Alteryx reports requested dedicated memory more than physical but plenty is available

[SamDesk]

Hi All,

Getting the following error:

Info: Designer x64: The Designer x64 reported: Allocating requested dedicated sort/join memory would be more than available physical memory.  Reverting to 1296MB of memory.

But I have plenty of RAM available, 16/32GB at the time of running as you can see in the below screenshot.

Spoiler

Potentially useful information

• Multiple instances (3) of Alteryx are open across several virtual desktops
• Running on Windows 10 with 32GB RAM, 16GB available at the time of running
• When running I am seeing values on individual tools that might exceed the available 16GB but I am unsure of what these values mean in the sense of if they are running totals or individual to the tools.

Spoiler

Thanks for any help you can offer.

Sam :)

[CharlieS]

In user settings, what is your "Default Sort/Join Memory" set at? It's my understanding that the engine will start by allocating that amount of memory, and increase it as needed. If you already had three other workflows running, those engine instances would have allocated 3x you default value or more, so that when this instance started only 1296MB was not already claimed by another engine instance.

https://help.alteryx.com/10.0/Memory_Utilization.htm

"A typical best practice is to ensure that this is set to half of the physical memory divided by the number of simultaneous processes you expect to run."

[SamDesk]

Hey @CharlieS,

It's left at the Alteryx set default value (i.e. not ticking the override box) and is set to 8156 MB. Also, the other workflows where open but none of them were running.

Sam :)

[CharlieS · Accepted solution]

Cool. That's the recommended setting so that makes sense. Lowering that setting is an option if you so desire since the engine will expand the memory allocated as needed anyways,

The message you got was really just a notification. There is an "Unable to allocate system memory" error that will occur if you really run out of available memory and will stop your workflow.