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Unfortunately we can't say what exactly is happening. If you can provide a simpler runnable reprex, or if you can isolate the problem to |
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Recently, I found that if I have roughly 10k targets in a project, and {crew} scheduler will consume a crazy 40 GiB memory. But that is not an issue for the superseded Although it is probably not good practice for having so many targets in a project, the fact is that data analysis goes into many branches very quickly! Therefore, the behavior like |
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I am sorry I cannot provide a simole reprex for this. But for a large project, e.g., my pipeline script, if {crew} is used for parallel analysis, I constantly get the following error:
But if I use
targets::tar_make_future()
, it never fails. I guess it is because {crew} dispatches all the targets though pending.Beta Was this translation helpful? Give feedback.
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