chore(swingset): add tools to classify mainnet runs #8680
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@toliaqat hey, what should we do about this one? I'm inclined to land it, so at least the classification logic is available for folks to look at, even if it's in python instead of js. |
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@warner I think we should merge this in the misc-tools even if it is in Python. I like the idea given in the last meeting that we can have this Python code run in a job on the slog files from blob storage. I want to create this pipeline so that we can start injecting such tools to export the metrics on datadog at regular intervals. decoupling the developer who wrote the tool from potential users of the outcome. |
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Feed a slogfile into stdin of `classify-runs.py`, and it will write
one line per run to two output files (runs-separate.csv and
runs-continued.jsonlines), describing why the run was
performed (price-feed, psm-sell, etc, known as the "type" of the run),
along with the b${blockNum}-r${runNum} identifier, the number of
computrons consumed, and the number of wallclock seconds consumed. See
the header of classify-runs.py for details.
Feed the .csv to the stdin of `classify-types.py`, and it will emit a
table of statistics about those types, like the median wallclock time
consumed.
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Feed a slogfile into stdin of
classify-runs.py, and it will emit one line per run, describing why the run was performed (price-feed, psm-sell, etc, known as the "type" of the run), along with the b${blockNum}-r${runNum} identifier, the number of computrons consumed, and the number of wallclock seconds consumed.Feed all those output lines into the stdin of
classify-types.py, and it will emit a table of statistics about those types, like the median wallclock time consumed.