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Ingest data from TikTok Ads

Important

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

This page shows how to create a managed TikTok Ads 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. See Manage privileges in Unity Catalog.

      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 TikTok Ads, you must first configure authentication from Azure Databricks. See Configure TikTok Ads for managed ingestion.

Create an ingestion pipeline

Declarative Automation Bundles

Use Declarative Automation Bundles to manage TikTok Ads pipelines as code. 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 Declarative Automation Bundles?.

  1. Create a new bundle using the Databricks CLI:

    databricks bundle init

  2. Add two new resource files to the bundle:

    • A pipeline definition file (for example, resources/tiktok_ads_pipeline.yml). See pipeline.ingestion_definition and Examples.
    • A job definition file that controls the frequency of data ingestion (for example, resources/tiktok_ads_job.yml).

  3. Deploy the pipeline using the Databricks CLI:

    databricks bundle deploy

Databricks notebook

  1. Import the following notebook into your Azure Databricks workspace:

    Get notebook

  2. Leave cells one and two as they are. Do not modify.

  3. Modify cell three with your pipeline configuration details. See pipeline.ingestion_definition and Examples.

  4. Optionally configure advanced pipeline settings. See Common patterns for managed ingestion pipelines.

  5. Click Run all.

Examples

For Declarative Automation Bundles deployments, use the following templates for your pipeline definition file and job definition file.

Pipeline definition file

resources:
  pipelines:
    tiktok_ads_pipeline:
      name: tiktok_ads_pipeline
      catalog: 'main'
      target: 'tiktok_ads_data'
      ingestion_definition:
        connection_name: tiktok_ads_connection
        objects:
          - table:
              source_schema: '<your_advertiser_id>'
              source_table: 'campaign_report_daily'
              destination_catalog: 'main'
              destination_schema: 'tiktok_ads_data'
              destination_table: 'campaign_report_daily'

Job definition file

resources:
  jobs:
    tiktok_ads_job:
      name: tiktok_ads_job
      schedule:
        quartz_cron_expression: '0 0 0 * * ?'
        timezone_id: 'UTC'
      tasks:
        - task_key: tiktok_ads_ingestion
          pipeline_task:
            pipeline_id: ${resources.pipelines.tiktok_ads_pipeline.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

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