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TikTok Ads connector limitations

Beta

This feature is in Beta.

General SaaS connector limitations​

The limitations in this section apply to all SaaS connectors in Lakeflow Connect.

  • When you run a scheduled pipeline, alerts don't trigger immediately. Instead, they trigger when the next update runs.
  • When a source table is deleted, the destination table is not automatically deleted. You must delete the destination table manually. This behavior is not consistent with Spark Declarative Pipelines on Lakeflow behavior.
  • During source maintenance periods, Databricks might not be able to access your data.
  • If a source table name conflicts with an existing destination table name, the pipeline update fails.
  • Multi-destination pipeline support is API-only.
  • You can optionally rename a table that you ingest. If you rename a table in your pipeline, it becomes an API-only pipeline, and you can no longer edit the pipeline in the UI.
  • If you select a column after a pipeline has already started, the connector does not automatically backfill data for the new column. To ingest historical data, manually run a full refresh on the table.
  • Databricks can't ingest two or more tables with the same name in the same pipeline, even if they come from different source schemas.
  • The source system assumes that the cursor columns are monotonically increasing.
  • The connector ingests raw data without transformations. Use downstream Spark Declarative Pipelines on Lakeflow pipelines for transformations.

Connector-specific limitations​

The limitations in this section apply to the TikTok Ads connector.

  • Some tables don't support incremental ingestion because the API doesn't support filtering based on a cursor. These tables are refreshed on each pipeline update. For a list of tables that support incremental ingestion, see Tables that support incremental updates.
  • Report data is only supported for reports with fewer than 20,000 ads. If a report includes 20,000 or more ads, TikTok's synchronous reporting API truncates the results, and report data might be incomplete.
  • SKAN metrics aren't supported for hourly reports.
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