--- title: Run Metabase Connector using the CLI slug: /connectors/dashboard/metabase/cli --- # Run Metabase using the metadata CLI | Stage | PROD | |------------|------------------------------| | Dashboards | {% icon iconName="check" /%} | | Charts | {% icon iconName="check" /%} | | Owners | {% icon iconName="cross" /%} | | Tags | {% icon iconName="cross" /%} | | Datamodels | {% icon iconName="cross" /%} | | Lineage | {% icon iconName="check" /%} | In this section, we provide guides and references to use the Metabase connector. Configure and schedule Metabase metadata and profiler workflows from the OpenMetadata UI: - [Requirements](#requirements) - [Metadata Ingestion](#metadata-ingestion) ## Requirements {%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%} To deploy OpenMetadata, check the Deployment 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. **Note:** We have tested Metabase with Versions `0.42.4` and `0.43.4`. ### Python Requirements To run the Metabase ingestion, you will need to install: ```bash pip3 install "openmetadata-ingestion[metabase]" ``` ## 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/metabaseConnection.json) you can find the structure to create a connection to Metabase. 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 Metabase: ### 1. Define the YAML Config {% codePreview %} {% codeInfoContainer %} #### Source Configuration - Service Connection {% codeInfo srNumber=1 %} **username**: Username to connect to Metabase, for ex. `user@organization.com`. This user should have access to relevant dashboards and charts in Metabase to fetch the metadata. {% /codeInfo %} {% codeInfo srNumber=2 %} **password**: Password of the user account to connect with Metabase. {% /codeInfo %} {% codeInfo srNumber=3 %} **hostPort**: The hostPort parameter specifies the host and port of the Metabase instance. This should be specified as a string in the format `http://hostname:port` or `https://hostname:port`. For example, you might set the hostPort parameter to `https://org.metabase.com:3000`. {% /codeInfo %} #### Source Configuration - Source Config {% codeInfo srNumber=4 %} 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 Names for ingesting 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". - **includeOwners**: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten. - **includeTags**: Set the 'Include Tags' toggle to control whether to include tags in 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. {% /codeInfo %} #### Sink Configuration {% codeInfo srNumber=5 %} To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. {% /codeInfo %} {% partial file="workflow-config.md" /%} {% /codeInfoContainer %} {% codeBlock fileName="filename.yaml" %} ```yaml source: type: metabase serviceName: serviceConnection: config: type: Metabase ``` ```yaml {% srNumber=1 %} username: ``` ```yaml {% srNumber=2 %} password: ``` ```yaml {% srNumber=3 %} hostPort: ``` ```yaml {% srNumber=4 %} sourceConfig: config: type: DashboardMetadata markDeletedDashboards: True # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 ``` ```yaml {% srNumber=5 %} sink: type: metadata-rest config: {} ``` {% partial file="workflow-config-yaml.md" /%} {% /codeBlock %} {% /codePreview %} ### 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.