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333 lines
11 KiB
Markdown
333 lines
11 KiB
Markdown
---
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title: Run Superset Connector using the CLI
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slug: /connectors/dashboard/superset/cli
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---
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# Run Superset using the metadata CLI
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In this section, we provide guides and references to use the Superset connector.
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Configure and schedule Superset metadata and profiler workflows from the OpenMetadata UI:
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- [Requirements](#requirements)
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- [Metadata Ingestion](#metadata-ingestion)
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## Requirements
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<InlineCallout color="violet-70" icon="description" bold="OpenMetadata 0.12 or later" href="/deployment">
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To deploy OpenMetadata, check the <a href="/deployment">Deployment</a> guides.
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</InlineCallout>
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To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
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custom Airflow plugins to handle the workflow deployment.
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The ingestion also works with Superset 2.0.0 🎉
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<Note>
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**API Connection**: To extract metadata from Superset via API, user must have at least `can read on Chart` & `can read on Dashboard` permissions.
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<br/>
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**Database Connection**: To extract metadata from Superset via MySQL or Postgres database, database user must have at least `SELECT` priviledge on `dashboards` & `slices` tables within superset schema.
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</Note>
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### Python Requirements
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To run the Superset ingestion, you will need to install:
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```bash
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pip3 install "openmetadata-ingestion[superset]"
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```
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## Metadata Ingestion
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All connectors are defined as JSON Schemas.
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[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/dashboard/supersetConnection.json)
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you can find the structure to create a connection to Superset.
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In order to create and run a Metadata Ingestion workflow, we will follow
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the steps to create a YAML configuration able to connect to the source,
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process the Entities if needed, and reach the OpenMetadata server.
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The workflow is modeled around the following
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[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)
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### 1. Define the YAML Config
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This is a sample config for Superset:
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```yaml
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source:
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type: superset
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serviceName: local_superset
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serviceConnection:
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config:
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type: Superset
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hostPort: http://localhost:8088
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connection:
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# For Superset API Connection
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username: admin
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password: admin
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provider: db # or provider: ldap
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# For MySQL Connection
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# type: Mysql
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# username: <username>
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# password: <password>
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# hostPort: <hostPort>
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# databaseSchema: superset
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# For Postgres Connection
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# type: Postgres
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# username: username
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# password: password
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# hostPort: localhost:5432
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# database: superset
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sourceConfig:
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config:
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type: DashboardMetadata
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# dbServiceNames:
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# - service1
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# - service2
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# dashboardFilterPattern:
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# includes:
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# - dashboard1
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# - dashboard2
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# excludes:
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# - dashboard3
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# - dashboard4
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# chartFilterPattern:
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# includes:
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# - chart1
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# - chart2
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# excludes:
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# - chart3
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# - chart4
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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 # DEBUG, INFO, WARN or ERROR
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openMetadataServerConfig:
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hostPort: <OpenMetadata host and port>
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authProvider: <OpenMetadata auth provider>
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```
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#### Source Configuration - Service Connection
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- **hostPort**: URL to the Superset instance.
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- **connection**: Add the connection details to fetch metadata from Superset either through APIs or Database.
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<Collapse title="Superset API Connection">
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- **username**: Specify the User to connect to Superset. It should have enough privileges to read all the metadata.
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- **password**: Password for Superset.
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- **provider**: Authentication provider for the Superset service. For basic user/password authentication, the default value `db` can be used. This parameter is used internally to connect to Superset's REST API.
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</Collapse>
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<Collapse title="MySQL Connection">
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- **username**: Specify the User to connect to MySQL. It should have enough privileges to read all the metadata.
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- **password**: Password to connect to MySQL.
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- **hostPort**: Enter the fully qualified hostname and port number for your MySQL deployment in the Host and Port field.
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- **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to MySQL during the connection. These details must be added as Key-Value pairs.
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- **Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent to MySQL during the connection. These details must be added as Key-Value pairs.
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- In case you are using Single-Sign-On (SSO) for authentication, add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "sso_login_url"`
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- In case you authenticate with SSO using an external browser popup, then add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "externalbrowser"`
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</Collapse>
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<Collapse title="Postgres Connection">
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- **username**: Specify the User to connect to Postgres. It should have enough privileges to read all the metadata.
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- **password**: Password to connect to Postgres.
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- **hostPort**: Enter the fully qualified hostname and port number for your Postgres deployment in the Host and Port field.
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- **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to Postgres during the connection. These details must be added as Key-Value pairs.
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- **Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent to Postgres during the connection. These details must be added as Key-Value pairs.
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- In case you are using Single-Sign-On (SSO) for authentication, add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "sso_login_url"`
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- In case you authenticate with SSO using an external browser popup, then add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "externalbrowser"`
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</Collapse>
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#### Source Configuration - Source Config
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The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json):
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- `dbServiceNames`: Database Service Name for the creation of lineage, if the source supports it.
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- `dashboardFilterPattern` and `chartFilterPattern`: Note that the `dashboardFilterPattern` and `chartFilterPattern` both support regex as include or exclude. E.g.,
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```yaml
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dashboardFilterPattern:
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includes:
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- users
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- type_test
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```
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#### Sink Configuration
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To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
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#### Workflow Configuration
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The main property here is the `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation.
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For a simple, local installation using our docker containers, this looks like:
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```yaml
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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: '{bot_jwt_token}'
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```
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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).
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You can find the different implementation of the ingestion below.
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<Collapse title="Configure SSO in the Ingestion Workflows">
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### Openmetadata JWT Auth
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```yaml
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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: '{bot_jwt_token}'
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```
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### Auth0 SSO
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: auth0
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securityConfig:
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clientId: '{your_client_id}'
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secretKey: '{your_client_secret}'
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domain: '{your_domain}'
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```
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### Azure SSO
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: azure
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securityConfig:
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clientSecret: '{your_client_secret}'
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authority: '{your_authority_url}'
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clientId: '{your_client_id}'
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scopes:
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- your_scopes
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```
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### Custom OIDC SSO
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: custom-oidc
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securityConfig:
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clientId: '{your_client_id}'
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secretKey: '{your_client_secret}'
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domain: '{your_domain}'
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```
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### Google SSO
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: google
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securityConfig:
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secretKey: '{path-to-json-creds}'
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```
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### Okta SSO
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: http://localhost:8585/api
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authProvider: okta
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securityConfig:
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clientId: "{CLIENT_ID - SPA APP}"
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orgURL: "{ISSUER_URL}/v1/token"
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privateKey: "{public/private keypair}"
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email: "{email}"
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scopes:
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- token
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```
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### Amazon Cognito SSO
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The ingestion can be configured by [Enabling JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens)
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: auth0
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securityConfig:
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clientId: '{your_client_id}'
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secretKey: '{your_client_secret}'
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domain: '{your_domain}'
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```
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### OneLogin SSO
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Which uses Custom OIDC for the ingestion
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: custom-oidc
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securityConfig:
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clientId: '{your_client_id}'
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secretKey: '{your_client_secret}'
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domain: '{your_domain}'
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```
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### KeyCloak SSO
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Which uses Custom OIDC for the ingestion
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```yaml
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workflowConfig:
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openMetadataServerConfig:
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hostPort: 'http://localhost:8585/api'
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authProvider: custom-oidc
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securityConfig:
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clientId: '{your_client_id}'
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secretKey: '{your_client_secret}'
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domain: '{your_domain}'
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```
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</Collapse>
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### 2. Run with the CLI
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First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
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```bash
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metadata ingest -c <path-to-yaml>
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```
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Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
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you will be able to extract metadata from different sources.
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