OpenMetadata/openmetadata-docs/content/v1.1.0/connectors/pipeline/domo-pipeline/cli.md

title	slug
Run Domo Pipeline Connector using the CLI	/connectors/pipeline/domo-pipeline/cli

Run Domo Pipeline using the Metadata CLI

In this section, we provide guides and references to use the Domo Pipeline connector.

Configure and schedule Domo Pipeline metadata and profiler workflows from the OpenMetadata UI:

• Requirements
• 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: For metadata ingestion, kindly make sure add alteast data scopes to the clientId provided. Question related to scopes, click here.

Python Requirements

To run the Domo Pipeline ingestion, you will need to install:

pip3 install "openmetadata-ingestion[domo]"

Metadata Ingestion

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Airbyte.

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

1. Define the YAML Config

This is a sample config for Domo-Pipeline:

{% codePreview %}

{% codeInfoContainer %}

Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

Client ID: Client ID to Connect to DOMO Pipeline.

{% /codeInfo %}

{% codeInfo srNumber=2 %}

Secret Token: Secret Token to Connect DOMO Pipeline.

{% /codeInfo %}

{% codeInfo srNumber=3 %}

Access Token: Access to Connect to DOMO Pipeline.

{% /codeInfo %}

{% codeInfo srNumber=4 %}

API Host: API Host to Connect to DOMO Pipeline instance.

{% /codeInfo %}

{% codeInfo srNumber=5 %}

SandBox Domain: Connect to SandBox Domain.

{% /codeInfo %}

Source Configuration - Source Config

{% codeInfo srNumber=6 %}

The sourceConfig is defined here:

dbServiceNames: Database Service Name for the creation of lineage, if the source supports it.

includeTags: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.

markDeletedPipelines: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.

pipelineFilterPattern and chartFilterPattern: Note that the pipelineFilterPattern and chartFilterPattern both support regex as include or exclude.

{% /codeInfo %}

Sink Configuration

{% codeInfo srNumber=7 %}

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" %}

source:
  type: domopipeline
  serviceName: domo-pipeline_source
  serviceConnection:
    config:
      type: DomoPipeline

      clientID: clientid

      secretToken: secret-token

      accessToken: access-token

      apiHost: api.domo.com

      sandboxDomain: https://<api_domo>.domo.com

  sourceConfig:
    config:
      type: PipelineMetadata
      # markDeletedPipelines: True
      # includeTags: True
      # includeLineage: true
      # pipelineFilterPattern:
      #   includes:
      #     - pipeline1
      #     - pipeline2
      #   excludes:
      #     - pipeline3
      #     - pipeline4

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:

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.