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HI DavidK,
This should more be related to your data amounts. After I finish checked your sample file and I found they have 81M and 40K records.
For this scenario, your formula will iterator and calculate through over more than 3240B(81M x 40K) rows. It obviously will spend a huge amount of system resources to calculate.
If you add more conditions to your expression, it will cost more resources than fewer conditions version. (it looks like your device are good enough to process the simple version but failed on more condition versions)
In my opinion, I'd like to suggest you use measure expression instead of the calculated column formula, it only calculates when you use it to analyze visualizations.
In addition, you can also try to do some pre-aggregate on your result to reduce the looping range of records, then you can calculate on fewer records to avoid the 'memory allocation' issue.
Notice: 1GB memory equal to 1,048,576KB. If we suppose each 100K rows looping will spend 1 KB memory, 3240B rows also required 31 GB memory to quick cache and calculate on the expanded range of records or spend more time to execute with idle resources until calculation timeout. (the real scenario and calculation may not such complex or poor performance than I supposed)
Regards,
Xiaoxin Sheng
Hi DavidK,
How many idle memory your device has, did you work on the 32-bit desktop client?AFAIK, 32bit has 4GB memory limit on application usage:
Memory Limits for Windows and Windows Server Releases
I think this should be related to iterator calculations, you're formula will calculate on each row in the 'Combination' table to iterate and check with sale tables records. ('combination' row count X 'sales' table row count)
Optimizing nested iterators in DAX
BTW, you can also use Dax studio to trace how many rows DAX formula calculate across:
Regards,
Xiaoxin Sheng
I can ´t understand why it doesn ´ work corect 😞 ....i add here example with training data. Please would you be so kind and check where i do mistake 😞
https://drive.google.com/drive/folders/1XoFc1e0odTNQ1SiNO6hIV1-9F-gGpjrD?usp=sharing
Thank you in advance.
HI DavidK,
This should more be related to your data amounts. After I finish checked your sample file and I found they have 81M and 40K records.
For this scenario, your formula will iterator and calculate through over more than 3240B(81M x 40K) rows. It obviously will spend a huge amount of system resources to calculate.
If you add more conditions to your expression, it will cost more resources than fewer conditions version. (it looks like your device are good enough to process the simple version but failed on more condition versions)
In my opinion, I'd like to suggest you use measure expression instead of the calculated column formula, it only calculates when you use it to analyze visualizations.
In addition, you can also try to do some pre-aggregate on your result to reduce the looping range of records, then you can calculate on fewer records to avoid the 'memory allocation' issue.
Notice: 1GB memory equal to 1,048,576KB. If we suppose each 100K rows looping will spend 1 KB memory, 3240B rows also required 31 GB memory to quick cache and calculate on the expanded range of records or spend more time to execute with idle resources until calculation timeout. (the real scenario and calculation may not such complex or poor performance than I supposed)
Regards,
Xiaoxin Sheng