Spline

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Pipelines

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Ingestion Deployment

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 you want to install it manually in an already existing Airflow host, you can follow this guide.

If you don't want to use the OpenMetadata Ingestion container to configure the workflows via the UI, then you can check the following docs to run the Ingestion Framework in any orchestrator externally.

Requirements

The Spline connector support lineage of data source of type jdbc or dbfs i.e. The spline connector would be able to extract lineage if the data source is either a jdbc connection or the data source is databricks instance.

Currently, we do not support data source of type aws s3 or any other cloud storage, which also means that the lineage for external tables from databricks will not be extracted.

You can refer this documentation on how to configure databricks with spline.

Metadata Ingestion

1. Visit the Services Page

The first step is to ingest the metadata from your sources. To do that, you first need to create a Service connection first.

This Service will be the bridge between OpenMetadata and your source system.

Once a Service is created, it can be used to configure your ingestion workflows.

Select your Service Type and Add a New Service

2. Create a New Service

Click on Add New Service to start the Service creation.

Add a new Service from the Services page

3. Select the Service Type

Select Spline as the Service type and click Next.

Select your Service from the list

4. Name and Describe your Service

Provide a name and description for your Service.

Service Name

OpenMetadata uniquely identifies Services by their Service Name. Provide a name that distinguishes your deployment from other Services, including the other Spline Services that you might be ingesting metadata from.

Note that when the name is set, it cannot be changed.

Provide a Name and description for your Service

5. Configure the Service Connection

In this step, we will configure the connection settings required for Spline.

Please follow the instructions below to properly configure the Service to read from your sources. You will also find helper documentation on the right-hand side panel in the UI.

Configure the Service connection by filling the form

Connection Details

Spline REST Server Host & Port: OpenMetadata uses Spline REST Server APIs to extract the execution details from spline to generate lineage. This should be specified as a URI string in the format scheme://hostname:port. E.g., http://localhost:8080, http://host.docker.internal:8080.
Spline UI Host & Port: Spline UI Host & Port is an optional field which is used for generating redirection URL from OpenMetadata to Spline Portal. This should be specified as a URI string in the format scheme://hostname:port. E.g., http://localhost:9090, http://host.docker.internal:9090.

6. Test the Connection

Once the credentials have been added, click on Test Connection and Save the changes.

Test the connection and save the Service

7. Configure Metadata Ingestion

In this step we will configure the metadata ingestion pipeline, Please follow the instructions below

Configure Metadata Ingestion Page

Metadata Ingestion Options

Name: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.
Pipeline Filter Pattern (Optional): Use to pipeline filter patterns to control whether or not to include pipeline as part of metadata ingestion.
- Include: Explicitly include pipeline by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all pipeline with names matching one or more of the supplied regular expressions. All other schemas will be excluded.
- Exclude: Explicitly exclude pipeline by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all pipeline with names matching one or more of the supplied regular expressions. All other schemas will be included.
Include lineage (toggle): Set the Include lineage toggle to control whether to include lineage between pipelines and data sources as part of metadata ingestion.
Enable Debug Log (toggle): Set the Enable Debug Log toggle to set the default log level to debug.
Mark Deleted Pipelines (toggle): Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.

8. Schedule the Ingestion and Deploy

Scheduling can be set up at an hourly, daily, weekly, or manual cadence. The timezone is in UTC. Select a Start Date to schedule for ingestion. It is optional to add an End Date.

Review your configuration settings. If they match what you intended, click Deploy to create the service and schedule metadata ingestion.

If something doesn't look right, click the Back button to return to the appropriate step and change the settings as needed.

After configuring the workflow, you can click on Deploy to create the pipeline.

Schedule the Ingestion Pipeline and Deploy

9. View the Ingestion Pipeline

Once the workflow has been successfully deployed, you can view the Ingestion Pipeline running from the Service Page.

View the Ingestion Pipeline from the Service Page

Troubleshooting

Workflow Deployment Error

If there were any errors during the workflow deployment process, the Ingestion Pipeline Entity will still be created, but no workflow will be present in the Ingestion container.

You can then Edit the Ingestion Pipeline and Deploy it again.
From the Connection tab, you can also Edit the Service if needed.