelineConnection from '../jsons/connectionSchemas/connections/pipel
|
||||
import fivetranConnection from '../jsons/connectionSchemas/connections/pipeline/fivetranConnection.json';
|
||||
import gluePipelineConnection from '../jsons/connectionSchemas/connections/pipeline/gluePipelineConnection.json';
|
||||
import nifiConnection from '../jsons/connectionSchemas/connections/pipeline/nifiConnection.json';
|
||||
import splineConnection from '../jsons/connectionSchemas/connections/pipeline/splineConnection.json';
|
||||
|
||||
export const getPipelineConfig = (type: PipelineServiceType) => {
|
||||
let schema = {};
|
||||
@ -76,6 +77,11 @@ export const getPipelineConfig = (type: PipelineServiceType) => {
|
||||
|
||||
break;
|
||||
}
|
||||
case PipelineServiceType.Spline: {
|
||||
schema = splineConnection;
|
||||
|
||||
break;
|
||||
}
|
||||
|
||||
default:
|
||||
break;
|
||||
|
||||
@ -92,6 +92,7 @@ import {
|
||||
SERVICE_TYPE_MAP,
|
||||
SINGLESTORE,
|
||||
SNOWFLAKE,
|
||||
SPLINE,
|
||||
SQLITE,
|
||||
SUPERSET,
|
||||
TABLEAU,
|
||||
@ -261,6 +262,9 @@ export const serviceTypeLogo = (type: string) => {
|
||||
case PipelineServiceType.GluePipeline:
|
||||
return GLUE;
|
||||
|
||||
case PipelineServiceType.Spline:
|
||||
return SPLINE;
|
||||
|
||||
case PipelineServiceType.Nifi:
|
||||
return NIFI;
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user