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:

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 run the Tableau ingestion, you will need to install:

pip3 install "openmetadata-ingestion[tableau]"

All connectors are defined as JSON Schemas. Here 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

This is a sample config for Tableau:

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: http://localhost:8585/api
    authProvider: no-auth

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.

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: http://localhost:8585/api
    authProvider: no-auth

1. Sample config for non-default tableau site

For a non-default tableau site siteName and siteUrl fields are required.

Note

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.

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: http://localhost:8585/api
    authProvider: no-auth

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:

  • 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.,
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:

workflowConfig:
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: no-auth

We support different security providers. You can find their definitions here. You can find the different implementation of the ingestion below.

chevron_rightConfigure SSO in the Ingestion Workflows

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

metadata ingest -c <path-to-yaml>

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.

Still have questions?

You can take a look at our Q&A or reach out to us in Slack

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