The error "The XML for Analysis request timed out before it was completed" usually indicates that the query is taking too long to process in the Power BI Service, especially on a premium node. Here are some steps you can try to troubleshoot and potentially resolve this:
1. Optimize Query Performance:
- Review DAX Calculations: Complex DAX queries can significantly impact refresh times, especially with large datasets. Look for any potential optimizations, such as simplifying calculations, avoiding complex filters, or using aggregations.
- Reduce Dataset Size: If possible, consider reducing the dataset size by filtering or aggregating data in advance. This can often be done at the data source level or by using dataflows to pre-aggregate data.
2. Increase Query Timeout:
- Power BI Service has a default timeout setting, but for premium capacities, you might be able to adjust the timeout by changing settings in the capacity. Check the Power BI Admin Portal under "Capacity settings" for any configurable options for query timeouts.
3. Monitor and Troubleshoot with Performance Analyzer:
- In Power BI Desktop, use the Performance Analyzer (under View tab) to capture detailed logs of the query timings. This can help identify which specific part of the query or model is causing the delay.
- Also, look at the query duration in Power BI Service by accessing the Refresh History in the workspace settings, which may provide additional insights on how long each part of the query is taking.
4. Partitioning Data (if applicable):
- If you’re working with large datasets, consider partitioning the data. Partitioning helps by loading data in segments, allowing for quicker refreshes in the service.
5. Review Premium Capacity Usage:
- In the Power BI Admin Portal, review metrics for your premium capacity to see if there’s resource contention during the refresh window. If other workloads are consuming significant resources, it could be delaying or timing out the refresh.
6. Consider Dataflows and Incremental Refresh:
- Since you’ve already tried dataflows, ensure that incremental refresh is configured if your data allows for it. Incremental refresh minimizes the amount of data processed during each refresh by only refreshing new or changed data.
7. Check the Data Source Configuration:
- For SSAS sources, confirm that the server’s performance and network bandwidth are sufficient to handle the load. Also, ensure that the server isn’t experiencing any throttling or resource issues during the scheduled refresh time.
If none of these steps help, you may need to open a support ticket with Microsoft, especially if the refresh works locally but consistently fails in the service.
