DeltaLake

Feature supports in DeltaLake

Feature Supports

Metadata

Query Usage

Data Profile

Lineage

DBT

Supported Versions

Requirements

To run the Ingestion via the UI you'll need to use the metadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment.

Metadata Ingestion

Step 1: Visit the Service Page

The first step is ingesting the metadata from your sources. Under Settings, you will find a Services link an external source system to Darkseal. Once a service is created, it can be used to configure metadata, usage, and profiler workflows.

To visit the Services page, select Services from the Settings menu or my-data table.

Step 2: Create a New Service

Click on the Add New Service button to start the Service creation.

Step 3: Select the Service Type

Select DeltaLake as the service type and click Next.

Step 4: Name and Describe your Service

Provide a name and description for your service as illustrated below.

Step 5: Configure the Service Connection

In this step, we will configure the connection settings required for this connector. Please follow the instructions below to ensure that you've configured the connector to read from your DataLake service as desired.

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

To execute metadata extraction AWS account should have enough access to fetch required data. The Bucket Policy in AWS requires at least these permissions:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::<my bucket>",
                "arn:aws:s3:::<my bucket>/*"
            ]
        }
    ]
}

Step 6: Configure Metadata Ingestion

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

Metadata Ingestion Options:

• Name: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.

• Database Filter Pattern (Optional): Use to database filter patterns to control whether or not to include database as part of metadata ingestion.

  • Include: Explicitly include databases by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all databases with names matching one or more of the supplied regular expressions. All other databases will be excluded.

  • Exclude: Explicitly exclude databases by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all databases with names matching one or more of the supplied regular expressions. All other databases will be included.

• Schema Filter Pattern (Optional): Use to schema filter patterns to control whether or not to include schemas as part of metadata ingestion.

  • Include: Explicitly include schemas by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all schemas with names matching one or more of the supplied regular expressions. All other schemas will be excluded.

  • Exclude: Explicitly exclude schemas by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all schemas with names matching one or more of the supplied regular expressions. All other schemas will be included.

• Table Filter Pattern (Optional): Use to table filter patterns to control whether or not to include tables as part of metadata ingestion.

  • Include: Explicitly include tables by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all tables with names matching one or more of the supplied regular expressions. All other tables will be excluded.

  • Exclude: Explicitly exclude tables by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all tables with names matching one or more of the supplied regular expressions. All other tables will be included.

• Include views (toggle): Set the Include views toggle to control whether or not to include views as part of metadata ingestion.

• Include tags (toggle): Set the Include tags toggle to control whether or not to include tags as part of metadata ingestion.

• Enable Debug Log (toggle): Set the Enable Debug Log toggle to set the default log level to debug, these logs can be viewed later in Airflow.

• Mark Deleted Tables (toggle): Set the Mark Deleted Tables toggle to flag tables as soft-deleted if they are not present anymore in the source system.

• Mark Deleted Tables from Filter Only (toggle): Set the Mark Deleted Tables from Filter Only toggle to flag tables as soft-deleted if they are not present anymore within the filtered schema or database only. This flag is useful when you have more than one ingestion pipelines. For example if you have a schema

• Auto Tag PII(toggle): Auto PII tagging checks for column name to mark PII Sensitive/NonSensitive tag

Step 7: Schedule the Ingestion and Deploy

Scheduling can be set up at an hourly, daily, or weekly 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.