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r-autometric

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Intense parallel workloads can be difficult to monitor. Packages 'crew.cluster', 'clustermq', and 'future.batchtools' distribute hundreds of worker processes over multiple computers. If a worker process exhausts its available memory, it may terminate silently, leaving the underlying problem difficult to detect or troubleshoot. Using the 'autometric' package, a worker can proactively monitor itself in a detached background thread. The worker process itself runs normally, and the thread writes to a log every few seconds. If the worker terminates unexpectedly, 'autometric' can read and visualize the log file to reveal potential resource-related reasons for the crash. The 'autometric' package borrows heavily from the methods of packages 'ps' <doi:10.32614/CRAN.package.ps> and 'psutil'.

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Summary

Intense parallel workloads can be difficult to monitor. Packages 'crew.cluster', 'clustermq', and 'future.batchtools' distribute hundreds of worker processes over multiple computers. If a worker process exhausts its available memory, it may terminate silently, leaving the underlying problem difficult to detect or troubleshoot. Using the 'autometric' package, a worker can proactively monitor itself in a detached background thread. The worker process itself runs normally, and the thread writes to a log every few seconds. If the worker terminates unexpectedly, 'autometric' can read and visualize the log file to reveal potential resource-related reasons for the crash. The 'autometric' package borrows heavily from the methods of packages 'ps' <doi:10.32614/CRAN.package.ps> and 'psutil'.

Last Updated

Sep 24, 2025 at 22:47

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MIT

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