Skip to main content
cancel
Turn on suggestions
Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.
Showing results for 
Search instead for 
Did you mean: 

A new Data Days event is coming soon! This time we’re going bigger than ever. Fabric, Power BI, SQL, AI and more. Don't miss out.

Memory error: Memory Allocation failure. Try simplifying or reducing the number of queries.

Submitted by Anonymous on ‎08-09-2023 03:04 AM

Hi,

While importing data in Power BI Desktop from Power BI Dataflow, I am getting error - "Memory error: Memory Allocation failure. Try simplifying or reducing the number of queries".

 

The dataflow contains more than 2 years of data and requirement is to import data for last 2 years.

For filtering data, I am using Date/Time parameter.

I am able to import data for a month which consists of 6 tables (2.1 lakhs rows each and 26 columns each). But, when I am trying to import more data, i.e. for more number of months, it is throwing above mentioned error.

I tried changing sequence of table loading, but still the issue exists.

 

Data is currently being imported for a month and requirement is to import it for last 2 years. Any suggestions ??

 

Thanks in advance.

 

Memory Allocation Error.jpg

Status: Investigating
See more ideas labeled with:
1 Comment (1 New)
Comments
Anonymous
Not applicable
‎08-09-2023 07:16 PM

Hi  @Anonymous ,

 

It sounds like you are running into a memory allocation issue when trying to import a large amount of data into Power BI Desktop from a Power BI Dataflow. One potential solution would be to simplify or reduce the number of queries that you are using to import the data.

Another option would be to try and optimize the queries themselves to reduce the amount of memory required to import the data. This could involve filtering the data in the Power BI Dataflow before importing it into Power BI Desktop, or reducing the number of columns that you are importing.

You could also try increasing the amount of memory available to Power BI Desktop by adjusting the memory settings in the Options menu. However, this may not be a viable option if you are working with limited resources.

Finally, you could consider breaking up the data into smaller chunks and importing it into Power BI Desktop in stages. This would allow you to work with the data in smaller, more manageable pieces and avoid running into memory allocation issues.

 

Best regards.
Community Support Team_Caitlyn

 

 

Idea Statuses