test(profiling): add profiles dictionary benchmarks#2088
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How stable is the benchmark in your experience so far? It seems like it would be pretty variable, but at least you have a startup barrier in there.
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@morrisonlevi Good question, I checked this again. I think I remember trying benchmark runs on gitlab multiple times and got stable results, I'm going to re-run them again at the latest commit for updated data. From my local runs using workspaces,
at least for 1 ~2 threads cases which I believe more resembles the case of dd-trace-py and ddprof profilers, are stable enough to be used as a baseline. Yeah, the barrier helps avoid measuring staggered thread starts. |
The generated input shares some full strings across workers, so "unique_string_inserts" was misleading. Rename the benchmark group and function to "profile_string_inserts" and update the comments to match. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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What does this PR do?
Adds a focused Criterion benchmark for
ProfilesDictionaryunique string insertion.The benchmark uses
ProfilesDictionaryand covers 1, 2, 4, and 16 producer threads, so follow-up arena sizing/growth changes have a baseline in the GitLab benchmark job.#2048 changes the default configs for the ProfilesDictionary
Why these thread counts?
This benchmark is focused on dictionary string interning. It is not a full end-to-end profiler benchmark.
In dd-trace-py, profile mutation and serialization are guarded by
profile_mtx, but dictionary interning can happen before a sample is added to the profile. This means dictionary insertion can still be concurrent even when profile writes are serialized.What this does not cover
This benchmark does not model every profiler behavior. In particular, it does not cover:
Why only
ProfilesDictionary?I originally tried an additional synthetic benchmark comparing 4 vs 16 shards. Local exploratory results suggested 16 shards helps once there is concurrent insertion:
However, that synthetic comparison also changed total initial hash-table capacity because the capacity was applied per shard. Since the current follow-up keeps the production shard count at 16, this PR stays minimal and only adds the
ProfilesDictionarybenchmark.If we revisit shard count later, we should add a dedicated shard-count benchmark that holds total starting capacity constant across shard counts.
How to test the change?
PROF-14423