Forum Discussion
BUG::TIMEOUT PERIOD ELAPSED::POOL ERROR::IDbConnection interface
The issue didn't reoccur without me doing anything... so obviously something on the backend got fixed or it is randomly intermittent and will rear its ugly head again.
Hi Element115
Thanks for using Microsoft Fabric Community.
Apologies for the inconvenience.
The error message indicates that the Power BI slicer linked to the dim table in the live connection is experiencing a timeout issue.
- Click on "Refresh" in the Power BI Desktop ribbon. This might establish a new connection to the LH and resolve the timeout issue.
- In some cases, a corrupted slicer object might be causing the issue. Try deleting the current slicer and recreating it from the dim table in the LH.
- If a connection issue is suspected, delete the existing relationship between the dimension and fact table. Subsequently, re-establish the relationship using the appropriate columns. This process can sometimes help resolve connection errors.
I hope this information helps. Please do let us know if you have any further queries.
Thank you.
Hi Element115
We haven’t heard from you on the last response and was just checking back to see if you have a resolution yet. In case if you have any resolution please do share that same with the community as it can be helpful to others.
Otherwise, will respond back with the more details and we will try to help.
Thanks.
Thanks.
On closing/reopening the report, the slicer reloaded normally. I do notice though that all slicers seem to have long load time. These are linked to small dim tables stored in the LH, so it's kind of puzzling why the load times in DirectQuery are so slow for what amounts to 2 - 10 row tables with no more 3-10 columns.
Hi Element115
Apologies for the inconvenience.
While the initial connection pool issue seems to be resolved by reopening the report, the overall slow slicer load times for small dim tables in DirectQuery mode require further investigation.
The following are potential approaches to explore which might help you.
- Latency and Network Issues: Despite the small size of the dimension tables, any latency or network disruptions between Power BI Desktop and the Lakehouse can significantly impact load times. It’s essential to verify network stability.
- Lakehouse Query Processing: Although the dimension tables themselves are small, the Lakehouse’s query processing may introduce inefficiencies. Investigate whether there are specific optimizations for querying small tables within your Lakehouse platform.
- Power BI Caching: Ensure that Power BI effectively caches slicer data for these small tables. You can force a cache refresh by navigating to File > Options and Settings > Options > Global. Under ‘Data Load,’ select ‘Clear cache’ and observe if it improves slicer load times."
I hope this information helps. Please do let us know if the issue still persists.
Thank you.
Hi Element115
We haven’t heard from you on the last response and was just checking back to see if you have a resolution yet. In case if you have any resolution please do share that same with the community as it can be helpful to others.
Otherwise, will respond back with the more details and we will try to help.Thank you.