Meta Ads ingestion connector FAQs
The Meta Ads connector is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.
This page answers frequently asked questions about the Meta Ads ingestion connector in Databricks Lakeflow Connect.
General managed connector FAQs
The answers in Managed connector FAQs apply to all managed connectors in Lakeflow Connect. Keep reading for Meta Ads-specific FAQs.
Which Meta API does the ingestion connector use?
The Meta Ads connector uses the Insights API to retrieve advertising data from your Meta Ads accounts.
How does Databricks connect to Meta Ads?
Databricks connects to the Insights API using HTTPS. Credentials are stored securely in Unity Catalog and can only be retrieved if the user running the ingestion flow has the appropriate permissions.
How does the connector incrementally pull updates?
The connector uses cursor-based incremental ingestion. For most objects, the connector uses the updated_time field as the cursor to detect changes. On each pipeline run, the connector ingests only records that have been created or modified since the last run.
For objects without an updated_time field, the connector uses full refresh ingestion.
How many objects can be ingested in one pipeline?
Databricks recommends limiting one pipeline to 250 objects. If you need to ingest more objects, create multiple pipelines.
What happens if I hit Meta API rate limits?
If the connector encounters rate limit errors from the Insights API, it automatically retries with exponential backoff. The connector waits 1 second before retrying, then 2 seconds, then 4 seconds, and so on. If rate limits persist, the pipeline fails, and you can retry on the next scheduled run.
To avoid rate limit issues, consider:
- Reducing the frequency of your pipeline schedule
- Reducing the number of objects ingested in a single pipeline
- Spreading ingestion across multiple pipelines
Can I configure custom attribution windows?
No. In Beta, attribution windows are fixed at 7 days for click attribution and 1 day for view attribution. Custom attribution windows aren't configurable.
Does the connector support Instagram ads?
No. The connector only supports Facebook Ads during Beta. Instagram Ads aren't supported.
Does the connector support real-time ingestion?
No. The connector uses scheduled batch ingestion. Real-time ingestion isn't supported. You can schedule your pipeline to run as frequently as hourly, but Databricks recommends less frequent schedules to avoid rate limit issues.
How does the connector handle deletes?
The connector doesn't detect or handle deletes. If a record is deleted from Meta Ads, it remains in the destination table. To remove deleted records, you must perform a full refresh of the table.
Why is my ad_insights data incomplete for recent dates?
The ad_insights object uses an attribution window to account for delayed conversion events. Data for recent dates may be incomplete until the attribution window closes (7 days for click attribution, 1 day for view attribution). The connector automatically ingests updated data on subsequent pipeline runs.
Which breakdown combinations are supported for ad_insights?
The connector supports all breakdown and action breakdown combinations that are allowed by the Insights API. Some combinations may not be valid. Check the Insights API documentation for details on valid breakdown combinations.
When will UI-based pipeline creation be available?
UI-based pipeline creation isn't available during Beta. Use the Databricks CLI, APIs, SDKs, or Databricks Asset Bundles to create pipelines. UI support may be added in a future release.