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DataDog / saluki

An experimental toolkit for building telemetry data planes in Rust.
Apache License 2.0
12 stars 2 forks source link

build(deps): bump indexmap from 2.4.0 to 2.5.0 #230

Closed dependabot[bot] closed 1 week ago

dependabot[bot] commented 1 week ago

Bumps indexmap from 2.4.0 to 2.5.0.

Changelog

Sourced from indexmap's changelog.

2.5.0

  • Added an insert_before method to IndexMap and IndexSet, as an alternative to shift_insert with different behavior on existing entries.
  • Added first_entry and last_entry methods to IndexMap.
  • Added From implementations between IndexedEntry and OccupiedEntry.
Commits
  • 48ed490 Release 2.5.0
  • 139d7ad Merge pull request #340 from cuviper/insert-bounds
  • 1d9b5e3 Add doc examples for insert_before and shift_insert
  • 8ca01b0 Use insert_before for "new" entries in insert_sorted
  • 7224def Add insert_before as an alternate to shift_insert
  • 0247a15 Document and assert index bounds in shift_insert
  • 922c6ad Update the CI badge
  • e482e17 Merge pull request #342 from cuviper/btree-like
  • b63e4a1 Merge pull request #341 from cuviper/from-entry
  • 264e5b7 Add doc aliases like BTreeMap/BTreeSet
  • Additional commits viewable in compare view


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pr-commenter[bot] commented 1 week ago

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: 3b2d38f4-f000-4a93-9f59-9879f3a1a9cd

Baseline: 7.55.2 Comparison: 7.55.3

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

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_3k_contexts | ingress throughput | +0.03 | [-0.03, +0.09] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.02 | [+0.01, +0.03] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.01 | [-0.03, +0.05] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.00 | [-0.03, +0.03] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.00] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | -0.01 | [-0.03, +0.02] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.04 | [-0.12, +0.03] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.05 | [-0.11, +0.01] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | -1.91 | [-2.12, -1.70] | |

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] commented 1 week ago

Regression Detector (Saluki)

Regression Detector Results

Run ID: 2e17f0df-f01e-48ae-a7c7-3a898bccf3a3

Baseline: 95b2925da12ba98980e5b9b66df61aa89726bbe0 Comparison: f07abb5d6b1aed942e49ead4e51633a361dcf7b3

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

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_100mb_3k_contexts_distributions_only | memory utilization | +1.68 | [+1.55, +1.81] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +1.65 | [+1.56, +1.74] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.02 | [-0.03, +0.08] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.02 | [-0.25, +0.28] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.01 | [-0.05, +0.06] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | -0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | -0.00 | [-0.05, +0.05] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.01 | [-0.07, +0.04] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.18 | [-3.40, +3.05] | |

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] commented 1 week ago

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]
dependabot[bot] commented 1 week ago

Looks like indexmap is up-to-date now, so this is no longer needed.