The operation was throttled by Power BI Premium

[Anonymous]

Hi All,

The Power BI Data set is taking too much time to get refresh on PBI service, I am getting following error:

The operation was throttled by Power BI Premium because there were too many datasets being processed concurrently. Please try again later.

Please kindly help me out of this, its on high priority.

Thanks

Deepak

[v-xicai · Accepted solution]

Hi @Anonymous ,

For more details about why you get the above error, please review Yaswanth's reply in this similar thread.

In your scenario, please set schedule refresh for different datasets at different times, and make sure that you are using the latest version of gateway.

Please make sure that you don't schedule more than max parallel refreshes for the different nodes in these capacities. Also we suggest that you first disable all refreshes on all capacities. Then slowly enable the refreshes one by one. Make sure refreshes are staggered apart (e.g. 1 hour apart), and that no more than max concurrent refreshes happen at overlapping time periods.

You can also review the following articles to learn about how premium works.

https://docs.microsoft.com/en-us/power-bi/service-admin-premium-monitor-capacity

https://docs.microsoft.com/en-us/power-bi/service-premium-understand-how-it-works

Best Regards,

Amy

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[nickyvv]

Please refer to the this page about Premium.
For a P1 you can only refresh 6 datasets concurrently. Any other datasets will have to wait in queue. The important part of the documentation is this:

Refreshes, like queries, require the model be loaded into memory. If there is insufficient memory, the Power BI service will attempt to evict inactive models, and if this is not possible (as all models are active), the refresh job is queued. Refreshes are typically CPU-intensive, even more so than queries. For this reason, there are capacity limits on the number of concurrent refreshes, set to 1.5 x the number of backend v-cores, rounded up. If there are too many concurrent refreshes, a scheduled refresh will be queued. When these situations occur, it takes longer for the refresh to complete. On-demand refreshes such as those triggered by a user request or an API call will retry three times [1]. If there still aren't enough resources, the refresh will then fail.

So to solve your issues, you'll want to have a look at the Premium Capacity Metrics App and look at other refreshes happening at the same time.

Did this help you or did I answer your question?
Then please give kudos or mark my post as a solution!
My blog: nickyvv.com