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2.2 KiB
2.2 KiB
| description |
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| This guide will help install DBT connector and run manually |
DBT
{% hint style="info" %} Prerequisites
OpenMetadata is built using Java, DropWizard, Jetty, and MySQL.
- Python 3.7 or above {% endhint %}
Install from PyPI
{% tabs %} {% tab title="Install Using PyPI" %}
pip install 'openmetadata-ingestion[dbt]'
{% endtab %} {% endtabs %}
Run Manually
metadata ingest -c ./examples/workflows/dbt.json
Configuration
{% code title="dbt.json" %}
{
"source": {
"type": "dbt",
"config": {
"service_name": "bigquery",
"service_type": "BigQuery",
"catalog_file": "./examples/sample_data/dbt/catalog.json",
"manifest_file": "./examples/sample_data/dbt/manifest.json",
"run_results_file": "./examples/sample_data/dbt/run_results.json",
"database": "shopify"
}
}
...
{% endcode %}
- service_name - Service Name for this MySQL cluster. If you added MySQL cluster through OpenMetadata UI, make sure the service name matches the same.
- catalog_file - It contains includes, excludes options to choose which pattern of datasets you want to ingest into OpenMetadata
- manifest_file - Enable data-profiling (Optional). It will provide you the newly ingested data.
- run_results_file - Specify offset.
- database - Specify limit.
Publish to OpenMetadata
Below is the configuration to publish DBT data into the OpenMetadata service.
Add optionally pii processor and metadata-rest sink along with metadata-server config
{% code title="dbt.json" %}
{
"source": {
"type": "dbt",
"config": {
"service_name": "bigquery",
"service_type": "BigQuery",
"catalog_file": "./examples/sample_data/dbt/catalog.json",
"manifest_file": "./examples/sample_data/dbt/manifest.json",
"run_results_file": "./examples/sample_data/dbt/run_results.json",
"database": "shopify"
}
},
"sink": {
"type": "metadata-rest",
"config": {}
},
"metadata_server": {
"type": "metadata-server",
"config": {
"api_endpoint": "http://localhost:8585/api",
"auth_provider_type": "no-auth"
}
}
}
{% endcode %}