Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1699 (993b392fda*) started at 2026-02-14T00:01:16.566


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

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

Set-up completed after 10.38s


################################################################################
# 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 v1.9.0
  [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...
   2914.8 ms  ✓ SearchModels
   7070.9 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 10 seconds. 81 already precompiled.

Precompilation completed after 28.53s


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

     Testing SimilaritySearch
      Status `/tmp/jl_wCpt5J/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_wCpt5J/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 v1.9.0
  [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  15.6s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  3.7s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.7s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.1s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  5.159721 seconds (400.96 k allocations: 24.718 MiB, 31.03% compilation time)
  3.787077 seconds (7 allocations: 512 bytes)
  5.730856 seconds (255.86 k allocations: 16.082 MiB, 31.35% compilation time)
  3.618998 seconds (7 allocations: 512 bytes)
  5.338363 seconds (239.62 k allocations: 15.180 MiB, 33.64% compilation time)
  3.395233 seconds (7 allocations: 512 bytes)
  5.454556 seconds (235.05 k allocations: 14.924 MiB, 32.22% compilation time)
  3.759002 seconds (7 allocations: 512 bytes)
 15.880589 seconds (247.53 k allocations: 15.587 MiB, 0.47% gc time, 10.38% compilation time)
 14.242331 seconds (7 allocations: 512 bytes)
 27.387784 seconds (7 allocations: 512 bytes)
 26.740173 seconds (7 allocations: 512 bytes)
 19.912865 seconds (511.57 k allocations: 31.513 MiB, 8.08% compilation time)
 18.593674 seconds (7 allocations: 512 bytes)
 17.554935 seconds (406.76 k allocations: 25.483 MiB, 0.42% gc time, 6.96% compilation time)
 16.356557 seconds (7 allocations: 512 bytes)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m18.0s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.884272 seconds (169.00 k allocations: 11.272 MiB, 38.99% compilation time)
  2.352950 seconds (7 allocations: 512 bytes)
 30.575629 seconds (210.19 k allocations: 13.606 MiB, 5.41% compilation time)
 26.124770 seconds (7 allocations: 528 bytes)
 28.152441 seconds (7 allocations: 528 bytes)
 29.027195 seconds (7 allocations: 528 bytes)
  5.367443 seconds (152.91 k allocations: 9.926 MiB, 2.24% gc time, 34.01% compilation time)
  3.687839 seconds (7 allocations: 512 bytes)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m11.3s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 11.051844 seconds (165.75 k allocations: 10.782 MiB, 12.81% compilation time)
  9.434124 seconds (7 allocations: 512 bytes)
 11.038701 seconds (154.64 k allocations: 10.077 MiB, 13.58% compilation time)
  9.882973 seconds (7 allocations: 512 bytes)
 11.216723 seconds (154.55 k allocations: 10.073 MiB, 13.10% compilation time)
  9.583322 seconds (7 allocations: 512 bytes)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m04.3s
  1.174276 seconds (227.56 k allocations: 14.251 MiB, 96.64% compilation time)
  0.039545 seconds (7 allocations: 512 bytes)
  1.827936 seconds (235.76 k allocations: 15.066 MiB, 98.14% compilation time)
  0.033933 seconds (7 allocations: 512 bytes)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  5.1s
  1.921863 seconds (289.51 k allocations: 17.771 MiB, 97.01% compilation time)
  0.057130 seconds (7 allocations: 512 bytes)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  2.7s

allknn   2%|▉                                            |  ETA: 0:03:29
allknn 100%|█████████████████████████████████████████████| Time: 0:00:04
ExhaustiveSearch allknn: 4.983057 seconds (1.81 M allocations: 110.516 MiB, 0.55% gc time, 99.95% 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  5.0s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:45.789
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-14T00:09:46.483
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) 2026-02-14T00:09:49.393
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) 2026-02-14T00:09:51.241
LOG n.size quantiles:[1.0, 2.0, 2.0, 2.0, 3.0]
[ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:51.701
D.map = UInt32[0x00000001, 0x00000003, 0x00000004, 0x00000006, 0x0000000a, 0x0000000d, 0x0000001a, 0x0000002d, 0x00000054, 0x00000059]
D.nn = Int32[1, 1, 3, 4, 3, 6, 4, 6, 4, 10, 3, 10, 13, 1, 3, 1, 3, 10, 13, 10, 3, 1, 10, 1, 4, 26, 26, 26, 26, 26, 26, 26, 26, 1, 26, 1, 3, 1, 6, 4, 26, 1, 1, 1, 45, 1, 13, 1, 1, 13, 26, 13, 3, 26, 13, 26, 26, 13, 3, 3, 26, 4, 1, 1, 13, 3, 26, 26, 13, 13, 3, 10, 3, 26, 1, 26, 13, 1, 13, 13, 13, 26, 3, 84, 4, 10, 26, 26, 89, 26, 1, 84, 10, 26, 1, 26, 13, 6, 6, 26]
D.dist = Float32[0.0, 0.08543068, 0.0, 0.0, 0.017637372, 0.0, 0.028018475, 0.016189873, 0.03098607, 0.0, 0.028284729, 0.09078616, 0.0, 0.067180336, 0.050507605, 0.023212135, 0.06799406, 0.025330782, 0.08701265, 0.033930242, 0.05445522, 0.077842, 0.0821743, 0.08856404, 0.07240516, 0.0, 0.03349495, 0.049900234, 0.021355093, 0.060144067, 0.07046449, 0.031041801, 0.07089156, 0.013772488, 0.038214445, 0.066346645, 0.033075213, 0.029237151, 0.027279258, 0.07731485, 0.046358168, 0.014277577, 0.034101248, 0.035433173, 0.0, 0.070953965, 0.039008915, 0.0825631, 0.054992378, 0.07584083, 0.08570671, 0.046271086, 0.05757618, 0.05423367, 0.038866103, 0.08623052, 0.023280144, 0.056615293, 0.027129233, 0.03341329, 0.08812368, 0.07381666, 0.034369886, 0.033287704, 0.032154202, 0.009107232, 0.03458184, 0.03839612, 0.0084504485, 0.03905672, 0.047246754, 0.05989015, 0.074757576, 0.05098957, 0.039604187, 0.0022203326, 0.04360318, 0.019275367, 0.010981739, 0.019463003, 0.09239912, 0.053874373, 0.023416877, 0.0, 0.032007217, 0.06122893, 0.028681517, 0.036834896, 0.0, 0.012120962, 0.052262962, 0.046200514, 0.057252884, 0.018731654, 0.06328893, 0.074653566, 0.02938366, 0.008987069, 0.024004936, 0.04944718]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  21.0s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:52.846
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-14T00:09:52.846
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:55.831
LOG add_vertex! sp=7 ep=7 n=6 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-14T00:09:55.832
LOG n.size quantiles:[4.0, 4.0, 4.0, 4.0, 4.0]
[ Info: neardup> range: 33:48, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:55.832
[ Info: neardup> range: 49:64, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:55.832
[ Info: neardup> range: 65:80, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:55.832
[ Info: neardup> range: 81:96, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:55.832
[ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.107
[ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.107
D.map = UInt32[0x00000001, 0x00000003, 0x00000004, 0x00000006, 0x0000000a, 0x0000000d, 0x0000001a, 0x0000002d, 0x00000054, 0x00000059]
D.nn = Int32[1, 1, 3, 4, 3, 6, 4, 6, 4, 10, 3, 10, 13, 1, 3, 1, 3, 10, 13, 10, 3, 1, 10, 1, 4, 26, 3, 6, 3, 26, 26, 1, 26, 1, 26, 1, 3, 1, 6, 4, 26, 1, 1, 1, 45, 1, 13, 1, 1, 13, 26, 13, 3, 26, 13, 26, 26, 13, 3, 3, 26, 4, 1, 1, 13, 3, 26, 26, 13, 13, 3, 10, 3, 26, 1, 26, 13, 1, 13, 13, 13, 26, 3, 84, 4, 10, 26, 26, 89, 26, 1, 45, 10, 26, 1, 26, 13, 6, 6, 26]
D.dist = Float32[0.0, 0.08543068, 0.0, 0.0, 0.017637372, 0.0, 0.028018475, 0.016189873, 0.03098607, 0.0, 0.028284729, 0.09078616, 0.0, 0.067180336, 0.050507605, 0.023212135, 0.06799406, 0.025330782, 0.08701265, 0.033930242, 0.05445522, 0.077842, 0.0821743, 0.08856404, 0.07240516, 0.0, 0.04391533, 0.087848544, 0.0949406, 0.060144067, 0.07046449, 0.051340044, 0.07089156, 0.013772488, 0.038214445, 0.066346645, 0.033075213, 0.029237151, 0.027279258, 0.07731485, 0.046358168, 0.014277577, 0.034101248, 0.035433173, 0.0, 0.070953965, 0.039008915, 0.0825631, 0.054992378, 0.07584083, 0.08570671, 0.046271086, 0.05757618, 0.05423367, 0.038866103, 0.08623052, 0.023280144, 0.056615293, 0.027129233, 0.03341329, 0.08812368, 0.07381666, 0.034369886, 0.033287704, 0.032154202, 0.009107232, 0.03458184, 0.03839612, 0.0084504485, 0.03905672, 0.047246754, 0.05989015, 0.074757576, 0.05098957, 0.039604187, 0.0022203326, 0.04360318, 0.019275367, 0.010981739, 0.019463003, 0.09239912, 0.053874373, 0.023416877, 0.0, 0.032007217, 0.06122893, 0.028681517, 0.036834896, 0.0, 0.012120962, 0.052262962, 0.06023401, 0.057252884, 0.018731654, 0.06328893, 0.074653566, 0.02938366, 0.008987069, 0.024004936, 0.04944718]
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: 2026-02-14T00:09:56.192
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-14T00:09:56.193
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: 2026-02-14T00:09:56.193
[ Info: neardup> range: 33:48, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.193
[ Info: neardup> range: 49:64, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.193
[ Info: neardup> range: 65:80, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.194
[ Info: neardup> range: 81:96, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.194
[ Info: neardup> range: 97:100, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.194
[ Info: neardup> finished current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:09:56.194
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000001e, 0x0000001f, 0x0000002d]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 7, 10, 14, 10, 7, 2, 11, 9, 9, 2, 15, 8, 7, 30, 31, 2, 31, 1, 15, 1, 5, 16, 8, 15, 2, 1, 14, 1, 45, 15, 13, 15, 16, 13, 12, 13, 7, 31, 8, 2, 30, 13, 15, 5, 12, 4, 1, 2, 13, 3, 2, 8, 13, 13, 11, 11, 15, 9, 14, 2, 13, 1, 13, 13, 9, 15, 11, 31, 9, 12, 2, 31, 2, 31, 15, 45, 16, 30, 1, 30, 13, 8, 6, 30]
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, 0.041997313, 0.025330782, 0.027284741, 0.033930242, 0.041098237, 0.014463127, 0.051810443, 0.069788575, 0.015923083, 0.029111922, 0.035971284, 0.03652799, 0.09179336, 0.0, 0.0, 0.030719519, 0.02547443, 0.013772488, 0.023074687, 0.066346645, 0.024442554, 0.011346698, 0.016833901, 0.03991425, 0.029160023, 0.014277577, 0.03311199, 0.035433173, 0.0, 0.041141868, 0.039008915, 0.04550165, 0.034861326, 0.07584083, 0.010532975, 0.046271086, 0.03305441, 0.02177322, 0.009386897, 0.024823189, 0.03666979, 0.056615293, 0.0085372925, 0.012536228, 0.013713658, 0.07381666, 0.034369886, 0.026431918, 0.032154202, 0.009107232, 0.04501772, 0.03961402, 0.0084504485, 0.03905672, 0.021137655, 0.030407667, 0.017750204, 0.026213706, 0.0039740205, 0.02607286, 0.04360318, 0.019275367, 0.010981739, 0.019463003, 0.03906107, 0.02571547, 0.0053670406, 0.040699005, 0.022521079, 0.03364575, 0.0029873848, 0.027409792, 0.043705046, 0.027747393, 0.02291298, 0.06023401, 0.022083879, 0.044741035, 0.06328893, 0.014260948, 0.02938366, 0.0025926232, 0.024004936, 0.022061884]
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: 2026-02-14T00:10:00.987
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=6 n=6 2026-02-14T00:10:01.344
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:02.494
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=6 ep=7 n=7 2026-02-14T00:10:02.494
[ Info: neardup> range: 33:48, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:02.500
[ Info: neardup> range: 49:64, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:02.500
[ Info: neardup> range: 65:80, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:02.500
[ Info: neardup> range: 81:96, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:02.501
[ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:03.605
[ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-14T00:10:03.606
D.map = UInt32[0x00000001, 0x00000003, 0x00000004, 0x00000006, 0x0000000a, 0x0000000d, 0x0000001a, 0x0000002d, 0x00000054, 0x00000059]
D.nn = Int32[1, 1, 3, 4, 3, 6, 4, 6, 4, 10, 3, 10, 13, 1, 3, 1, 3, 10, 13, 10, 3, 1, 10, 1, 4, 26, 3, 6, 3, 26, 26, 1, 26, 1, 26, 1, 3, 1, 6, 4, 26, 1, 1, 1, 45, 1, 13, 1, 1, 13, 26, 13, 3, 26, 13, 26, 26, 13, 3, 3, 26, 4, 1, 1, 13, 3, 26, 26, 13, 13, 3, 10, 3, 26, 1, 26, 13, 1, 13, 13, 13, 26, 3, 84, 4, 10, 26, 26, 89, 26, 1, 45, 10, 26, 1, 26, 13, 6, 6, 26]
D.dist = Float32[0.0, 0.08543068, 0.0, 0.0, 0.017637372, 0.0, 0.028018475, 0.016189873, 0.03098607, 0.0, 0.028284729, 0.09078616, 0.0, 0.067180336, 0.050507605, 0.023212135, 0.06799406, 0.025330782, 0.08701265, 0.033930242, 0.05445522, 0.077842, 0.0821743, 0.08856404, 0.07240516, 0.0, 0.04391533, 0.087848544, 0.0949406, 0.060144067, 0.07046449, 0.051340044, 0.07089156, 0.013772488, 0.038214445, 0.066346645, 0.033075213, 0.029237151, 0.027279258, 0.07731485, 0.046358168, 0.014277577, 0.034101248, 0.035433173, 0.0, 0.070953965, 0.039008915, 0.0825631, 0.054992378, 0.07584083, 0.08570671, 0.046271086, 0.05757618, 0.05423367, 0.038866103, 0.08623052, 0.023280144, 0.056615293, 0.027129233, 0.03341329, 0.08812368, 0.07381666, 0.034369886, 0.033287704, 0.032154202, 0.009107232, 0.03458184, 0.03839612, 0.0084504485, 0.03905672, 0.047246754, 0.05989015, 0.074757576, 0.05098957, 0.039604187, 0.0022203326, 0.04360318, 0.019275367, 0.010981739, 0.019463003, 0.09239912, 0.053874373, 0.023416877, 0.0, 0.032007217, 0.06122893, 0.028681517, 0.036834896, 0.0, 0.012120962, 0.052262962, 0.06023401, 0.057252884, 0.018731654, 0.06328893, 0.074653566, 0.02938366, 0.008987069, 0.024004936, 0.04944718]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  7.4s
computing farthest point 1, dmax: Inf, imax: 27, n: 30
computing farthest point 2, dmax: 0.9196436, imax: 30, n: 30
computing farthest point 3, dmax: 0.76473135, imax: 14, n: 30
computing farthest point 4, dmax: 0.71480274, imax: 5, n: 30
computing farthest point 5, dmax: 0.69635284, imax: 9, n: 30
computing farthest point 6, dmax: 0.61588126, imax: 29, n: 30
computing farthest point 7, dmax: 0.54551697, imax: 18, n: 30
computing farthest point 8, dmax: 0.53598326, imax: 12, n: 30
computing farthest point 9, dmax: 0.50894886, imax: 11, n: 30
computing farthest point 10, dmax: 0.5036111, imax: 24, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.9s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.7s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-14T00:10:12.481
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) 2026-02-14T00:10:14.056
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=0.84224164, maxvisits=108) 2026-02-14T00:10:27.708
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 5.0]
(i, j, d) = (461, 621, -2.3841858f-7)
(i, j, d, :parallel) = (461, 621, -2.3841858f-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 => 22.712298542, :exact => 1.018454734)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  24.3s
  7.285586 seconds (196.76 k allocations: 12.321 MiB, 0.37% gc time, 24.65% compilation time)
SEARCH Exhaustive 1: 0.004409 seconds
SEARCH Exhaustive 2: 0.004311 seconds
SEARCH Exhaustive 3: 0.004832 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) 2026-02-14T00:10:55.829
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) 2026-02-14T00:10:57.520
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=8, Δ=1.21275, maxvisits=214) 2026-02-14T00:11:07.778
LOG n.size quantiles:[3.0, 4.0, 5.0, 5.0, 5.0]
LOG add_vertex! sp=16115 ep=16119 n=16114 BeamSearch(bsize=8, Δ=1.025, maxvisits=362) 2026-02-14T00:11:08.778
LOG n.size quantiles:[4.0, 6.0, 7.0, 8.0, 10.0]
LOG add_vertex! sp=30350 ep=30354 n=30349 BeamSearch(bsize=14, Δ=1.05, maxvisits=450) 2026-02-14T00:11:09.778
LOG n.size quantiles:[5.0, 5.0, 5.0, 6.0, 6.0]
LOG add_vertex! sp=41605 ep=41609 n=41604 BeamSearch(bsize=7, Δ=1.157625, maxvisits=450) 2026-02-14T00:11:10.778
LOG n.size quantiles:[6.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=52405 ep=52409 n=52404 BeamSearch(bsize=7, Δ=1.157625, maxvisits=450) 2026-02-14T00:11:11.779
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=60050 ep=60054 n=60049 BeamSearch(bsize=4, Δ=1.21275, maxvisits=490) 2026-02-14T00:11:12.779
LOG n.size quantiles:[3.0, 5.0, 5.0, 7.0, 7.0]
LOG add_vertex! sp=69180 ep=69184 n=69179 BeamSearch(bsize=4, Δ=1.21275, maxvisits=490) 2026-02-14T00:11:13.779
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 6.0]
LOG add_vertex! sp=77870 ep=77874 n=77869 BeamSearch(bsize=4, Δ=1.21275, maxvisits=490) 2026-02-14T00:11:14.779
LOG n.size quantiles:[4.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch(bsize=10, Δ=1.1287501, maxvisits=528) 2026-02-14T00:11:15.839
LOG n.size quantiles:[7.0, 7.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=93305 ep=93309 n=93304 BeamSearch(bsize=10, Δ=1.1287501, maxvisits=528) 2026-02-14T00:11:16.839
LOG n.size quantiles:[4.0, 6.0, 9.0, 10.0, 10.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 90.0]
[ Info: minrecall: queries per second: 2780.883089503048, recall: 0.90275
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.13, maxvisits=696))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 90.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.14, maxvisits=634)), 1000, 8)
[ Info: rebuild: queries per second: 15550.201102975765, recall: 0.8985
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.14, maxvisits=634))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=20, Δ=1.1287501, maxvisits=756)), 1000, 8)
  0.627674 seconds (93.03 k allocations: 5.469 MiB, 87.36% compilation time)
[ Info: matrixhints: queries per second: 12642.28560589437, recall: 0.9025
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=20, Δ=1.1287501, maxvisits=756))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 90.0]
  3.147244 seconds (158.41 k allocations: 10.369 MiB, 51.54% compilation time)
SEARCH Exhaustive 1: 0.001487 seconds
SEARCH Exhaustive 2: 0.001450 seconds
SEARCH Exhaustive 3: 0.001640 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) 2026-02-14T00:12:34.502
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) 2026-02-14T00:12:36.128
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=8, Δ=1.21275, maxvisits=214) 2026-02-14T00:12:45.979
LOG n.size quantiles:[3.0, 4.0, 5.0, 5.0, 5.0]
LOG add_vertex! sp=19500 ep=19504 n=19499 BeamSearch(bsize=8, Δ=1.025, maxvisits=362) 2026-02-14T00:12:46.979
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=34905 ep=34909 n=34904 BeamSearch(bsize=14, Δ=1.05, maxvisits=450) 2026-02-14T00:12:47.979
LOG n.size quantiles:[4.0, 5.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=45445 ep=45449 n=45444 BeamSearch(bsize=7, Δ=1.157625, maxvisits=450) 2026-02-14T00:12:48.980
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=56550 ep=56554 n=56549 BeamSearch(bsize=7, Δ=1.157625, maxvisits=450) 2026-02-14T00:12:49.980
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=66000 ep=66004 n=65999 BeamSearch(bsize=4, Δ=1.21275, maxvisits=490) 2026-02-14T00:12:50.980
LOG n.size quantiles:[6.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=75470 ep=75474 n=75469 BeamSearch(bsize=4, Δ=1.21275, maxvisits=490) 2026-02-14T00:12:51.980
LOG n.size quantiles:[4.0, 7.0, 8.0, 9.0, 10.0]
LOG add_vertex! sp=84515 ep=84519 n=84514 BeamSearch(bsize=4, Δ=1.21275, maxvisits=490) 2026-02-14T00:12:52.981
LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 11.0]
LOG add_vertex! sp=92630 ep=92634 n=92629 BeamSearch(bsize=10, Δ=1.1287501, maxvisits=528) 2026-02-14T00:12:53.981
LOG n.size quantiles:[7.0, 8.0, 8.0, 8.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 90.0]
[ Info: minrecall: queries per second: 2944.6009809048896, recall: 0.90275
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.13, maxvisits=696))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 90.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.14, maxvisits=634)), 1000, 8)
[ Info: rebuild: queries per second: 18049.837442261505, recall: 0.8985
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.14, maxvisits=634))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=20, Δ=1.1287501, maxvisits=756)), 1000, 8)
  0.638073 seconds (94.12 k allocations: 5.623 MiB, 89.32% compilation time)
[ Info: matrixhints: queries per second: 15264.595273299756, recall: 0.9025
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=20, Δ=1.1287501, maxvisits=756))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 90.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  3m06.1s
     Testing SimilaritySearch tests passed 

Testing completed after 694.65s

PkgEval succeeded after 748.34s