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Tracing
#rstats allocations for a production Shiny app using#bpf. Inspired by my reading of@brendangregg's wonderful new BPF book. Source: https://gist.github.com/atheriel/20f41cef79a9d13435a644d2ae3ff4cd …pic.twitter.com/jmoORQ1vp0
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There is nothing *quite* so satisfying as optimizing the hell out of some
#rstats function with#rcpp. (Though, in my experience, 800x speedups like this are pretty rare.)pic.twitter.com/h56HH0NeyZ
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Turns out you *can* strip out some of the tryCatch() overhead in APIs by compiling the
#rstats {httpuv} package with an additional flag. Relevant GitHub issue: https://github.com/rstudio/httpuv/issues/244 …pic.twitter.com/jpB3aeETou
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Flamegraph of an actual production
#rstats Plumber API. A surprising amount of the call depth is due to tryCatch and promise handling... I wonder if some of that could be avoided.pic.twitter.com/Vxg2EZb85Z
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There are really only two important things in life: bias and variance. -- Andrew Gelman (https://youtu.be/ZmbrsbYwRWw )
#rstats
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