[PROF-10124] Lower value used to clamp very high allocation profiling weights#3793
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… weights **What does this PR do?** This PR lowers the profiling internal constant `MAX_ALLOC_WEIGHT` from 65535 to 10000. This value is used when clamping very high allocation profiling weights. Aka: Each allocation sample taken by the profiler has a weight assigned to it; this weight is clamped (e.g. limited to) this maximum value. The remaining weight is assigned to a separate "skipped samples" placeholder (see #3792). **Motivation:** Very large weights on samples can produce biased results; by lowering the maximum we reduce the maximum bias that can ever be introduced. **Additional Notes:** I've gathered data from a number of apps when choosing this value, see <https://docs.google.com/document/d/1lWLB714wlLBBq6T4xZyAc4a5wtWhSmr4-hgiPKeErlA/edit> for details (Datadog-only link, sorry!). **How to test the change?** The tests for #3792 also cover this change (although the changes are otherwise independent).
BenchmarksBenchmark execution time: 2024-07-18 10:52:23 Comparing candidate commit 4cd8e7b in PR branch Found 0 performance improvements and 0 performance regressions! Performance is the same for 10 metrics, 2 unstable metrics. |
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## master #3793 +/- ##
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Coverage 97.91% 97.91%
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Files 1246 1246
Lines 75037 75037
Branches 3629 3629
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+ Hits 73473 73474 +1
+ Misses 1564 1563 -1 ☔ View full report in Codecov by Sentry. |
anmarchenko
approved these changes
Jul 24, 2024
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What does this PR do?
This PR lowers the profiling internal constant
MAX_ALLOC_WEIGHTfrom 65535 to 10000.This value is used when clamping very high allocation profiling weights.
Aka: Each allocation sample taken by the profiler has a weight assigned to it; this weight is clamped (e.g. limited to) this maximum value. The remaining weight is assigned to a separate "skipped samples" placeholder (see #3792).
Motivation:
Very large weights on samples can produce biased results; by lowering the maximum we reduce the maximum bias that can ever be introduced.
Additional Notes:
I've gathered data from a number of apps when choosing this value, see https://docs.google.com/document/d/1lWLB714wlLBBq6T4xZyAc4a5wtWhSmr4-hgiPKeErlA/edit for details (Datadog-only link, sorry!).
How to test the change?
The tests for #3792 also cover this change (although the changes are otherwise independent).