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91 lines
2.7 KiB
Markdown
91 lines
2.7 KiB
Markdown
---
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title: Run Elasticsearch Reindex using Airflow SDK
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slug: /how-to-guides/data-insights/elasticsearch-reindex
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---
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# Run Elasticsearch Reindex using Airflow SDK
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## 1. Define the YAML Config
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This is a sample config for Elasticsearch Reindex:
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```yaml
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source:
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source:
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type: metadata_elasticsearch
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serviceName: openMetadata
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serviceConnection:
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config:
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type: MetadataES
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sourceConfig:
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config: {}
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sink:
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type: elasticsearch
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config:
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es_host: localhost
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es_port: 9200
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recreate_indexes: true
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workflowConfig:
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openMetadataServerConfig:
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hostPort: http://localhost:8585/api
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authProvider: openmetadata
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securityConfig:
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jwtToken: "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
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```
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### 2. Prepare the Ingestion DAG
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Create a Python file in your Airflow DAGs directory with the following contents:
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```python
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import pathlib
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import yaml
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from datetime import timedelta
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from airflow import DAG
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try:
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from airflow.operators.python import PythonOperator
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except ModuleNotFoundError:
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from airflow.operators.python_operator import PythonOperator
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from metadata.config.common import load_config_file
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from metadata.workflow.metadata import MetadataWorkflow
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from metadata.workflow.workflow_output_handler import print_status
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from airflow.utils.dates import days_ago
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default_args = {
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"owner": "user_name",
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"email": ["username@org.com"],
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"email_on_failure": False,
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"retries": 3,
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"retry_delay": timedelta(minutes=5),
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"execution_timeout": timedelta(minutes=60)
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}
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config = """
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<your YAML configuration>
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"""
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def metadata_ingestion_workflow():
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workflow_config = yaml.safe_load(config)
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workflow = MetadataWorkflow.create(workflow_config)
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workflow.execute()
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workflow.raise_from_status()
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print_status(workflow)
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workflow.stop()
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with DAG(
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"sample_data",
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default_args=default_args,
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description="An example DAG which runs a OpenMetadata ingestion workflow",
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start_date=days_ago(1),
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is_paused_upon_creation=False,
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schedule_interval='*/5 * * * *',
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catchup=False,
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) as dag:
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ingest_task = PythonOperator(
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task_id="ingest_using_recipe",
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python_callable=metadata_ingestion_workflow,
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)
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```
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