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2.1 KiB
description |
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This guide will help install Vertica Usage connector and run manually |
Vertica Usage
{% 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[vertica]'
{% endtab %} {% endtabs %}
Run Manually
metadata ingest -c ./examples/workflows/vertica.json
Configuration
{% code title="vertica.json" %}
{
"source": {
"type": "vertica",
"config": {
"username": "openmetadata_user",
"password": "openmetadata_password",
"database": "openmetadata_db",
"service_name": "local_vertica",
"filter_pattern": {
"excludes": []
}
}
},
{% endcode %}
- **username **- pass the Vertica username.
- password - password for the username.
- service_name - Service Name for this Vertica cluster. If you added Vertica 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 Vertica Usage data into the OpenMetadata service.
Add Optionally query-parser
processor, table-usage
stage andmetadata-usage
bulk_sink along with metadata-server
config
{% code title="vertica.json" %}
{
"source": {
"type": "vertica",
"config": {
"username": "openmetadata_user",
"password": "openmetadata_password",
"database": "openmetadata_db",
"service_name": "local_vertica",
"filter_pattern": {
"excludes": []
}
}
},
"sink": {
"type": "metadata-rest",
"config": {}
},
"metadata_server": {
"type": "metadata-server",
"config": {
"api_endpoint": "http://localhost:8585/api",
"auth_provider_type": "no-auth"
}
}
}
{% endcode %}