--- 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 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. ### 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 username: username password: password env: tableau_prod hostPort: http://localhost siteName: site_name siteUrl: site_url apiVersion: api_version # If not setting user and password # personalAccessTokenName: personal_access_token_name # personalAccessTokenSecret: personal_access_token_secret sourceConfig: config: type: DashboardMetadata # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 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 username: username password: password env: tableau_prod hostPort: http://localhost siteName: "" siteUrl: "" apiVersion: api_version # If not setting user and password # personalAccessTokenName: personal_access_token_name # personalAccessTokenSecret: personal_access_token_secret sourceConfig: config: type: DashboardMetadata # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 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 username: username password: password env: tableau_prod hostPort: http://localhost siteName: openmetadata siteUrl: openmetadata apiVersion: api_version # If not setting user and password # personalAccessTokenName: personal_access_token_name # personalAccessTokenSecret: personal_access_token_secret sourceConfig: config: type: DashboardMetadata # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 sink: type: metadata-rest config: {} workflowConfig: # loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR openMetadataServerConfig: hostPort: authProvider: ``` #### Source Configuration - Service Connection - **hostPort**: URL to the Tableau instance. - **username**: Specify the User to connect to Tableau. It should have enough privileges to read all the metadata. - **password**: Password for Tableau. - **apiVersion**: Tableau API version. - **siteName**: Tableau Site Name. To be kept empty if you are using the default Tableau site - **siteUrl**: Tableau Site Url. To be kept empty if you are using the default Tableau site - **personalAccessTokenName**: Access token. To be used if not logging in with user/password. - **personalAccessTokenSecret**: Access token Secret. To be used if not logging in with user/password. - **env**: 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): - `dbServiceName`: Database Service Name for the creation of lineage, if the source supports it. - `dashboardFilterPattern` and `chartFilterPattern`: Note that the `dashboardFilterPattern` and `chartFilterPattern` both support regex as include or exclude. E.g., ```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.