Forum Discussion
Performance Optimization for Power BI Row Level Security Model
Hi sumanthkakarla,
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Hi sumanthkakarla,
Thank you for your inquiry through the Microsoft Fabric Community Forum.
Implementing Row-Level Security (RLS) in Power BI for a large user base necessitates careful optimisation to maintain performance. Kindly follow the steps outlined below to enhance efficiency:
- Establish relationships using integer keys instead of strings for efficient joins.Since this has already been implemented, you are on the right track.
-
Instead of using MAXX and FILTER, consider a more direct approach, as illustrated below:
'NEW_ACCOUNT_MAP'[USERNAME] = USERPRINCIPALNAME() || 'NEW_ACCOUNT_MAP'[CLIENT_ACCOUNT_NUMBER] = "ALL"
This expression verifies whether the logged-in user has access to specific accounts or all accounts directly, thereby reducing computational overhead. - If high granularity is unnecessary, aggregate data before importing to reduce processing load.
- Measures are computed on demand, making them more efficient than calculated columns. Additionally, simplify DAX expressions to minimise the use of complex filters and calculations within measures.
- Regularly track usage and assess user concurrency to prevent performance issues.
For further reference, please visit:
Row-level security (RLS) guidance in Power BI Desktop - Power BI | Microsoft LearnIf this response is helpful, kindly mark it as the accepted solution and provide kudos to assist other community members.
Thank you.
v-pnaroju-msft , to avoing many to many relationship i tred the brige table, somehow this is also not working, not sure whats wrong with my data model, userlookup( al distinct users) filter bridge table for a given login user, bridge table should filter client_lookup( distinct client account numebrs), client_lokup should filter the fact table for those users acccessed accounts data, please note i am giving Dynamic RLS as this on user_lookup table , whats worng with my data model ? why i amnot able to see when i apply Dynamic RLS ?
