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Kim Gustyr
11a09af20d
All numbers on one machine and environment, attributed in the docs: Apple M2 Pro, ClickHouse 25.12.11.4 in Docker, Python 3.11.11. Methodology change: scripts end their imports with 'import timing' (new perf/timing.py) which starts the clock and reports wall time and max RSS at exit. Interpreter startup and imports are excluded from timings; importing the numpy/pyarrow stack costs ~0.5 s and dominated sub-second cells under whole-process timing. New typed-projection PyArrow scripts (21-24) cover analytic extracts: int and string column subsets, clickhouse-driver vs clickhouse-connect. All perf scripts carry PEP 723 blocks with pinned versions. Scripts 15-17 updated to the current clickhouse-connect streaming API. beep boop
16 lines
396 B
Python
16 lines
396 B
Python
import atexit
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import resource
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import sys
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import time
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_start = time.monotonic()
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@atexit.register
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def _report():
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elapsed = time.monotonic() - _start
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rss = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
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if sys.platform != "darwin":
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rss *= 1024 # Linux reports kilobytes, macOS reports bytes.
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print("{:.2f} s / {} bytes max RSS".format(elapsed, rss), file=sys.stderr)
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