2023-04-14 19:28:31 +05:30

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---
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.
<InlineCallout color="violet-70" icon="description" bold="OpenMetadata 0.12 or later" href="/deployment">
To deploy OpenMetadata, check the <a href="/deployment">Deployment</a> guides.
</InlineCallout>
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: <OpenMetadata host and port>
authProvider: <OpenMetadata auth provider>
```
### 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: <OpenMetadata host and port>
authProvider: <OpenMetadata auth provider>
```
#### 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.
</Note>
```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: <OpenMetadata host and port>
authProvider: <OpenMetadata auth provider>
```
#### 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.
<Collapse title="Configure SSO in the Ingestion Workflows">
### 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}'
```
</Collapse>
### 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 <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.