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| description |
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| This guide will help install Looker connector and run manually |
Looker
{% hint style="info" %} Prerequisites
OpenMetadata is built using Java, DropWizard, Jetty, and MySQL.
- Python 3.7 or above
- OpenMetadata Server up and running {% endhint %}
Install from PyPI or Source
{% 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": "username",
"password": "password",
"url": "http://localhost",
"service_name": "looker",
"service_type": "Looker",
}
},
{% endcode %}
- username - pass the Looker username.
- password - the password for the Looker username.
- url - looker connector url
- 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.
- 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 Optionallypii processor and metadata-rest-tables sink along with metadata-server config
{% code title="looker.json" %}
{
"source": {
"type": "looker",
"config": {
"username": "username",
"password": "password",
"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 %}