[APR-205] core: track seen data types in event buffers

[tobz]

Context

This PR updates EventBuffer to track the data types it has seen for events currently in the buffer. As DataType is already a bitfield, we simply OR the data type of an event being added (whether through EventBuffer::push or Extend) to a new field, seen_data_types, and expose a new method -- EventBuffer::has_data_type -- that checks if a given data type is contained in seen_data_types. Care is taken to ensure that seen_data_types is reset when the buffer is cleared.

This allows code which intermingles multiple data types in a single EventBuffer to efficiently know if there's a need to filter out/split the buffer into multiple buffers, such as when the buffer must have a homogenous event type, without having to first iterate over it.

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Regression Detector (DogStatsD)

Regression Detector Results

Run ID: 29d94e69-67bb-4826-8af0-800d71cee9ef

Baseline: 7.52.0 Comparison: 7.52.1

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Fine details of change detection per experiment

| perf | experiment | goal | Δ mean % | Δ mean % CI | links | |------|----------------------------------------------|--------------------|----------|----------------|-------| | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.03 | [-0.01, +0.08] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.03 | [-0.04, +0.11] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.02 | [-0.03, +0.06] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.01 | [-0.00, +0.02] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.00 | [-0.04, +0.05] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.02 | [-0.07, +0.03] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.03 | [-0.06, +0.00] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | -1.48 | [-1.68, -1.28] | |

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI". For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true: 1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look. 2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that *if our statistical model is accurate*, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants. 3. Its configuration does not mark it "erratic".

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Regression Detector (Saluki)

Regression Detector Results

Run ID: 358a91a4-343b-4b35-8077-da49a75bdf86

Baseline: 6a77280228403ebd04966956d2443091880f5e24 Comparison: 96df846857864982f014f53c4b1aa4fbe181d7b3

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Fine details of change detection per experiment

| perf | experiment | goal | Δ mean % | Δ mean % CI | links | |------|-------------------------------------------------|--------------------|----------|----------------|-------| | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.80 | [-2.48, +4.09] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.07 | [+0.01, +0.14] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.03 | [+0.00, +0.06] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.02 | [-0.26, +0.30] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | +0.00 | [-0.06, +0.06] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.05, +0.05] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.02 | [-0.24, +0.20] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.03 | [-0.07, +0.00] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.08 | [-0.17, +0.02] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | -3.47 | [-3.63, -3.32] | |

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI". For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true: 1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look. 2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that *if our statistical model is accurate*, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants. 3. Its configuration does not mark it "erratic".

[pr-commenter[bot]]

Regression Detector Links

Experiment Result Links

experiment	link(s)
dsd_uds_100mb_250k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts_distributions_only	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_10mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts_memlimit	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_500mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_512kb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining (ADP only)	[Profiling (ADP)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining_no_allocs (ADP only)	[Profiling (ADP)] [SMP Dashboard]