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449 lines
13 KiB
Markdown
449 lines
13 KiB
Markdown
---
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title: Run Tableau Connector using the CLI
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slug: /connectors/dashboard/tableau/cli
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---
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# Run Tableau using the metadata CLI
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In this section, we provide guides and references to use the Tableau connector.
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Configure and schedule Tableau 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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To ingest tableau metadata, minimum `Site Role: Viewer` is requried for the tableau user.
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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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To create lineage between tableau dashboard and any database service via the queries provided from Tableau Metadata API, please enable the Tableau Metadata API for your tableau server.
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For more information on enabling the Tableau Metadata APIs follow the link [here](https://help.tableau.com/current/api/metadata_api/en-us/docs/meta_api_start.html)
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### Python Requirements
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To run the Tableau ingestion, you will need to install:
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```bash
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pip3 install "openmetadata-ingestion[tableau]"
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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/tableauConnection.json)
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you can find the structure to create a connection to Tableau.
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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 Tableau:
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```yaml
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source:
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type: tableau
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serviceName: local_tableau
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serviceConnection:
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config:
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type: Tableau
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# For Tableau, choose one of basic or access token authentication
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# # For basic authentication
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# authType:
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# username: username
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# password: password
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# # For access token authentication
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# authType:
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# personalAccessTokenName: personal_access_token_name
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# personalAccessTokenSecret: personal_access_token_secret
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env: tableau_prod
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hostPort: http://localhost
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siteName: site_name
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siteUrl: site_url
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apiVersion: api_version
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sourceConfig:
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config:
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type: DashboardMetadata
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overrideOwner: True
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markDeletedDashboards: True
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includeTags: True
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includeDataModels: True
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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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# dataModelFilterPattern:
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# includes:
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# - datamodel1
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# - datamodel2
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# excludes:
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# - datamodel3
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# - datamodel4
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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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### Example Source Configurations for default and non-default tableau sites
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#### 1. Sample config for default tableau site
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For a default tableau site `siteName` and `siteUrl` fields should be kept as empty strings as shown in the below config.
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```yaml
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source:
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type: tableau
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serviceName: local_tableau
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serviceConnection:
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config:
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type: Tableau
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# For Tableau, choose one of basic or access token authentication
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# # For basic authentication
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# authType:
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# username: username
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# password: password
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# # For access token authentication
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# authType:
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# personalAccessTokenName: personal_access_token_name
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# personalAccessTokenSecret: personal_access_token_secret
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env: tableau_prod
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hostPort: http://localhost
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siteName: ""
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siteUrl: ""
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apiVersion: api_version
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sourceConfig:
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config:
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overrideOwner: True
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markDeletedDashboards: True
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includeTags: True
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includeDataModels: True
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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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# dataModelFilterPattern:
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# includes:
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# - datamodel1
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# - datamodel2
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# excludes:
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# - datamodel3
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# - datamodel4
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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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#### 1. Sample config for non-default tableau site
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For a non-default tableau site `siteName` and `siteUrl` fields are required.
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<Note>
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If `https://xxx.tableau.com/#/site/sitename/home` represents the homepage url for your tableau site, the `sitename` from the url should be entered in the `siteName` and `siteUrl` fields in the config below.
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</Note>
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```yaml
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source:
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type: tableau
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serviceName: local_tableau
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serviceConnection:
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config:
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type: Tableau
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# For Tableau, choose one of basic or access token authentication
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# # For basic authentication
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# authType:
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# username: username
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# password: password
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# # For access token authentication
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# authType:
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# personalAccessTokenName: personal_access_token_name
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# personalAccessTokenSecret: personal_access_token_secret
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env: tableau_prod
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hostPort: http://localhost
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siteName: openmetadata
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siteUrl: openmetadata
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apiVersion: api_version
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sourceConfig:
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config:
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type: DashboardMetadata
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overrideOwner: True
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markDeletedDashboards: True
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includeTags: True
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includeDataModels: True
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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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# dataModelFilterPattern:
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# includes:
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# - datamodel1
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# - datamodel2
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# excludes:
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# - datamodel3
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# - datamodel4
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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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- **Host and Port**: URL to the Tableau instance.
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- **Authentication Types**:
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1. Basic Authenticaton
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- Username: Specify the User to connect to Tableau. It should have enough privileges to read all the metadata.
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- Password: Password for Tableau.
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2. Access Token Authentication
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- Personal Access Token: Access token. To be used if not logging in with user/password.
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- Personal Access Token Secret: Access token Secret. To be used if not logging in with user/password.
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- **API Version**: Tableau API version.
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- **Site Name**: Tableau Site Name. To be kept empty if you are using the default Tableau site
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- **Site Url**: Tableau Site Url. To be kept empty if you are using the default Tableau site
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- **Environment**: Tableau Environment.
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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` / `chartFilterPattern` / `dataModelFilterPattern`: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
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- `overrideOwner`: Flag to override current owner by new owner from source, if found during metadata ingestion.
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- `includeTags`: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.
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- `includeDataModels`: Set the 'Include Data Models' toggle to control whether to include tags as part of metadata ingestion.
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- `markDeletedDashboards`: Set the Mark Deleted Dashboards toggle to flag dashboards as soft-deleted if they are not present anymore in the source system.
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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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