In this section, we provide guides and references to use the Alation Sink connector.
Configure and schedule Alation Sink metadata using the yaml:
How to Run the Connector Externally
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.
If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check
the following docs to run the Ingestion Framework anywhere.
Requirements
The connector uses POST requests to write the data into Alation.
Hence, an user credentials or an access token with Source Admin or Catalog Admin or Server Admin permissions will be required.
Follow the link here to create the access token.
Data Mapping and Assumptions
Following entities are supported and will be mapped to the from OpenMetadata to the entities in Alation.
| Alation Entity | OpenMetadata Entity |
|---|
| Data Source (OCF) | Database |
| Schema | Schema |
| Table | Table |
| Columns | Columns |
Python Requirements
We have support for Python versions 3.9-3.11
To run the Alation Sink ingestion, you will need to install:
pip3 install "openmetadata-ingestion[alationsink]"
All connectors are defined as JSON Schemas.
Here
you can find the structure to create a connection to Alation Sink.
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
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.