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Hi,
We have mulitple reports using some similar tables and we are thinking about using dataflows as source for the reports.
Although the tables are the same, some parts of the queries are different for different reports. We are thinking about making mulitple dataflows of one table for this reason.
Should I make multiple dataflows with different queries for one table and use the dataflow that is specific for the report?
Does the make of different/mulitple dataflows affect capacity, or more than without dataflows???
Solved! Go to Solution.
Hi @Anonymous ,
1. Different queries need different dataflows even though you used the same source.
2. When refreshing a dataflow, the dataflow workload spawns a container for each entity in the dataflow. Each container can take memory up to the volume specified in the Container Size setting. The default for all SKUs is 700 MB. You might want to change this setting if:
It's recommended you use the Power BI Premium Capacity Metrics app to analyze Dataflow workload performance.
In some cases, increasing container size may not improve performance. For example, if the dataflow is getting data only from a source without performing significant calculations, changing container size probably won't help. Increasing container size might help if it will enable the Dataflow workload to allocate more memory for entity refresh operations. By having more memory allocated, it can reduce the time it takes to refresh heavily computed entities.
The Container Size value can't exceed the maximum memory for the Dataflows workload. For example, a P1 capacity has 25GB of memory. If the Dataflow workload Max Memory (%) is set to 20%, Container Size (MB) cannot exceed 5000. In all cases, the Container Size cannot exceed the Max Memory, even if you set a higher value.
If you'd like to refresh the dataset with a large model, you might refer to the official document: You can use incremental refresh to configure a dataset to grow beyond 10 GB
https://docs.microsoft.com/en-us/power-bi/service-premium-large-models
Also, if you'd like to split the dataset into several dataflow and run the number of parallel model refreshes. Kindly note the below limitations:
https://docs.microsoft.com/en-us/power-bi/service-premium-what-is#capacity-nodes
Hi @Anonymous ,
1. Different queries need different dataflows even though you used the same source.
2. When refreshing a dataflow, the dataflow workload spawns a container for each entity in the dataflow. Each container can take memory up to the volume specified in the Container Size setting. The default for all SKUs is 700 MB. You might want to change this setting if:
It's recommended you use the Power BI Premium Capacity Metrics app to analyze Dataflow workload performance.
In some cases, increasing container size may not improve performance. For example, if the dataflow is getting data only from a source without performing significant calculations, changing container size probably won't help. Increasing container size might help if it will enable the Dataflow workload to allocate more memory for entity refresh operations. By having more memory allocated, it can reduce the time it takes to refresh heavily computed entities.
The Container Size value can't exceed the maximum memory for the Dataflows workload. For example, a P1 capacity has 25GB of memory. If the Dataflow workload Max Memory (%) is set to 20%, Container Size (MB) cannot exceed 5000. In all cases, the Container Size cannot exceed the Max Memory, even if you set a higher value.
If you'd like to refresh the dataset with a large model, you might refer to the official document: You can use incremental refresh to configure a dataset to grow beyond 10 GB
https://docs.microsoft.com/en-us/power-bi/service-premium-large-models
Also, if you'd like to split the dataset into several dataflow and run the number of parallel model refreshes. Kindly note the below limitations:
https://docs.microsoft.com/en-us/power-bi/service-premium-what-is#capacity-nodes