Use Delta Live Tables pipelines with legacy Hive metastore

This article details configurations and caveats specific to Delta Live Tables pipelines configured to publish data to the legacy Hive metastore. Databricks recommends using Unity Catalog for all new pipelines. See Use Unity Catalog with your Delta Live Tables pipelines.

Publish pipeline datasets to the legacy Hive metastore

While optional, you should specify a target to publish tables created by your pipeline anytime you move beyond development and testing for a new pipeline. Publishing a pipeline to a target makes datasets available for querying elsewhere in your Databricks environment.

You can make the output data of your pipeline discoverable and available to query by publishing datasets to the Hive metastore. To publish datasets to the metastore, enter a schema name in the Target field when you create a pipeline. You can also add a target database to an existing pipeline.

All tables and views created in Delta Live Tables are local to the pipeline by default. You must publish tables to a target schema to query or use Delta Live Tables datasets outside the pipeline in which they are declared.

To publish tables from your pipelines to Unity Catalog, see Use Unity Catalog with your Delta Live Tables pipelines.

How to publish Delta Live Tables datasets to the legacy Hive metastore

You can declare a target schema for all tables in your Delta Live Tables pipeline using the Target schema field in the Pipeline settings and Create pipeline UIs.

You can also specify a schema in a JSON configuration by setting the target value.

You must run an update for the pipeline to publish results to the target schema.

You can use this feature with multiple environment configurations to publish to different schemas based on the environment. For example, you can publish to a dev schema for development and a prod schema for production data.

How to query streaming tables and materialized views in the legacy Hive metastore

After an update is complete, you can view the schema and tables, query the data, or use the data in downstream applications.

Once published, Delta Live Tables tables can be queried from any environment with access to the target schema. This includes Databricks SQL, notebooks, and other Delta Live Tables pipelines.

Important

When you create a target configuration, only tables and associated metadata are published. Views are not published to the metastore.

Specify a storage location

You can specify a storage location for a pipeline that publishes to the Hive metastore. The primary motivation for specifying a location is to control the object storage location for data written by your pipeline.

Because all tables, data, checkpoints, and metadata for Delta Live Tables pipelines are fully managed by Delta Live Tables, most interaction with Delta Live Tables datasets happens through tables registered to the Hive metastore or Unity Catalog.

Cloud storage configuration

You use AWS instance profiles to configure access to S3 storage in AWS. To add an instance profile in the Delta Live Tables UI when you create or edit a pipeline:

On the Pipeline details page for your pipeline, click the Settings button.
In the Instance profile drop-down menu In the Compute section of the pipeline settings, select an instance profile.

To configure an AWS instance profile by editing the JSON settings for your pipeline clusters, click the JSON button and enter the instance profile configuration in the aws_attributes.instance_profile_arn field in the cluster configuration:

{
  "clusters": [
    {
      "aws_attributes": {
        "instance_profile_arn": "arn:aws:..."
      }
    }
  ]
}

You can also configure instance profiles when you create cluster policies for your Delta Live Tables pipelines. For an example, see the knowledge base.