Skip to main content

Ingest data from Zendesk Support

Beta

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

This page shows how to create a managed Zendesk Support ingestion pipeline using Lakeflow Connect.

Requirements

  • To create an ingestion pipeline, you must first 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 Zendesk Support, you must first complete the steps in Configure Zendesk Support for OAuth.

Create an ingestion pipeline

Each source table is ingested into a streaming table.

  1. In the sidebar of the Databricks workspace, click Data Ingestion.
  2. On the Add data page, under Databricks connectors, click Zendesk Support.
  3. On the Connection page of the ingestion wizard, select the connection that stores your Zendesk Support access credentials. If you have the CREATE CONNECTION privilege on the metastore, you can click Plus icon. Create connection to create a new connection with the authentication details in Configure Zendesk Support for OAuth.
  4. Click Next.
  5. On the Ingestion setup page, enter a unique name for the pipeline.
  6. Select a catalog and a schema to write event logs to. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, you can click Plus icon. Create schema in the drop-down menu to create a new schema.
  7. Click Create pipeline and continue.
  8. On the Source page, select the tables to ingest.
  9. Click Save and continue.
  10. On the Destination page, select a catalog and a schema to load data into. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, you can click Plus icon. Create schema in the drop-down menu to create a new schema.
  11. Click Save and continue.
  12. (Optional) On the Schedules and notifications page, click Plus icon. Create schedule. Set the frequency to refresh the destination tables.
  13. (Optional) Click Plus icon. Add notification to set email notifications for pipeline operation success or failure, then click Save and run pipeline.

Examples

Use these examples to configure your pipeline.

Ingest a single source table

The following pipeline definition file ingests a single source table:

YAML
variables:
dest_catalog:
default: main
dest_schema:
default: ingest_destination_schema

# The main pipeline for zendesk_dab
resources:
pipelines:
pipeline_zendesk:
name: zendesk_pipeline
catalog: ${var.dest_catalog}
schema: ${var.dest_schema}
ingestion_definition:
connection_name: <zendesk-connection>
objects:
# An array of objects to ingest from Zendesk Support. This example ingests the tickets table.
- table:
source_schema: default
source_table: tickets
destination_catalog: ${var.dest_catalog}
destination_schema: ${var.dest_schema}

Ingest multiple source tables

The following pipeline definition file ingests multiple source tables:

YAML
variables:
dest_catalog:
default: main
dest_schema:
default: ingest_destination_schema

# The main pipeline for zendesk_dab
resources:
pipelines:
pipeline_zendesk:
name: zendesk_pipeline
catalog: ${var.dest_catalog}
schema: ${var.dest_schema}
ingestion_definition:
connection_name: <zendesk-connection>
objects:
# An array of objects to ingest from Zendesk Support. This example ingests the tickets and users tables.
- table:
source_schema: default
source_table: tickets
destination_catalog: ${var.dest_catalog}
destination_schema: ${var.dest_schema}
- table:
source_schema: default
source_table: users
destination_catalog: ${var.dest_catalog}
destination_schema: ${var.dest_schema}

Bundle job definition file

The following is an example job definition file to use with Declarative Automation Bundles. The job runs every day, exactly one day from the last run.

YAML
resources:
jobs:
zendesk_dab_job:
name: zendesk_dab_job

trigger:
periodic:
interval: 1
unit: DAYS

email_notifications:
on_failure:
- <email-address>

tasks:
- task_key: refresh_pipeline
pipeline_task:
pipeline_id: ${resources.pipelines.pipeline_zendesk.id}

Common patterns

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

Next steps

Start, schedule, and set alerts on your pipeline. See Common pipeline maintenance tasks.

Additional resources