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Surekha_PM's avatar
Surekha_PM
Resolver I
8 months ago
Solved

Resources Exceeded Error

Hi Everyone, I am using a star schema where one table is connected with 6 tables. There are also 2 calculated tables, which are the split of another table to check two different categories. There ...
Need Help
  • Surekha_PM's avatar
    Surekha_PM
    8 months ago

    Hello @EsraaKamal, @rohit1991, @srlabhe and Anonymous,

    I appreciate how quickly you responded and provided a solution.

    I tried every solution, but none of them were able to fix the problem. This is because the problem with my data set was different. Two date tables that I was using had non-continuous dates. The data load issue was resolved after those tables were removed.


    Again, thank you very much for your support, everyone.



    Regards,
    Surekha 

AntoineW's avatar
AntoineW
Super User
8 months ago

Hi Surekha_PM,

 

The “Resources Exceeded” error usually appears when Power BI detects that a query requires too much memory or CPU because the model structure forces expensive operations — even if the dataset is small (40k rows is not an issue by itself).

Looking at your model, there are a few likely causes and ways to fix them:

✅ 1. Too many bi-directional or ambiguous relationships

Your schema shows several tables connected in multiple directions.
When a visual runs, Power BI must resolve filter propagation across all paths — this can trigger:

  • relationship ambiguity

  • large auto-exist operations

  • expensive cross-joins

  • excessive memory usage

➡ Fix

  • Switch relationships to single-direction wherever possible

  • Keep a clear separation: dimension tables → fact table (one direction)

  • Avoid bi-directional or many-to-many relationships unless absolutely necessary

✅ 2. Too many calculated tables — computed at query time

You mentioned 4 calculated tables, including date tables and split versions of existing tables.

Calculated tables are stored but their logic is executed during model load and sometimes referenced at query time, which can increase memory pressure.

➡ Fix

  • Replace calculated tables with Power Query transformations

  • For date ranges (last 30 days, yesterday, etc.), use DAX measures, not calculated tables

✅ 3. A “snowflake” or circular filtering design

Your screenshot shows multiple fact-like tables linking with multiple dimensions, creating complex filter paths.

This is a typical scenario where visuals explode into large intermediate joins, even with small data volumes.

➡ Fix

  • Simplify the schema to a proper star model

  • Avoid dimension → dimension chains

  • Merge small lookup tables in Power Query if possible

 

Even though your dataset is small (40k rows), the relationship logic can make Power BI behave like it’s processing millions, because the engine tries to resolve every possible combination.

Optimizing the data model is the real fix here — not increasing capacity.

 

Hope it can help you !

Best regards,

Antoine