Ingest data from HubSpot into Databricks

Beta

This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.

Learn how to create a managed ingestion pipeline to ingest data from HubSpot into Databricks.

Requirements

To create an ingestion pipeline, you must meet the following requirements:

Your workspace must be enabled for Unity Catalog.
Serverless compute must be enabled for your workspace. See Serverless compute requirements.
If you plan to create a new connection: You must have CREATE CONNECTION privileges on the metastore.

If the connector supports UI-based pipeline authoring, an admin can create the connection and the pipeline at the same time by completing the steps on this page. However, if the users who create pipelines use API-based pipeline authoring or are non-admin users, an admin must first create the connection in Catalog Explorer. See Connect to managed ingestion sources.
If you plan to use an existing connection: You must have USE CONNECTION privileges or ALL PRIVILEGES on the connection object.
You must have USE CATALOG privileges on the target catalog.
You must have USE SCHEMA and CREATE TABLE privileges on an existing schema or CREATE SCHEMA privileges on the target catalog.

To ingest from HubSpot, you must complete the steps in Configure OAuth for HubSpot ingestion.

Create an ingestion pipeline

Databricks Asset Bundles
Databricks notebook

You can deploy an ingestion pipeline using Databricks Asset Bundles. Bundles can contain YAML definitions of jobs and tasks, are managed using the Databricks CLI, and can be shared and run in different target workspaces (such as development, staging, and production). For more information, see What are Databricks Asset Bundles?.

Create a new bundle using the Databricks CLI:
Bash
```
databricks bundle init
```
Add two new resource files to the bundle:
- A pipeline definition file (resources/hubspot_pipeline.yml).
- A workflow file that controls the frequency of data ingestion (resources/hubspot_job.yml).
See Values to modify and Pipeline definition templates.
Deploy the pipeline using the Databricks CLI:
Bash
```
databricks bundle deploy
```

Values to modify

Value	Description
`name`	A unique name for the pipeline.
`connection_name`	The name of the Unity Catalog connection that stores authentication details for HubSpot.
`source_schema`	The name of the schema that contains the data you want to ingest.
`source_table`	The name of the table you want to ingest.
`destination_catalog`	The name of the catalog you want to write to in Databricks.
`destination_schema`	The name of the schema you want to write to in Databricks.
`destination_table`	Optional. A unique name for the table you want to write to in Databricks. If you don't provide this, the connector automatically uses the source table name.

Pipeline definition templates

YAML
JSON

These are templates to use with Databricks Asset Bundles. The following is an example resources/hubspot_pipeline.yml file:

YAML
resources:
  pipelines:
    pipeline_hubspot:
      name: <pipeline>
      catalog: <destination-catalog>
      target: <destination-schema>
      ingestion_definition:
        connection_name: <connection>
        objects:
          - table:
              source_schema: <source-schema>
              source_table: <source-table>
              destination_catalog: <destination-catalog>
              destination_schema: <destination-schema>
              destination_table: <destination-table>

The following is an example resources/hubspot_job.yml file:

YAML
resources:
  jobs:
    hubspot_dab_job:
      name: hubspot_dab_job

      trigger:
        # Run this job every day, exactly one day from the last run
        # See https://docs.databricks.com/api/workspace/jobs/create#trigger
        periodic:
          interval: 1
          unit: DAYS

      email_notifications:
        on_failure:
          - <email-address>

      tasks:
        - task_key: refresh_pipeline
          pipeline_task:
            pipeline_id: <pipeline-id>

This is a pipeline definition template for use with Databricks notebooks.

JSON
pipeline_spec = """
{
 "name": "<pipeline>",
 "ingestion_definition": {
    "connection_name": "<connection>",
    "objects": [
      {
        "table": {
          "source_schema": "<source-schema>",
          "source_table": "<source-table>",
          "destination_catalog": "<destination-catalog>",
          "destination_schema": "<destination-schema>",
          "destination_table": "<destination-table>"
        }
      }
    ]
  }
}
"""

Common patterns

For details about advanced pipeline configurations, see Common patterns for managed ingestion pipelines.

Requirements​

Create an ingestion pipeline​

Values to modify​

Pipeline definition templates​

Common patterns​

Additional resources​

Requirements

Create an ingestion pipeline

Values to modify

Pipeline definition templates

Common patterns

Additional resources