OpenMetadata/docs/integrations/connectors/looker.md

description
This guide will help install Looker connector and run manually

Looker

{% hint style="info" %} Prerequisites

OpenMetadata is built using Java, DropWizard, Jetty, and MySQL.

1. Python 3.7 or above {% endhint %}

Install from PyPI

{% tabs %} {% tab title="Install Using PyPI" %}

pip install 'openmetadata-ingestion[looker]'

{% endtab %} {% endtabs %}

Run Manually

metadata ingest -c ./examples/workflows/looker.json

Configuration

{% code title="looker.json" %}

{
  "source": {
    "type": "looker",
    "config": {
      "username": "Looker Client ID",
      "password": "Looker Client Secret",
      "url": "http://localhost",
      "service_name": "looker",
      "service_type": "Looker"
    }
  }
...

{% endcode %}

1. username - pass the Looker Client ID.
2. password - the password for the Looker Client Secret.
3. url - looker connector url
4. service_name - Service Name for this Looker cluster. If you added the Looker cluster through OpenMetadata UI, make sure the service name matches the same.
5. filter_pattern - It contains includes, excludes options to choose which pattern of datasets you want to ingest into OpenMetadata.

Publish to OpenMetadata

Below is the configuration to publish Looker data into the OpenMetadata service.

Add metadata-rest sink along with metadata-server config

{% code title="looker.json" %}

{
  "source": {
    "type": "looker",
    "config": {
      "username": "Looker Client ID",
      "password": "Looker Client Secret",
      "url": "http://localhost",
      "service_name": "looker",
      "service_type": "Looker"
    }
  },
  "sink": {
    "type": "metadata-rest",
    "config": {}
  },
  "metadata_server": {
    "type": "metadata-server",
    "config": {
      "api_endpoint": "http://localhost:8585/api",
      "auth_provider_type": "no-auth"
    }
  }
}

{% endcode %}