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93 lines
3.3 KiB
Markdown
93 lines
3.3 KiB
Markdown
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---
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title: Ingest dbt CLI
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slug: /connectors/ingestion/workflows/dbt/ingest-dbt-cli
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---
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# dbt Workflow CLI
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Learn how to configure the dbt workflow from the cli to ingest dbt data from your data sources.
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## CLI Configuration
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Once the metadata ingestion runs correctly and we are able to explore the service Entities, we can add the dbt information.
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This will populate the dbt tab from the Table Entity Page.
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<Image src="/images/openmetadata/ingestion/workflows/dbt/dbt-features/dbt-query.png" alt="dbt" caption="dbt"/>
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We can create a workflow that will obtain the dbt information from the dbt files and feed it to OpenMetadata. The dbt Ingestion will be in charge of obtaining this data.
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### 1. Create the workflow configuration
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Configure the dbt.yaml file according keeping only one of the required source (local, http, gcs, s3).
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The dbt files should be present on the source mentioned and should have the necssary permissions to be able to access the files.
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Enter the name of your database service from OpenMetadata in the `serviceName` key in the yaml
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```yaml
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source:
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type: dbt
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serviceName: service_name
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sourceConfig:
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config:
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type: DBT
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# For dbt, choose one of Cloud, Local, HTTP, S3 or GCS configurations
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# dbtConfigSource:
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# # For cloud
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# dbtCloudAuthToken: token
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# dbtCloudAccountId: ID
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# dbtCloudProjectId: project_id
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# # For Local
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# dbtCatalogFilePath: path-to-catalog.json
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# dbtManifestFilePath: path-to-manifest.json
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# dbtRunResultsFilePath: path-to-run_results.json
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# # For HTTP
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# dbtCatalogHttpPath: http://path-to-catalog.json
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# dbtManifestHttpPath: http://path-to-manifest.json
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# dbtRunResultsHttpPath: http://path-to-run_results.json
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# # For S3
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# dbtSecurityConfig: # These are modeled after all AWS credentials
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# awsAccessKeyId: KEY
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# awsSecretAccessKey: SECRET
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# awsRegion: us-east-2
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# dbtPrefixConfig:
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# dbtBucketName: bucket
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# dbtObjectPrefix: "dbt/"
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# # For GCS Values
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# dbtSecurityConfig: # These are modeled after all GCS credentials
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# gcsConfig:
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# type: My Type
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# projectId: project ID
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# privateKeyId: us-east-2
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# privateKey: |
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# -----BEGIN PRIVATE KEY-----
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# Super secret key
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# -----END PRIVATE KEY-----
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# clientEmail: client@mail.com
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# clientId: 1234
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# authUri: https://accounts.google.com/o/oauth2/auth (default)
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# tokenUri: https://oauth2.googleapis.com/token (default)
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# authProviderX509CertUrl: https://www.googleapis.com/oauth2/v1/certs (default)
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# clientX509CertUrl: https://cert.url (URI)
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# # For GCS Values
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# dbtSecurityConfig: # These are modeled after all GCS credentials
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# gcsConfig: path-to-credentials-file.json
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# dbtPrefixConfig:
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# dbtBucketName: bucket
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# dbtObjectPrefix: "dbt/"
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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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openMetadataServerConfig:
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hostPort: http://localhost:8585/api
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authProvider: no-auth
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```
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### 2. Run the dbt ingestion
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After saving the YAML config, we will run the command for dbt ingestion
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```bash
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metadata ingest -c <path-to-yaml>
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```
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