Google Analytics Aggregated connector limitations

Important

This feature is in Beta. To use it, a workspace admin must turn on Lakeflow Connect for Google Analytics Aggregated from the Previews page. See Manage Azure Databricks previews.

The managed Google Analytics Aggregated connector in Lakeflow Connect ingests only aggregated report data, runs each custom report against a single property, and consumes Google Analytics Data API quota on every request.

General software as a service (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 Google Analytics Aggregated connector.

• To analyze individual events, use the Google Analytics Raw Data connector. This connector ingests only the aggregated Google Analytics 4 (GA4) reports that the Google Analytics Data API returns, so event-level rows aren't available.
• To ingest dimensions or metrics that a prebuilt report table doesn't include, use the custom_report table. Each prebuilt table requests a fixed set of dimensions and metrics, so it doesn't contain other columns. See Custom reports.
• To run a custom report against several GA4 properties, add a custom_report object for each property, each with a different destination_table. Each object accepts a single property_id, so each property's report lands in its own destination table.
• To aggregate a custom report by week, month, or year, set cursor_dimension to yearWeek, yearMonth, or year. The connector accepts only these values and date, so a custom report can't aggregate over other periods. The prebuilt report tables aggregate by day, except weekly_events_report, which aggregates by GA4 week.
• To reduce quota use, ingest fewer tables or properties in each pipeline, or set a later start_date. The connector requests day-aggregated tables one day at a time, and every request consumes property quota tokens, so large pipelines can reach a property's quota. When that happens, the connector backs off and retries, and the run fails if the quota doesn't recover before the retries run out. For quota limits, see Limits and quotas in the Google documentation.