--- title: Run Tableau Connector using the CLI slug: /connectors/dashboard/tableau/cli --- # Run Tableau using the metadata CLI In this section, we provide guides and references to use the Tableau connector. Configure and schedule Tableau metadata and profiler workflows from the OpenMetadata UI: - [Requirements](#requirements) - [Metadata Ingestion](#metadata-ingestion) ## Requirements To ingest tableau metadata, minimum `Site Role: Viewer` is requried for the tableau user. To deploy OpenMetadata, check the Deployment guides. 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. 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. 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) ### Python Requirements To run the Tableau ingestion, you will need to install: ```bash pip3 install "openmetadata-ingestion[tableau]" ``` ## 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/dashboard/tableauConnection.json) you can find the structure to create a connection to Tableau. 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 Tableau: ```yaml source: type: tableau serviceName: local_tableau serviceConnection: config: type: Tableau # For Tableau, choose one of basic or access token authentication # # For basic authentication # authType: # username: username # password: password # # For access token authentication # authType: # personalAccessTokenName: personal_access_token_name # personalAccessTokenSecret: personal_access_token_secret env: tableau_prod hostPort: http://localhost siteName: site_name siteUrl: site_url apiVersion: api_version sourceConfig: config: type: DashboardMetadata overrideOwner: True markDeletedDashboards: True includeTags: True includeDataModels: True # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 # dataModelFilterPattern: # includes: # - datamodel1 # - datamodel2 # excludes: # - datamodel3 # - datamodel4 sink: type: metadata-rest config: {} workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: authProvider: ``` ### Example Source Configurations for default and non-default tableau sites #### 1. Sample config for default tableau site For a default tableau site `siteName` and `siteUrl` fields should be kept as empty strings as shown in the below config. ```yaml source: type: tableau serviceName: local_tableau serviceConnection: config: type: Tableau # For Tableau, choose one of basic or access token authentication # # For basic authentication # authType: # username: username # password: password # # For access token authentication # authType: # personalAccessTokenName: personal_access_token_name # personalAccessTokenSecret: personal_access_token_secret env: tableau_prod hostPort: http://localhost siteName: "" siteUrl: "" apiVersion: api_version sourceConfig: config: overrideOwner: True markDeletedDashboards: True includeTags: True includeDataModels: True type: DashboardMetadata # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 # dataModelFilterPattern: # includes: # - datamodel1 # - datamodel2 # excludes: # - datamodel3 # - datamodel4 sink: type: metadata-rest config: {} workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: authProvider: ``` #### 1. Sample config for non-default tableau site For a non-default tableau site `siteName` and `siteUrl` fields are required. 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. ```yaml source: type: tableau serviceName: local_tableau serviceConnection: config: type: Tableau # For Tableau, choose one of basic or access token authentication # # For basic authentication # authType: # username: username # password: password # # For access token authentication # authType: # personalAccessTokenName: personal_access_token_name # personalAccessTokenSecret: personal_access_token_secret env: tableau_prod hostPort: http://localhost siteName: openmetadata siteUrl: openmetadata apiVersion: api_version sourceConfig: config: type: DashboardMetadata overrideOwner: True markDeletedDashboards: True includeTags: True includeDataModels: True # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 # dataModelFilterPattern: # includes: # - datamodel1 # - datamodel2 # excludes: # - datamodel3 # - datamodel4 sink: type: metadata-rest config: {} workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: authProvider: ``` #### Source Configuration - Service Connection - **Host and Port**: URL to the Tableau instance. - **Authentication Types**: 1. Basic Authenticaton - Username: Specify the User to connect to Tableau. It should have enough privileges to read all the metadata. - Password: Password for Tableau. 2. Access Token Authentication - Personal Access Token: Access token. To be used if not logging in with user/password. - Personal Access Token Secret: Access token Secret. To be used if not logging in with user/password. - **API Version**: Tableau API version. - **Site Name**: Tableau Site Name. To be kept empty if you are using the default Tableau site - **Site Url**: Tableau Site Url. To be kept empty if you are using the default Tableau site - **Environment**: Tableau Environment. #### Source Configuration - Source Config The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json): - `dbServiceNames`: Database Service Name for the creation of lineage, if the source supports it. - `dashboardFilterPattern` / `chartFilterPattern` / `dataModelFilterPattern`: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard". - `overrideOwner`: Flag to override current owner by new owner from source, if found during metadata ingestion. - `includeTags`: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion. - `includeDataModels`: Set the 'Include Data Models' toggle to control whether to include tags as part of metadata ingestion. - `markDeletedDashboards`: Set the Mark Deleted Dashboards toggle to flag dashboards as soft-deleted if they are not present anymore in the source system. ```yaml dashboardFilterPattern: includes: - users - type_test ``` #### Sink Configuration To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. #### Workflow Configuration 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: ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: openmetadata securityConfig: jwtToken: '{bot_jwt_token}' ``` 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). You can find the different implementation of the ingestion below. ### Openmetadata JWT Auth ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: openmetadata securityConfig: jwtToken: '{bot_jwt_token}' ``` ### Auth0 SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: auth0 securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### Azure SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: azure securityConfig: clientSecret: '{your_client_secret}' authority: '{your_authority_url}' clientId: '{your_client_id}' scopes: - your_scopes ``` ### Custom OIDC SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: custom-oidc securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### Google SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: google securityConfig: secretKey: '{path-to-json-creds}' ``` ### Okta SSO ```yaml workflowConfig: openMetadataServerConfig: hostPort: http://localhost:8585/api authProvider: okta securityConfig: clientId: "{CLIENT_ID - SPA APP}" orgURL: "{ISSUER_URL}/v1/token" privateKey: "{public/private keypair}" email: "{email}" scopes: - token ``` ### Amazon Cognito SSO The ingestion can be configured by [Enabling JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens) ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: auth0 securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### OneLogin SSO Which uses Custom OIDC for the ingestion ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: custom-oidc securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### KeyCloak SSO Which uses Custom OIDC for the ingestion ```yaml workflowConfig: openMetadataServerConfig: hostPort: 'http://localhost:8585/api' authProvider: custom-oidc securityConfig: clientId: '{your_client_id}' secretKey: '{your_client_secret}' domain: '{your_domain}' ``` ### 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 ``` 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.