Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1826 (44c835795b*) started at 2026-03-02T14:23:27.999


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

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

Set-up completed after 14.93s


################################################################################
# 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 v1.5.2
  [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 5.07s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   3202.3 ms  ✓ SearchModels
   6713.1 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 10 seconds. 81 already precompiled.

Precompilation completed after 34.42s


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

     Testing SimilaritySearch
      Status `/tmp/jl_X88BS7/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_X88BS7/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 v1.5.2
  [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 v1.3.2+0
  [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  17.1s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.2s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  3.8s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  3.4s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  6.714333 seconds (402.87 k allocations: 24.732 MiB, 37.27% compilation time)
  3.700722 seconds (7 allocations: 512 bytes)
  6.022042 seconds (256.12 k allocations: 15.978 MiB, 35.84% compilation time)
  3.919284 seconds (7 allocations: 512 bytes)
  5.943579 seconds (239.83 k allocations: 15.087 MiB, 40.30% compilation time)
  3.549086 seconds (7 allocations: 512 bytes)
  5.788656 seconds (235.02 k allocations: 14.822 MiB, 39.35% compilation time)
  3.613349 seconds (7 allocations: 512 bytes)
 16.404116 seconds (248.45 k allocations: 15.524 MiB, 0.51% gc time, 13.48% compilation time)
 14.331673 seconds (7 allocations: 512 bytes)
 27.681836 seconds (7 allocations: 512 bytes)
 27.277527 seconds (7 allocations: 512 bytes)
 20.361982 seconds (516.98 k allocations: 31.611 MiB, 8.00% compilation time)
 18.780524 seconds (7 allocations: 512 bytes)
 18.109406 seconds (407.75 k allocations: 25.396 MiB, 0.42% gc time, 7.89% compilation time)
 16.754830 seconds (7 allocations: 512 bytes)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m24.5s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  4.480421 seconds (168.43 k allocations: 11.140 MiB, 45.43% compilation time)
  2.473885 seconds (7 allocations: 512 bytes)
 30.383428 seconds (211.41 k allocations: 13.581 MiB, 6.81% compilation time)
 27.768758 seconds (7 allocations: 528 bytes)
 27.770540 seconds (7 allocations: 528 bytes)
 27.449098 seconds (7 allocations: 528 bytes)
  5.457112 seconds (151.95 k allocations: 9.797 MiB, 40.35% compilation time)
  3.250373 seconds (7 allocations: 512 bytes)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m11.2s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 12.318865 seconds (164.35 k allocations: 10.617 MiB, 16.93% compilation time)
 10.140460 seconds (7 allocations: 512 bytes)
 11.883870 seconds (153.13 k allocations: 9.907 MiB, 16.62% compilation time)
  9.759258 seconds (7 allocations: 512 bytes)
 11.885669 seconds (153.04 k allocations: 9.903 MiB, 17.21% compilation time)
  9.859375 seconds (7 allocations: 512 bytes)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m08.0s
  1.316772 seconds (227.45 k allocations: 14.177 MiB, 96.99% compilation time)
  0.039707 seconds (7 allocations: 512 bytes)
  2.360347 seconds (235.45 k allocations: 14.944 MiB, 98.50% compilation time)
  0.034574 seconds (7 allocations: 512 bytes)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  5.7s
  2.497721 seconds (292.20 k allocations: 17.822 MiB, 97.62% compilation time)
  0.057174 seconds (7 allocations: 512 bytes)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  3.2s

allknn   2%|▉                                            |  ETA: 0:03:54
allknn 100%|█████████████████████████████████████████████| Time: 0:00:05
ExhaustiveSearch allknn: 5.536835 seconds (1.80 M allocations: 110.334 MiB, 0.50% gc time, 99.95% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    1      1  5.7s
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  4.7s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:26.285
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-03-02T14:32:27.430
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) 2026-03-02T14:32:30.859
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) 2026-03-02T14:32:33.162
LOG n.size quantiles:[2.0, 3.0, 3.0, 3.0, 3.0]
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:33.677
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x00000009, 0x0000000a, 0x0000000d, 0x0000000f, 0x0000002b, 0x00000040, 0x00000046]
D.nn = Int32[1, 2, 3, 3, 1, 6, 1, 3, 9, 10, 6, 1, 13, 1, 15, 2, 9, 10, 15, 2, 2, 15, 1, 15, 1, 9, 3, 1, 15, 2, 9, 15, 15, 2, 1, 2, 13, 13, 6, 13, 15, 1, 43, 10, 15, 43, 1, 1, 15, 9, 15, 1, 13, 9, 15, 1, 9, 13, 10, 10, 2, 2, 15, 64, 64, 6, 15, 10, 9, 70, 64, 9, 15, 2, 15, 9, 6, 9, 2, 6, 15, 2, 2, 64, 9, 9, 2, 15, 13, 43, 3, 6, 70, 64, 70, 6, 9, 15, 15, 64]
D.dist = Float32[0.0, 0.0, 0.0, 0.054688513, 0.07305533, 0.0, 0.06263322, 0.09420419, 0.0, 0.0, 0.02979815, 0.06363231, 0.0, 0.09030968, 0.0, 0.07080513, 0.0130467415, 0.077497244, 0.099583924, 0.04975313, 0.0055838823, 0.050211728, 0.035735488, 0.03666985, 0.022336185, 0.06421459, 0.053032458, 0.044343114, 0.026441395, 0.016333997, 0.048695207, 0.021682024, 0.044570267, 0.01839739, 0.05835849, 0.06684744, 0.023586571, 0.03673613, 0.036084592, 0.026628256, 0.02769643, 0.019648314, 0.0, 0.043120265, 0.048517227, 0.0070433617, 0.015662134, 0.031099916, 0.078719735, 0.00891006, 0.07302678, 0.021922588, 0.07589257, 0.034671485, 0.052515686, 0.015450716, 0.04405296, 0.0071939826, 0.040413916, 0.0076061487, 0.0638687, 0.044899583, 0.093696654, 0.0, 0.04479742, 0.049037457, 0.059971213, 0.037174344, 0.06119603, 0.0, 0.03563279, 0.032883108, 0.06733227, 0.07527977, 0.051773787, 0.08762473, 0.0006482601, 0.059103012, 0.015119195, 0.08009881, 0.026645422, 0.017816007, 0.07430929, 0.07196909, 0.05814147, 0.05919224, 0.066064894, 0.040074766, 0.01769048, 0.034313858, 0.033648014, 0.039692998, 0.038665295, 0.03443885, 0.01869756, 0.028397202, 0.06303686, 0.027616441, 0.034256816, 0.06368512]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  24.3s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:34.959
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-03-02T14:32:34.959
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:38.790
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:38.790
LOG add_vertex! sp=9 ep=9 n=8 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-03-02T14:32:38.790
LOG n.size quantiles:[2.0, 2.0, 2.0, 2.0, 2.0]
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:38.790
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:38.791
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:38.791
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.050
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.050
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x00000009, 0x0000000a, 0x0000000d, 0x0000000f, 0x0000002b, 0x00000040, 0x00000046]
D.nn = Int32[1, 2, 3, 3, 1, 6, 1, 3, 9, 10, 6, 1, 13, 1, 15, 2, 9, 10, 15, 2, 2, 15, 1, 15, 1, 9, 3, 1, 15, 2, 9, 15, 15, 2, 1, 2, 13, 13, 6, 13, 15, 1, 43, 10, 15, 43, 1, 1, 15, 9, 15, 1, 13, 9, 15, 1, 9, 13, 10, 10, 2, 2, 15, 64, 64, 6, 15, 10, 9, 70, 64, 9, 15, 2, 15, 9, 6, 9, 2, 6, 15, 2, 2, 64, 9, 9, 2, 15, 13, 43, 3, 6, 70, 64, 70, 6, 9, 15, 15, 64]
D.dist = Float32[0.0, 0.0, 0.0, 0.054688513, 0.07305533, 0.0, 0.06263322, 0.09420419, 0.0, 0.0, 0.02979815, 0.06363231, 0.0, 0.09030968, 0.0, 0.07080513, 0.0130467415, 0.077497244, 0.099583924, 0.04975313, 0.0055838823, 0.050211728, 0.035735488, 0.03666985, 0.022336185, 0.06421459, 0.053032458, 0.044343114, 0.026441395, 0.016333997, 0.048695207, 0.021682024, 0.044570267, 0.01839739, 0.05835849, 0.06684744, 0.023586571, 0.03673613, 0.036084592, 0.026628256, 0.02769643, 0.019648314, 0.0, 0.043120265, 0.048517227, 0.0070433617, 0.015662134, 0.031099916, 0.078719735, 0.00891006, 0.07302678, 0.021922588, 0.07589257, 0.034671485, 0.052515686, 0.015450716, 0.04405296, 0.0071939826, 0.040413916, 0.0076061487, 0.0638687, 0.044899583, 0.093696654, 0.0, 0.04479742, 0.049037457, 0.059971213, 0.037174344, 0.06119603, 0.0, 0.03563279, 0.032883108, 0.06733227, 0.07527977, 0.051773787, 0.08762473, 0.0006482601, 0.059103012, 0.015119195, 0.08009881, 0.026645422, 0.017816007, 0.07430929, 0.07196909, 0.05814147, 0.05919224, 0.066064894, 0.040074766, 0.01769048, 0.034313858, 0.033648014, 0.039692998, 0.038665295, 0.03443885, 0.01869756, 0.028397202, 0.06303686, 0.027616441, 0.034256816, 0.06368512]
Test Summary:       | Pass  Total  Time
neardup small block |    3      3  4.2s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.184
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-03-02T14:32:39.185
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: 2026-03-02T14:32:39.185
[ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.185
[ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.185
[ Info: neardup> range: 65:80, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.185
[ Info: neardup> range: 81:96, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.185
[ Info: neardup> range: 97:100, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.185
[ Info: neardup> finished current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:39.185
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 9, 4, 12, 2, 2, 15, 7, 15, 1, 5, 3, 12, 15, 2, 8, 15, 12, 2, 1, 2, 13, 8, 6, 5, 15, 12, 7, 10, 5, 7, 1, 1, 11, 9, 11, 1, 5, 9, 5, 1, 5, 13, 10, 10, 16, 2, 14, 4, 5, 6, 15, 10, 5, 14, 8, 9, 12, 16, 12, 16, 6, 9, 2, 12, 15, 2, 16, 8, 9, 9, 16, 11, 13, 7, 3, 6, 14, 5, 14, 6, 5, 15, 5, 11]
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, 0.0130467415, 0.040337503, 0.029195845, 0.04975313, 0.0055838823, 0.050211728, 0.02152139, 0.03666985, 0.022336185, 0.03941405, 0.053032458, 0.0064581037, 0.026441395, 0.016333997, 0.024963915, 0.021682024, 0.030918717, 0.01839739, 0.05835849, 0.06684744, 0.023586571, 0.024490833, 0.036084592, 0.012404263, 0.02769643, 0.017358422, 0.060146213, 0.043120265, 0.020097017, 0.07337141, 0.015662134, 0.031099916, 0.018514395, 0.00891006, 0.04984045, 0.021922588, 0.057336032, 0.034671485, 0.014976442, 0.015450716, 0.031105638, 0.0071939826, 0.040413916, 0.0076061487, 0.012786984, 0.044899583, 0.028370142, 0.04611391, 0.03275287, 0.049037457, 0.059971213, 0.037174344, 0.051709592, 0.056375086, 0.040233493, 0.032883108, 0.0012750626, 0.041847587, 0.043479204, 0.06266451, 0.0006482601, 0.059103012, 0.015119195, 0.072120965, 0.026645422, 0.017816007, 0.010243058, 0.028767586, 0.05814147, 0.05919224, 0.00950104, 0.0123586655, 0.01769048, 0.020242035, 0.033648014, 0.039692998, 0.0040451884, 0.032238126, 0.024059534, 0.028397202, 0.04342085, 0.027616441, 0.027805746, 0.049529135]
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: 2026-03-02T14:32:42.604
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=8 n=8 2026-03-02T14:32:43.058
[ Info: neardup> range: 17:32, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:44.311
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:44.311
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=8 ep=9 n=9 2026-03-02T14:32:44.311
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:44.316
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:44.316
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:44.317
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:45.497
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-03-02T14:32:45.497
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x00000009, 0x0000000a, 0x0000000d, 0x0000000f, 0x0000002b, 0x00000040, 0x00000046]
D.nn = Int32[1, 2, 3, 3, 1, 6, 1, 3, 9, 10, 6, 1, 13, 1, 15, 2, 9, 10, 15, 2, 2, 15, 1, 15, 1, 9, 3, 1, 15, 2, 9, 15, 15, 2, 1, 2, 13, 13, 6, 13, 15, 1, 43, 10, 15, 43, 1, 1, 15, 9, 15, 1, 13, 9, 15, 1, 9, 13, 10, 10, 2, 2, 15, 64, 64, 6, 15, 10, 9, 70, 64, 9, 15, 2, 15, 9, 6, 9, 2, 6, 15, 2, 2, 64, 9, 9, 2, 15, 13, 43, 3, 6, 70, 64, 70, 6, 9, 15, 15, 64]
D.dist = Float32[0.0, 0.0, 0.0, 0.054688513, 0.07305533, 0.0, 0.06263322, 0.09420419, 0.0, 0.0, 0.02979815, 0.06363231, 0.0, 0.09030968, 0.0, 0.07080513, 0.0130467415, 0.077497244, 0.099583924, 0.04975313, 0.0055838823, 0.050211728, 0.035735488, 0.03666985, 0.022336185, 0.06421459, 0.053032458, 0.044343114, 0.026441395, 0.016333997, 0.048695207, 0.021682024, 0.044570267, 0.01839739, 0.05835849, 0.06684744, 0.023586571, 0.03673613, 0.036084592, 0.026628256, 0.02769643, 0.019648314, 0.0, 0.043120265, 0.048517227, 0.0070433617, 0.015662134, 0.031099916, 0.078719735, 0.00891006, 0.07302678, 0.021922588, 0.07589257, 0.034671485, 0.052515686, 0.015450716, 0.04405296, 0.0071939826, 0.040413916, 0.0076061487, 0.0638687, 0.044899583, 0.093696654, 0.0, 0.04479742, 0.049037457, 0.059971213, 0.037174344, 0.06119603, 0.0, 0.03563279, 0.032883108, 0.06733227, 0.07527977, 0.051773787, 0.08762473, 0.0006482601, 0.059103012, 0.015119195, 0.08009881, 0.026645422, 0.017816007, 0.07430929, 0.07196909, 0.05814147, 0.05919224, 0.066064894, 0.040074766, 0.01769048, 0.034313858, 0.033648014, 0.039692998, 0.038665295, 0.03443885, 0.01869756, 0.028397202, 0.06303686, 0.027616441, 0.034256816, 0.06368512]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  6.3s
computing farthest point 1, dmax: Inf, imax: 19, n: 30
computing farthest point 2, dmax: 1.4957263, imax: 3, n: 30
computing farthest point 3, dmax: 1.1508261, imax: 9, n: 30
computing farthest point 4, dmax: 0.9529722, imax: 6, n: 30
computing farthest point 5, dmax: 0.87028974, imax: 23, n: 30
computing farthest point 6, dmax: 0.818184, imax: 16, n: 30
computing farthest point 7, dmax: 0.7936932, imax: 18, n: 30
computing farthest point 8, dmax: 0.7295347, imax: 13, n: 30
computing farthest point 9, dmax: 0.6388452, imax: 2, n: 30
computing farthest point 10, dmax: 0.6078609, imax: 25, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  2.1s
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) 2026-03-02T14:32:55.639
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) 2026-03-02T14:32:57.684
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=0.945, maxvisits=106) 2026-03-02T14:33:12.688
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 6.0]
(i, j, d) = (4, 595, -1.1920929f-7)
(i, j, d, :parallel) = (4, 595, -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 => 25.912879606, :exact => 1.080931034)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  27.5s
  8.047566 seconds (196.44 k allocations: 12.247 MiB, 26.64% compilation time)
SEARCH Exhaustive 1: 0.009742 seconds
SEARCH Exhaustive 2: 0.009576 seconds
SEARCH Exhaustive 3: 0.010726 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) 2026-03-02T14:33:44.407
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) 2026-03-02T14:33:46.270
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=16, Δ=1.075, maxvisits=238) 2026-03-02T14:33:58.349
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 7.0]
LOG add_vertex! sp=14370 ep=14374 n=14369 BeamSearch(bsize=16, Δ=0.95, maxvisits=396) 2026-03-02T14:33:59.349
LOG n.size quantiles:[3.0, 7.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=26930 ep=26934 n=26929 BeamSearch(bsize=6, Δ=1.075, maxvisits=456) 2026-03-02T14:34:00.350
LOG n.size quantiles:[3.0, 4.0, 5.0, 5.0, 6.0]
LOG add_vertex! sp=37880 ep=37884 n=37879 BeamSearch(bsize=8, Δ=1.0, maxvisits=470) 2026-03-02T14:34:01.439
LOG n.size quantiles:[4.0, 5.0, 5.0, 9.0, 9.0]
LOG add_vertex! sp=48260 ep=48264 n=48259 BeamSearch(bsize=8, Δ=1.0, maxvisits=470) 2026-03-02T14:34:02.439
LOG n.size quantiles:[5.0, 6.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:34:03.476
LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 10.0]
LOG add_vertex! sp=65665 ep=65669 n=65664 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:34:04.476
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=74180 ep=74184 n=74179 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:34:05.477
LOG n.size quantiles:[3.0, 4.0, 8.0, 8.0, 8.0]
LOG add_vertex! sp=82645 ep=82649 n=82644 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:34:06.477
LOG n.size quantiles:[4.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=89215 ep=89219 n=89214 BeamSearch(bsize=14, Δ=1.025, maxvisits=484) 2026-03-02T14:34:07.478
LOG n.size quantiles:[4.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=97415 ep=97419 n=97414 BeamSearch(bsize=14, Δ=1.025, maxvisits=484) 2026-03-02T14:34:08.478
LOG n.size quantiles:[6.0, 6.0, 8.0, 8.0, 10.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 22.0, 85.0]
[ Info: minrecall: queries per second: 2805.6103127299625, recall: 0.903625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=16, Δ=1.155, maxvisits=654))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 22.0, 85.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.157625, maxvisits=566)), 1000, 8)
[ Info: rebuild: queries per second: 13326.367729763439, recall: 0.901
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.157625, maxvisits=566))
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, 17.0, 19.0, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.21, maxvisits=858)), 1000, 8)
  0.629643 seconds (93.80 k allocations: 5.482 MiB, 85.41% compilation time)
[ Info: matrixhints: queries per second: 11196.579955387675, recall: 0.910375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.21, maxvisits=858))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 22.0, 85.0]
  3.387672 seconds (156.30 k allocations: 10.184 MiB, 57.72% compilation time)
SEARCH Exhaustive 1: 0.004422 seconds
SEARCH Exhaustive 2: 0.004429 seconds
SEARCH Exhaustive 3: 0.004715 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) 2026-03-02T14:35:31.019
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) 2026-03-02T14:35:33.088
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=16, Δ=1.075, maxvisits=238) 2026-03-02T14:35:45.530
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 7.0]
LOG add_vertex! sp=16905 ep=16909 n=16904 BeamSearch(bsize=16, Δ=0.95, maxvisits=396) 2026-03-02T14:35:46.530
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=29930 ep=29934 n=29929 BeamSearch(bsize=6, Δ=1.075, maxvisits=456) 2026-03-02T14:35:47.531
LOG n.size quantiles:[4.0, 7.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=39525 ep=39529 n=39524 BeamSearch(bsize=8, Δ=1.0, maxvisits=470) 2026-03-02T14:35:48.531
LOG n.size quantiles:[7.0, 7.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=50775 ep=50779 n=50774 BeamSearch(bsize=8, Δ=1.0, maxvisits=470) 2026-03-02T14:35:49.531
LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=60545 ep=60549 n=60544 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:35:50.531
LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 7.0]
LOG add_vertex! sp=70355 ep=70359 n=70354 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:35:51.532
LOG n.size quantiles:[6.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=76190 ep=76194 n=76189 BeamSearch(bsize=12, Δ=1.05, maxvisits=380) 2026-03-02T14:35:52.532
LOG n.size quantiles:[4.0, 5.0, 7.0, 7.0, 10.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch(bsize=14, Δ=1.025, maxvisits=484) 2026-03-02T14:35:53.603
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 12.0]
LOG add_vertex! sp=94420 ep=94424 n=94419 BeamSearch(bsize=14, Δ=1.025, maxvisits=484) 2026-03-02T14:35:54.603
LOG n.size quantiles:[5.0, 6.0, 7.0, 9.0, 10.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 22.0, 85.0]
[ Info: minrecall: queries per second: 3088.2614435172636, recall: 0.903625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=16, Δ=1.155, maxvisits=654))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 22.0, 85.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.157625, maxvisits=566)), 1000, 8)
[ Info: rebuild: queries per second: 14958.317600922797, recall: 0.901
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.157625, maxvisits=566))
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, 17.0, 19.0, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.21, maxvisits=858)), 1000, 8)
  0.670592 seconds (94.82 k allocations: 5.630 MiB, 87.72% compilation time)
[ Info: matrixhints: queries per second: 12722.632066264354, recall: 0.910375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.21, maxvisits=858))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 22.0, 85.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  3m24.1s
     Testing SimilaritySearch tests passed 

Testing completed after 734.74s

PkgEval succeeded after 803.1s