Forum Discussion
Incremental refresh with polling expression
Go with the timestamp that has the most even distribution (likely the created date). Create a large enough "hot" window to cover most of the jitter (modifications happening soon after creation). For example make your "hot" partitions the last three months instead of the last month. Then use the Modified date to catch any entries that fall outside the "hot" window and manually refresh their partitions if needed. Plan on doing a full refresh (or a sequential manual refresh of all partitions) every now and then.
No, based on what you've said the problem is with the performance of the SQL queries themselves and nothing to do with Power BI. You need to get a DBA or someone familiar with SQL performance tuning to help you here.
Thanks a lot cpwebb
Currently, we have a 6-month dataset, including a large table with over 2 million rows. The entire dataset is refreshed in the Power BI service every 30 minutes, taking maximum 2-3 minutes.
For the other dataset (3 years), which has refreshing issues, I partitioned the large table and each partition contains a maximum of 700k rows. but, each of these partitions takes not less than 2 minutes to refresh, which doesn't make sense.
Could this be because the Power BI service allocates more resources than PowerShell in Azure Runbooks?
Thanks again.
No, based on what you've said the problem is with the performance of the SQL queries themselves and nothing to do with Power BI. You need to get a DBA or someone familiar with SQL performance tuning to help you here.