Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1687 (b1350e5378*) started at 2026-02-05T17:03:53.642


################################################################################
# Set-up
#

Installing PkgEval dependencies (TestEnv)...
  Activating project at `~/.julia/environments/v1.14`

Set-up completed after 11.1s


################################################################################
# Installation
#

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [053f045d] + SimilaritySearch v0.13.8
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [7d9f7c33] + Accessors v0.1.43
  [79e6a3ab] + Adapt v4.4.0
  [4fba245c] + ArrayInterface v7.22.0
  [fb6a15b2] + CloseOpenIntervals v0.1.13
  [f70d9fcc] + CommonWorldInvalidations v1.0.0
  [34da2185] + Compat v4.18.1
  [a33af91c] + CompositionsBase v0.1.2
  [187b0558] + ConstructionBase v1.6.0
  [9a962f9c] + DataAPI v1.16.0
⌅ [864edb3b] + DataStructures v0.18.22
  [b4f34e82] + Distances v0.10.12
  [ffbed154] + DocStringExtensions v0.9.5
  [615f187c] + IfElse v0.1.1
  [3587e190] + InverseFunctions v0.1.17
  [92d709cd] + IrrationalConstants v0.2.6
  [10f19ff3] + LayoutPointers v0.1.17
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [1914dd2f] + MacroTools v0.5.16
  [d125e4d3] + ManualMemory v0.1.8
  [e1d29d7a] + Missings v1.2.0
  [bac558e1] + OrderedCollections v1.8.1
  [aea7be01] + PrecompileTools v1.3.3
  [21216c6a] + Preferences v1.5.1
  [92933f4c] + ProgressMeter v1.11.0
  [ae029012] + Requires v1.3.1
  [94e857df] + SIMDTypes v0.1.0
  [431bcebd] + SciMLPublic v1.0.1
  [0e966ebe] + SearchModels v0.5.0
  [053f045d] + SimilaritySearch v0.13.8
  [a2af1166] + SortingAlgorithms v1.2.2
  [aedffcd0] + Static v1.3.1
  [0d7ed370] + StaticArrayInterface v1.8.0
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
⌅ [2913bbd2] + StatsBase v0.33.21
  [7792a7ef] + StrideArraysCore v0.5.8
  [8290d209] + ThreadingUtilities v0.5.5
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8ba89e20] + Distributed v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.13.0
  [d6f4376e] + Markdown v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v1.0.0
  [9e88b42a] + Serialization v1.11.0
  [6462fe0b] + Sockets v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [f489334b] + StyledStrings v1.13.0
  [fa267f1f] + TOML v1.0.3
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1
  [4536629a] + OpenBLAS_jll v0.3.30+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [8e850b90] + libblastrampoline_jll v5.15.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 4.45s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   2998.1 ms  ✓ SearchModels
   6982.3 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 11 seconds. 81 already precompiled.

Precompilation completed after 29.64s


################################################################################
# Testing
#

     Testing SimilaritySearch
      Status `/tmp/jl_IdscD0/Project.toml`
  [7d9f7c33] Accessors v0.1.43
  [4c88cf16] Aqua v0.8.14
  [b4f34e82] Distances v0.10.12
  [92933f4c] ProgressMeter v1.11.0
  [0e966ebe] SearchModels v0.5.0
  [053f045d] SimilaritySearch v0.13.8
  [10745b16] Statistics v1.11.1
⌅ [2913bbd2] StatsBase v0.33.21
  [7792a7ef] StrideArraysCore v0.5.8
  [ade2ca70] Dates v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [9a3f8284] Random v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_IdscD0/Manifest.toml`
  [7d9f7c33] Accessors v0.1.43
  [79e6a3ab] Adapt v4.4.0
  [4c88cf16] Aqua v0.8.14
  [4fba245c] ArrayInterface v7.22.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.18.1
  [a33af91c] CompositionsBase v0.1.2
  [187b0558] ConstructionBase v1.6.0
  [9a962f9c] DataAPI v1.16.0
⌅ [864edb3b] DataStructures v0.18.22
  [b4f34e82] Distances v0.10.12
  [ffbed154] DocStringExtensions v0.9.5
  [615f187c] IfElse v0.1.1
  [3587e190] InverseFunctions v0.1.17
  [92d709cd] IrrationalConstants v0.2.6
  [10f19ff3] LayoutPointers v0.1.17
  [2ab3a3ac] LogExpFunctions v0.3.29
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [e1d29d7a] Missings v1.2.0
  [bac558e1] OrderedCollections v1.8.1
  [aea7be01] PrecompileTools v1.3.3
  [21216c6a] Preferences v1.5.1
  [92933f4c] ProgressMeter v1.11.0
  [ae029012] Requires v1.3.1
  [94e857df] SIMDTypes v0.1.0
  [431bcebd] SciMLPublic v1.0.1
  [0e966ebe] SearchModels v0.5.0
  [053f045d] SimilaritySearch v0.13.8
  [a2af1166] SortingAlgorithms v1.2.2
  [aedffcd0] Static v1.3.1
  [0d7ed370] StaticArrayInterface v1.8.0
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
⌅ [2913bbd2] StatsBase v0.33.21
  [7792a7ef] StrideArraysCore v0.5.8
  [8290d209] ThreadingUtilities v0.5.5
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0
  [b27032c2] LibCURL v1.0.0
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.14.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v1.0.0
  [9e88b42a] Serialization v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [f489334b] StyledStrings v1.13.0
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.18.0+0
  [e37daf67] LibGit2_jll v1.9.2+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.12.2
  [4536629a] OpenBLAS_jll v0.3.30+0
  [458c3c95] OpenSSL_jll v3.5.5+0
  [efcefdf7] PCRE2_jll v10.47.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [3161d3a3] Zstd_jll v1.5.7+1
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.68.0+1
  [3f19e933] p7zip_jll v17.7.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Test Summary:              | Pass  Total   Time
test database abstractions |   57     57  16.7s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  4.0s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.9s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  5.439759 seconds (399.06 k allocations: 24.589 MiB, 0.57% gc time, 34.42% compilation time)
  3.601918 seconds (7 allocations: 512 bytes)
  5.212759 seconds (254.63 k allocations: 16.009 MiB, 32.28% compilation time)
  3.489646 seconds (7 allocations: 512 bytes)
  5.122809 seconds (238.56 k allocations: 15.116 MiB, 34.33% compilation time)
  3.271884 seconds (7 allocations: 512 bytes)
  5.107419 seconds (234.13 k allocations: 14.865 MiB, 35.52% compilation time)
  3.283559 seconds (7 allocations: 512 bytes)
 14.524975 seconds (246.34 k allocations: 15.516 MiB, 9.93% compilation time)
 14.130325 seconds (7 allocations: 512 bytes)
 27.157237 seconds (7 allocations: 512 bytes)
 26.697770 seconds (7 allocations: 512 bytes)
 19.747618 seconds (509.64 k allocations: 31.382 MiB, 8.18% compilation time)
 18.251683 seconds (7 allocations: 512 bytes)
 17.692390 seconds (405.34 k allocations: 25.364 MiB, 0.41% gc time, 7.14% compilation time)
 16.498649 seconds (7 allocations: 512 bytes)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m14.6s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.929900 seconds (168.62 k allocations: 11.249 MiB, 36.98% compilation time)
  2.660252 seconds (7 allocations: 512 bytes)
 29.973314 seconds (209.48 k allocations: 13.560 MiB, 0.32% gc time, 5.68% compilation time)
 27.510347 seconds (7 allocations: 528 bytes)
 28.273761 seconds (7 allocations: 528 bytes)
 27.792301 seconds (7 allocations: 528 bytes)
  5.183204 seconds (152.56 k allocations: 9.904 MiB, 30.43% compilation time)
  3.565621 seconds (7 allocations: 512 bytes)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m10.9s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 11.301924 seconds (165.36 k allocations: 10.757 MiB, 11.35% compilation time)
 10.001469 seconds (7 allocations: 512 bytes)
 10.867189 seconds (154.30 k allocations: 10.056 MiB, 12.98% compilation time)
  9.527241 seconds (7 allocations: 512 bytes)
 11.215300 seconds (154.21 k allocations: 10.051 MiB, 0.70% gc time, 13.59% compilation time)
  9.751395 seconds (7 allocations: 512 bytes)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m04.7s
  1.061305 seconds (226.83 k allocations: 14.204 MiB, 95.55% compilation time)
  0.037569 seconds (7 allocations: 512 bytes)
  1.691145 seconds (234.93 k allocations: 15.013 MiB, 1.60% gc time, 97.92% compilation time)
  0.037949 seconds (7 allocations: 512 bytes)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  4.6s
  1.763778 seconds (288.30 k allocations: 17.696 MiB, 97.09% compilation time)
  0.052054 seconds (7 allocations: 512 bytes)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  2.4s

allknn   2%|▉                                            |  ETA: 0:03:28
allknn 100%|█████████████████████████████████████████████| Time: 0:00:04
ExhaustiveSearch allknn: 4.938653 seconds (1.80 M allocations: 110.055 MiB, 1.90% gc time, 99.94% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    1      1  5.2s
quantile(length.(hsp_knns), 0:0.1:1) = [2.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 5.0, 5.0, 5.0]
Test Summary: | Total  Time
HSP           |     0  4.9s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:21.845
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:22.578
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:25.431
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=5 ep=9 n=4 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:27.334
LOG n.size quantiles:[1.0, 1.0, 2.0, 2.0, 2.0]
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:27.896
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000005, 0x00000007, 0x00000024, 0x0000002b, 0x0000002e, 0x00000031, 0x00000042, 0x00000053]
D.nn = Int32[1, 2, 2, 4, 5, 2, 7, 5, 7, 7, 2, 1, 2, 2, 7, 5, 5, 2, 4, 4, 4, 7, 7, 2, 1, 4, 2, 2, 5, 5, 7, 2, 2, 4, 2, 36, 5, 7, 4, 2, 2, 2, 43, 4, 7, 46, 2, 46, 49, 46, 46, 2, 7, 4, 1, 36, 7, 49, 4, 2, 2, 5, 2, 1, 4, 66, 66, 2, 43, 4, 4, 5, 2, 43, 2, 2, 5, 2, 43, 5, 66, 46, 83, 2, 43, 49, 4, 4, 2, 7, 83, 7, 66, 1, 36, 7, 7, 7, 2, 5]
D.dist = Float32[0.0, 0.0, 0.07796478, 0.0, 0.0, 0.030352056, 0.0, 0.0051953793, 0.017359674, 0.016636789, 0.044708133, 0.041373134, 0.044730663, 0.006424248, 0.016929984, 0.03120625, 0.085437715, 0.07442725, 0.040919602, 0.071011305, 0.051954508, 0.0043929815, 0.03869939, 0.017303705, 0.04527414, 0.042401254, 0.012942612, 0.065650105, 0.08471626, 0.07432115, 0.020854771, 0.06666243, 0.04547763, 0.0132110715, 0.055965066, 0.0, 0.02452463, 0.031590104, 0.046459556, 0.06279701, 0.043266892, 0.08711928, 0.0, 0.06667948, 0.033160985, 0.0, 0.023639023, 0.08256388, 0.0, 0.040626884, 0.054611504, 0.053538978, 0.009473503, 0.0162431, 0.03524536, 0.003947437, 0.0068072677, 0.042214274, 0.019436836, 0.09301221, 0.057722688, 0.028162837, 0.093266785, 0.0596534, 0.073700964, 0.0, 0.03206545, 0.023501575, 0.0072767735, 0.08913839, 0.06677258, 0.08587438, 0.04467565, 0.06271219, 0.003923297, 0.057454526, 0.053251684, 0.04854095, 0.037486494, 0.033085883, 0.02679652, 0.06605673, 0.0, 0.04452938, 0.069750905, 0.07074952, 0.042170167, 0.026936471, 0.02419722, 0.0381819, 0.010865986, 0.04516381, 0.020506084, 0.080809, 0.04144293, 0.015477717, 0.016477227, 0.03232336, 0.02147609, 0.06427705]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  20.5s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:29.045
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:29.046
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.039
[ Info: neardup> range: 33:48, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.039
LOG add_vertex! sp=6 ep=8 n=5 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:32.039
LOG n.size quantiles:[1.0, 1.5, 2.0, 2.0, 2.0]
[ Info: neardup> range: 49:64, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.040
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.041
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.041
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.305
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.306
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000005, 0x00000007, 0x00000024, 0x0000002b, 0x0000002e, 0x00000031, 0x00000042, 0x00000053]
D.nn = Int32[1, 2, 2, 4, 5, 2, 7, 5, 7, 7, 2, 1, 2, 2, 7, 5, 5, 2, 4, 4, 4, 7, 7, 2, 1, 4, 2, 2, 5, 5, 7, 2, 2, 4, 2, 36, 5, 7, 4, 2, 2, 2, 43, 4, 7, 46, 2, 2, 49, 46, 46, 2, 7, 4, 1, 36, 7, 36, 4, 2, 2, 5, 2, 1, 4, 66, 2, 2, 43, 4, 4, 5, 2, 43, 2, 2, 5, 2, 43, 5, 66, 46, 83, 2, 43, 49, 4, 4, 2, 7, 83, 7, 66, 1, 36, 7, 7, 7, 2, 5]
D.dist = Float32[0.0, 0.0, 0.07796478, 0.0, 0.0, 0.030352056, 0.0, 0.0051953793, 0.017359674, 0.016636789, 0.044708133, 0.041373134, 0.044730663, 0.006424248, 0.016929984, 0.03120625, 0.085437715, 0.07442725, 0.040919602, 0.071011305, 0.051954508, 0.0043929815, 0.03869939, 0.017303705, 0.04527414, 0.042401254, 0.012942612, 0.065650105, 0.08471626, 0.07432115, 0.020854771, 0.06666243, 0.04547763, 0.0132110715, 0.055965066, 0.0, 0.02452463, 0.031590104, 0.046459556, 0.06279701, 0.043266892, 0.08711928, 0.0, 0.06667948, 0.033160985, 0.0, 0.023639023, 0.08739501, 0.0, 0.040626884, 0.054611504, 0.053538978, 0.009473503, 0.0162431, 0.03524536, 0.003947437, 0.0068072677, 0.09985775, 0.019436836, 0.09301221, 0.057722688, 0.028162837, 0.093266785, 0.0596534, 0.073700964, 0.0, 0.07673383, 0.023501575, 0.0072767735, 0.08913839, 0.06677258, 0.08587438, 0.04467565, 0.06271219, 0.003923297, 0.057454526, 0.053251684, 0.04854095, 0.037486494, 0.033085883, 0.02679652, 0.06605673, 0.0, 0.04452938, 0.069750905, 0.07074952, 0.042170167, 0.026936471, 0.02419722, 0.0381819, 0.010865986, 0.04516381, 0.020506084, 0.080809, 0.04144293, 0.015477717, 0.016477227, 0.03232336, 0.02147609, 0.06427705]
Test Summary:       | Pass  Total  Time
neardup small block |    3      3  3.3s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.393
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:32.393
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.394
[ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.394
[ Info: neardup> range: 49:64, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.394
[ Info: neardup> range: 65:80, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.395
[ Info: neardup> range: 81:96, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.395
[ Info: neardup> range: 97:100, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.395
[ Info: neardup> finished current elements: 21, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:32.395
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000024, 0x0000002b, 0x0000002e, 0x00000031, 0x00000053]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 11, 13, 13, 4, 7, 10, 2, 13, 13, 14, 13, 16, 16, 7, 16, 11, 4, 3, 36, 5, 9, 4, 2, 11, 11, 43, 13, 7, 46, 2, 6, 49, 16, 16, 11, 9, 4, 12, 36, 15, 36, 4, 3, 11, 16, 6, 10, 4, 6, 6, 2, 43, 4, 13, 16, 6, 11, 2, 11, 16, 11, 43, 8, 6, 46, 83, 12, 43, 11, 4, 4, 2, 12, 8, 12, 3, 1, 36, 7, 9, 14, 13, 16]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05676061, 0.03565842, 0.03586036, 0.065268874, 0.051954508, 0.0043929815, 0.0063545704, 0.017303705, 0.00755018, 0.038738906, 0.009380817, 0.057697773, 0.055069745, 0.026303947, 0.020854771, 0.02045089, 0.002891183, 0.0132110715, 0.02543974, 0.0, 0.02452463, 0.012971163, 0.046459556, 0.06279701, 0.003817439, 0.007656932, 0.0, 0.041617215, 0.033160985, 0.0, 0.023639023, 0.02875024, 0.0, 0.025657952, 0.027807355, 0.03286946, 0.0029526353, 0.0162431, 0.014313936, 0.003947437, 0.006719768, 0.09985775, 0.019436836, 0.050202847, 0.026956856, 0.004365146, 0.034468174, 0.021080375, 0.073700964, 0.032004952, 0.035407722, 0.023501575, 0.0072767735, 0.08913839, 0.051269352, 0.03406042, 0.010069191, 0.04041505, 0.003923297, 0.046167433, 0.010442793, 0.020588696, 0.037486494, 0.025218844, 0.068615735, 0.06605673, 0.0, 0.01148957, 0.069750905, 0.0607996, 0.042170167, 0.026936471, 0.02419722, 0.006649792, 0.09996998, 0.009258091, 0.015189469, 0.080809, 0.04144293, 0.015477717, 0.0004733801, 0.02013278, 0.015443385, 0.011090338]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  0.1s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:37.282
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=5 n=5 2026-02-05T17:12:37.642
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:39.057
[ Info: neardup> range: 33:48, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:39.057
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=5 ep=8 n=8 2026-02-05T17:12:39.058
[ Info: neardup> range: 49:64, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:39.063
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:39.064
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:39.064
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:40.212
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-05T17:12:40.212
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000005, 0x00000007, 0x00000024, 0x0000002b, 0x0000002e, 0x00000031, 0x00000042, 0x00000053]
D.nn = Int32[1, 2, 2, 4, 5, 2, 7, 5, 7, 7, 2, 1, 2, 2, 7, 5, 5, 2, 4, 4, 4, 7, 7, 2, 1, 4, 2, 2, 5, 5, 7, 2, 2, 4, 2, 36, 5, 7, 4, 2, 2, 2, 43, 4, 7, 46, 2, 2, 49, 46, 46, 2, 7, 4, 1, 36, 7, 36, 4, 2, 2, 5, 2, 1, 4, 66, 2, 2, 43, 4, 4, 5, 2, 43, 2, 2, 5, 2, 43, 5, 66, 46, 83, 2, 43, 49, 4, 4, 2, 7, 83, 7, 66, 1, 36, 7, 7, 7, 2, 5]
D.dist = Float32[0.0, 0.0, 0.07796478, 0.0, 0.0, 0.030352056, 0.0, 0.0051953793, 0.017359674, 0.016636789, 0.044708133, 0.041373134, 0.044730663, 0.006424248, 0.016929984, 0.03120625, 0.085437715, 0.07442725, 0.040919602, 0.071011305, 0.051954508, 0.0043929815, 0.03869939, 0.017303705, 0.04527414, 0.042401254, 0.012942612, 0.065650105, 0.08471626, 0.07432115, 0.020854771, 0.06666243, 0.04547763, 0.0132110715, 0.055965066, 0.0, 0.02452463, 0.031590104, 0.046459556, 0.06279701, 0.043266892, 0.08711928, 0.0, 0.06667948, 0.033160985, 0.0, 0.023639023, 0.08739501, 0.0, 0.040626884, 0.054611504, 0.053538978, 0.009473503, 0.0162431, 0.03524536, 0.003947437, 0.0068072677, 0.09985775, 0.019436836, 0.09301221, 0.057722688, 0.028162837, 0.093266785, 0.0596534, 0.073700964, 0.0, 0.07673383, 0.023501575, 0.0072767735, 0.08913839, 0.06677258, 0.08587438, 0.04467565, 0.06271219, 0.003923297, 0.057454526, 0.053251684, 0.04854095, 0.037486494, 0.033085883, 0.02679652, 0.06605673, 0.0, 0.04452938, 0.069750905, 0.07074952, 0.042170167, 0.026936471, 0.02419722, 0.0381819, 0.010865986, 0.04516381, 0.020506084, 0.080809, 0.04144293, 0.015477717, 0.016477227, 0.03232336, 0.02147609, 0.06427705]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  7.8s
computing farthest point 1, dmax: Inf, imax: 8, n: 30
computing farthest point 2, dmax: 1.2732537, imax: 11, n: 30
computing farthest point 3, dmax: 1.0060478, imax: 4, n: 30
computing farthest point 4, dmax: 0.9343072, imax: 15, n: 30
computing farthest point 5, dmax: 0.7198013, imax: 16, n: 30
computing farthest point 6, dmax: 0.69746107, imax: 3, n: 30
computing farthest point 7, dmax: 0.65371567, imax: 20, n: 30
computing farthest point 8, dmax: 0.6116928, imax: 25, n: 30
computing farthest point 9, dmax: 0.5488987, imax: 18, n: 30
computing farthest point 10, dmax: 0.5007207, imax: 28, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  2.0s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.6s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:48.783
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:12:50.414
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=2, Δ=0.97125, maxvisits=114) 2026-02-05T17:13:04.213
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 6.0]
(i, j, d) = (44, 65, -1.1920929f-7)
(i, j, d, :parallel) = (44, 65, -1.1920929f-7, :parallel)
[ Info: NOTE: the exact method will be faster on small datasets due to the preprocessing step of the approximation method
[ Info: ("closestpair computation time", :approx => 22.895246604, :exact => 0.95604777)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  24.4s
  6.989834 seconds (196.06 k allocations: 12.282 MiB, 24.65% compilation time)
SEARCH Exhaustive 1: 0.003901 seconds
SEARCH Exhaustive 2: 0.003801 seconds
SEARCH Exhaustive 3: 0.004415 seconds
typeof(seq) = ExhaustiveSearch{SqL2Distance, MatrixDatabase{Matrix{Float32}}}
typeof(ectx) = GenericContext{KnnSorted}
typeof(q) = SubArray{Float32, 1, Matrix{Float32}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}
typeof(res) = KnnSorted{Vector{IdWeight}}
[ Info: ===================== minrecall ==============================
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:13:31.416
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:13:33.119
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=12, Δ=1.21275, maxvisits=198) 2026-02-05T17:13:43.170
LOG n.size quantiles:[2.0, 4.0, 4.0, 5.0, 6.0]
LOG add_vertex! sp=15165 ep=15169 n=15164 BeamSearch(bsize=12, Δ=1.440603, maxvisits=456) 2026-02-05T17:13:44.170
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=26375 ep=26379 n=26374 BeamSearch(bsize=6, Δ=0.975, maxvisits=438) 2026-02-05T17:13:45.171
LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=38025 ep=38029 n=38024 BeamSearch(bsize=10, Δ=1.21275, maxvisits=608) 2026-02-05T17:13:46.171
LOG n.size quantiles:[3.0, 4.0, 5.0, 5.0, 6.0]
LOG add_vertex! sp=48410 ep=48414 n=48409 BeamSearch(bsize=10, Δ=1.21275, maxvisits=608) 2026-02-05T17:13:47.171
LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch(bsize=4, Δ=0.975, maxvisits=456) 2026-02-05T17:13:48.197
LOG n.size quantiles:[4.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=67440 ep=67444 n=67439 BeamSearch(bsize=4, Δ=0.975, maxvisits=456) 2026-02-05T17:13:49.198
LOG n.size quantiles:[6.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=77525 ep=77529 n=77524 BeamSearch(bsize=4, Δ=0.975, maxvisits=456) 2026-02-05T17:13:50.198
LOG n.size quantiles:[6.0, 6.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=85620 ep=85624 n=85619 BeamSearch(bsize=4, Δ=1.1, maxvisits=462) 2026-02-05T17:13:51.198
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=93670 ep=93674 n=93669 BeamSearch(bsize=4, Δ=1.1, maxvisits=462) 2026-02-05T17:13:52.198
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 91.0]
[ Info: minrecall: queries per second: 3425.7253516097703, recall: 0.900625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=15, Δ=1.155, maxvisits=750))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 91.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.155, maxvisits=568)), 1000, 8)
[ Info: rebuild: queries per second: 16236.499289953532, recall: 0.90025
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.155, maxvisits=568))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.157625, maxvisits=772)), 1000, 8)
  0.647362 seconds (92.47 k allocations: 5.432 MiB, 85.90% compilation time)
[ Info: matrixhints: queries per second: 13444.98641632855, recall: 0.900875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.157625, maxvisits=772))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 91.0]
  2.899391 seconds (158.07 k allocations: 10.348 MiB, 53.47% compilation time)
SEARCH Exhaustive 1: 0.001512 seconds
SEARCH Exhaustive 2: 0.001446 seconds
SEARCH Exhaustive 3: 0.001530 seconds
typeof(seq) = ExhaustiveSearch{SqL2Distance, StrideMatrixDatabase{StrideArraysCore.StrideArray{Float32, 2, (1, 2), Tuple{Int64, Int64}, Tuple{Nothing, Nothing}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}, Matrix{Float32}}}}
typeof(ectx) = GenericContext{KnnSorted}
typeof(q) = StrideArraysCore.StrideArray{Float32, 1, (1,), Tuple{Int64}, Tuple{Nothing}, Tuple{Static.StaticInt{1}}, Matrix{Float32}}
typeof(res) = KnnSorted{Vector{IdWeight}}
[ Info: ===================== minrecall ==============================
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:15:04.521
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-05T17:15:06.094
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=12, Δ=1.21275, maxvisits=198) 2026-02-05T17:15:15.317
LOG n.size quantiles:[2.0, 4.0, 4.0, 5.0, 6.0]
LOG add_vertex! sp=17970 ep=17974 n=17969 BeamSearch(bsize=12, Δ=1.440603, maxvisits=456) 2026-02-05T17:15:16.317
LOG n.size quantiles:[4.0, 6.0, 6.0, 9.0, 11.0]
LOG add_vertex! sp=31335 ep=31339 n=31334 BeamSearch(bsize=6, Δ=0.975, maxvisits=438) 2026-02-05T17:15:17.317
LOG n.size quantiles:[5.0, 7.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=43600 ep=43604 n=43599 BeamSearch(bsize=10, Δ=1.21275, maxvisits=608) 2026-02-05T17:15:18.317
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=54730 ep=54734 n=54729 BeamSearch(bsize=10, Δ=1.21275, maxvisits=608) 2026-02-05T17:15:19.317
LOG n.size quantiles:[5.0, 6.0, 6.0, 8.0, 10.0]
LOG add_vertex! sp=65020 ep=65024 n=65019 BeamSearch(bsize=4, Δ=0.975, maxvisits=456) 2026-02-05T17:15:20.317
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=76470 ep=76474 n=76469 BeamSearch(bsize=4, Δ=0.975, maxvisits=456) 2026-02-05T17:15:21.318
LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=86420 ep=86424 n=86419 BeamSearch(bsize=4, Δ=1.1, maxvisits=462) 2026-02-05T17:15:22.318
LOG n.size quantiles:[4.0, 5.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=96145 ep=96149 n=96144 BeamSearch(bsize=4, Δ=1.1, maxvisits=462) 2026-02-05T17:15:23.318
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 91.0]
[ Info: minrecall: queries per second: 3002.874402426868, recall: 0.900625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=15, Δ=1.155, maxvisits=750))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 91.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.155, maxvisits=568)), 1000, 8)
[ Info: rebuild: queries per second: 16374.856355666334, recall: 0.90025
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.155, maxvisits=568))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.157625, maxvisits=772)), 1000, 8)
  0.654745 seconds (93.55 k allocations: 5.584 MiB, 88.78% compilation time)
[ Info: matrixhints: queries per second: 13864.64655438854, recall: 0.900875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.157625, maxvisits=772))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 91.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  2m55.5s
     Testing SimilaritySearch tests passed 

Testing completed after 682.14s

PkgEval succeeded after 737.8s