How to Debug Out of Memory Errors in a Workflow Where Files are Moved via /tmp?

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This topic was automatically generated from Slack. You can find the original thread here.

How can I debug Out of Memory errors?

I am constantly hitting that error on a workflow, all files are being moved via /tmp and the documentation does not give much help after that. Note that the error is raised before even running the trigger which is even more baffling

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Are you using built-in actions? Or custom code?

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Are you able to check if you are streaming the data instead of loading it all into memory at once?

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I have a couple of builin actions and 3 code blocks.
The most memory intensive thing going on is PyPDF to extract PDF text. But the whole PDF is 300Kb so it is impossible it is taking up 256Mb!

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Got it, yeah I know it doesn’t look like that can be the issue but it could have some memory leakage there

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See this similar issue: [BUG] Microsoft OneDrive Upload File action not streaming · Issue #15845 · PipedreamHQ/pipedream · GitHub

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In our testing, a 20MB attachment still errored in a 2GB memory workflow in the OneDrive action, while the same in Google Drive (that had streaming) worked well in a 256MB memory workflow

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We gotta add this to our docs

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How can I dig deeper; or is there any possible workaround? I currently have zero clues on where to patch things as the OOM error is triggered at the top

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Still, even with a memory leak: this is an incoming mail with a 200-300Kb attachment that is written to /tmp, read from Python, and then read again from JavaScript to submit it via an API call.

I would think I’d need a few hundred runs to exhaust 256Mb!

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Yeah currently is hard to debug, but FYI you won’t be charged credits when testing in the builder

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But feel free to submit a support ticket if you need further help

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Is it possible to see what steps are using how much memory while in the builder?

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There isn’t a view for that, but we noticed this bug happening with the One Drive Upload File action even with a few KBs file due to memory leak. After changing it to stream the file instead of loading it all to memory, this issue was fixed. See this commit: