Package evaluation to test SimilaritySearch on Julia 1.12.4 (0f21d93eaa*) started at 2026-01-26T23:02:32.019


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

Installing PkgEval dependencies (TestEnv)...
  Activating project at `~/.julia/environments/v1.12`

Set-up completed after 8.1s


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

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.12/Project.toml`
  [053f045d] + SimilaritySearch v0.13.7
    Updating `~/.julia/environments/v1.12/Manifest.toml`
  [7d9f7c33] + Accessors v0.1.43
  [79e6a3ab] + Adapt v4.4.0
  [4fba245c] + ArrayInterface v7.22.0
  [62783981] + BitTwiddlingConvenienceFunctions v0.1.6
  [2a0fbf3d] + CPUSummary v0.2.7
  [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
  [adafc99b] + CpuId v0.3.1
  [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
  [d96e819e] + Parameters v0.12.3
  [f517fe37] + Polyester v0.7.18
  [1d0040c9] + PolyesterWeave v0.2.2
  [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 v0.4.1
  [053f045d] + SimilaritySearch v0.13.7
  [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
  [3a884ed6] + UnPack v1.0.2
  [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 v1.12.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.12.0
  [d6f4376e] + Markdown v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [6462fe0b] + Sockets v1.11.0
  [2f01184e] + SparseArrays v1.12.0
  [f489334b] + StyledStrings v1.11.0
  [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 v0.3.29+0
  [bea87d4a] + SuiteSparse_jll v7.8.3+2
  [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 4.86s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   8169.8 ms  ✓ SearchModels
  34145.7 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 44 seconds. 87 already precompiled.

Precompilation completed after 59.71s


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

     Testing SimilaritySearch
      Status `/tmp/jl_8gnk4E/Project.toml`
  [7d9f7c33] Accessors v0.1.43
  [4c88cf16] Aqua v0.8.14
  [b4f34e82] Distances v0.10.12
  [f517fe37] Polyester v0.7.18
  [92933f4c] ProgressMeter v1.11.0
⌅ [0e966ebe] SearchModels v0.4.1
  [053f045d] SimilaritySearch v0.13.7
  [10745b16] Statistics v1.11.1
⌅ [2913bbd2] StatsBase v0.33.21
  [7792a7ef] StrideArraysCore v0.5.8
  [ade2ca70] Dates v1.11.0
  [37e2e46d] LinearAlgebra v1.12.0
  [9a3f8284] Random v1.11.0
  [2f01184e] SparseArrays v1.12.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_8gnk4E/Manifest.toml`
  [7d9f7c33] Accessors v0.1.43
  [79e6a3ab] Adapt v4.4.0
  [4c88cf16] Aqua v0.8.14
  [4fba245c] ArrayInterface v7.22.0
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [2a0fbf3d] CPUSummary v0.2.7
  [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
  [adafc99b] CpuId v0.3.1
  [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
  [d96e819e] Parameters v0.12.3
  [f517fe37] Polyester v0.7.18
  [1d0040c9] PolyesterWeave v0.2.2
  [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 v0.4.1
  [053f045d] SimilaritySearch v0.13.7
  [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
  [3a884ed6] UnPack v1.0.2
  [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 v1.12.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.12.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.12.1
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.12.0
  [f489334b] StyledStrings v1.11.0
  [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 v8.15.0+0
  [e37daf67] LibGit2_jll v1.9.0+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.11.4
  [4536629a] OpenBLAS_jll v0.3.29+0
  [458c3c95] OpenSSL_jll v3.5.4+0
  [bea87d4a] SuiteSparse_jll v7.8.3+2
  [83775a58] Zlib_jll v1.3.1+2
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.64.0+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 |   56     56  12.2s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.0s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  4.0s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.8s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  6.297166 seconds (1000 allocations: 78.125 KiB)
  6.412527 seconds (1000 allocations: 78.125 KiB)
  4.380126 seconds (1000 allocations: 78.125 KiB)
  4.416398 seconds (1000 allocations: 78.125 KiB)
  4.275283 seconds (1000 allocations: 78.125 KiB)
  4.241981 seconds (1000 allocations: 78.125 KiB)
  4.193185 seconds (1000 allocations: 78.125 KiB)
  4.266754 seconds (1000 allocations: 78.125 KiB)
 15.232004 seconds (1000 allocations: 78.125 KiB)
 15.319736 seconds (1000 allocations: 78.125 KiB)
 27.649698 seconds (1000 allocations: 78.125 KiB)
 27.398082 seconds (1000 allocations: 78.125 KiB)
 19.629342 seconds (1000 allocations: 78.125 KiB)
 19.695278 seconds (1000 allocations: 78.125 KiB)
 15.876420 seconds (1000 allocations: 78.125 KiB)
 15.691148 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m27.5s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.258448 seconds (1000 allocations: 78.125 KiB)
  3.250414 seconds (1000 allocations: 78.125 KiB)
 40.374554 seconds (1000 allocations: 78.125 KiB)
 40.176736 seconds (1000 allocations: 78.125 KiB)
 42.152490 seconds (1000 allocations: 78.125 KiB)
 42.230664 seconds (1000 allocations: 78.125 KiB)
  5.132501 seconds (1000 allocations: 78.125 KiB)
  5.180648 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  3m05.4s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 10.617739 seconds (1000 allocations: 78.125 KiB)
 10.478046 seconds (1000 allocations: 78.125 KiB)
 10.628986 seconds (1000 allocations: 78.125 KiB)
 10.522687 seconds (1000 allocations: 78.125 KiB)
 10.380504 seconds (1000 allocations: 78.125 KiB)
 10.244762 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m05.9s
  0.044491 seconds (1000 allocations: 78.125 KiB)
  0.044542 seconds (1000 allocations: 78.125 KiB)
  0.042011 seconds (1000 allocations: 78.125 KiB)
  0.040982 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  3.3s
  0.061177 seconds (1000 allocations: 78.125 KiB)
  0.061897 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.4s
ExhaustiveSearch allknn: 4.400970 seconds (2.82 M allocations: 149.046 MiB, 0.72% gc time, 99.97% compilation time)
ParallelExhaustiveSearch allknn: 1.248561 seconds (685.17 k allocations: 35.039 MiB, 2.03% gc time, 99.89% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  6.3s
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, 6.0]
Test Summary: | Total  Time
HSP           |     0  3.1s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:43.086
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:12:43.117
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:12:44.206
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:44.556
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000007, 0x00000008, 0x00000009, 0x0000000e, 0x0000001a, 0x00000023, 0x00000027, 0x0000002d, 0x0000003c]
D.nn = Int32[1, 2, 3, 1, 2, 3, 7, 8, 9, 8, 7, 3, 7, 14, 7, 9, 14, 14, 2, 1, 7, 3, 7, 14, 7, 26, 7, 7, 2, 1, 7, 26, 7, 26, 35, 14, 14, 2, 39, 2, 9, 39, 3, 7, 45, 2, 1, 9, 14, 14, 26, 45, 2, 14, 14, 2, 3, 35, 7, 60, 1, 26, 9, 60, 26, 14, 7, 60, 7, 60, 9, 45, 3, 9, 26, 2, 7, 2, 7, 7, 9, 9, 7, 9, 3, 60, 2, 14, 60, 9, 60, 45, 7, 7, 7, 9, 60, 3, 60, 7]
D.dist = Float32[0.0, 0.0, 0.0, 0.046584427, 0.017930388, 0.039820433, 0.0, 0.0, 0.0, 0.042595983, 0.040593803, 0.049079478, 0.008853316, 0.0, 0.04933691, 0.025703669, 0.0954504, 0.06557578, 0.07545, 0.0013739467, 0.060035884, 0.030670583, 0.03664857, 0.07886708, 0.008301735, 0.0, 0.054170728, 0.031862617, 0.07494664, 0.025352895, 0.021870434, 0.047069788, 0.016626298, 0.012451649, 0.0, 0.061640203, 0.04744929, 0.01971519, 0.0, 0.07460189, 0.005433202, 0.04476005, 0.063548684, 0.038577676, 0.0, 0.012135446, 0.02699095, 0.0249089, 0.038006425, 0.069200754, 0.042927146, 0.04136455, 0.043478668, 0.040031195, 0.05086726, 0.058951795, 0.042244792, 0.076737165, 0.04267311, 0.0, 0.004708469, 0.009794176, 0.05649823, 0.017947197, 0.022408307, 0.06509495, 0.0142047405, 0.014201999, 0.024970233, 0.037689924, 0.0032659173, 0.005299449, 0.035517514, 0.045986414, 0.04701501, 0.07668048, 0.044625163, 0.027070463, 0.04232323, 0.0779832, 0.003076315, 0.009058714, 0.07914293, 0.01158303, 0.019110382, 0.04448563, 0.049674153, 0.028257787, 0.0130675435, 0.051024556, 0.014799774, 0.011919379, 0.0074197054, 0.024604678, 0.010493338, 0.037412703, 0.06089288, 0.051594317, 0.06582898, 0.086134136]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  17.4s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.395
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:12:45.395
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.395
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.395
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.396
[ Info: neardup> range: 65:80, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.396
[ Info: neardup> range: 81:96, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.396
[ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.396
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.396
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000007, 0x00000008, 0x00000009, 0x0000000e, 0x0000001a, 0x00000023, 0x00000027, 0x0000002d, 0x0000003c]
D.nn = Int32[1, 2, 3, 1, 2, 3, 7, 8, 9, 8, 7, 3, 7, 14, 7, 9, 14, 14, 2, 1, 7, 3, 7, 14, 7, 26, 7, 7, 2, 1, 7, 2, 7, 26, 35, 14, 14, 2, 39, 2, 9, 2, 3, 7, 45, 2, 1, 9, 14, 14, 26, 45, 2, 14, 14, 2, 3, 35, 7, 60, 1, 26, 9, 35, 26, 14, 7, 60, 7, 60, 9, 45, 3, 9, 26, 2, 7, 2, 7, 7, 9, 9, 7, 9, 3, 60, 2, 14, 60, 9, 60, 45, 7, 7, 7, 9, 60, 3, 60, 7]
D.dist = Float32[0.0, 0.0, 0.0, 0.046584427, 0.017930388, 0.039820433, 0.0, 0.0, 0.0, 0.042595983, 0.040593803, 0.049079478, 0.008853316, 0.0, 0.04933691, 0.025703669, 0.0954504, 0.06557578, 0.07545, 0.0013739467, 0.060035884, 0.030670583, 0.03664857, 0.07886708, 0.008301735, 0.0, 0.054170728, 0.031862617, 0.07494664, 0.025352895, 0.021870434, 0.08160746, 0.016626298, 0.012451649, 0.0, 0.061640203, 0.04744929, 0.01971519, 0.0, 0.07460189, 0.005433202, 0.08430928, 0.063548684, 0.038577676, 0.0, 0.012135446, 0.02699095, 0.0249089, 0.038006425, 0.069200754, 0.042927146, 0.04136455, 0.043478668, 0.040031195, 0.05086726, 0.058951795, 0.042244792, 0.076737165, 0.04267311, 0.0, 0.004708469, 0.009794176, 0.05649823, 0.07786298, 0.022408307, 0.06509495, 0.0142047405, 0.014201999, 0.024970233, 0.037689924, 0.0032659173, 0.005299449, 0.035517514, 0.045986414, 0.04701501, 0.07668048, 0.044625163, 0.027070463, 0.04232323, 0.0779832, 0.003076315, 0.009058714, 0.07914293, 0.01158303, 0.019110382, 0.04448563, 0.049674153, 0.028257787, 0.0130675435, 0.051024556, 0.014799774, 0.011919379, 0.0074197054, 0.024604678, 0.010493338, 0.037412703, 0.06089288, 0.051594317, 0.06582898, 0.086134136]
Test Summary:       | Pass  Total  Time
neardup small block |    3      3  0.0s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.455
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:12:45.455
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: 2026-01-26T23:12:45.456
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.456
[ Info: neardup> range: 49:64, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.456
[ Info: neardup> range: 65:80, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.456
[ Info: neardup> range: 81:96, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.456
[ Info: neardup> range: 97:100, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.456
[ Info: neardup> finished current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:45.456
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000001a, 0x00000023, 0x0000002d, 0x0000003c]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 14, 4, 2, 1, 13, 5, 13, 4, 7, 26, 15, 15, 5, 4, 13, 5, 7, 26, 35, 6, 6, 2, 6, 2, 9, 5, 12, 11, 45, 5, 4, 9, 14, 11, 26, 45, 2, 14, 4, 2, 6, 35, 15, 60, 1, 26, 9, 35, 26, 11, 16, 60, 15, 60, 9, 45, 3, 11, 26, 5, 7, 5, 15, 15, 9, 9, 11, 9, 3, 60, 2, 14, 60, 11, 60, 45, 7, 13, 7, 9, 60, 12, 60, 6]
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, 0.0954504, 0.034820437, 0.07545, 0.0013739467, 0.04125184, 0.018928409, 0.03242123, 0.026503682, 0.008301735, 0.0, 0.034381807, 0.009034276, 0.06333035, 0.016156912, 0.014294565, 0.026878357, 0.016626298, 0.012451649, 0.0, 0.059494615, 0.039321423, 0.01971519, 0.07207495, 0.07460189, 0.005433202, 0.058208644, 0.0013734102, 0.009851873, 0.0, 0.004513502, 0.02609849, 0.0249089, 0.038006425, 0.044076264, 0.042927146, 0.04136455, 0.043478668, 0.040031195, 0.04971105, 0.058951795, 0.01419127, 0.076737165, 0.016156852, 0.0, 0.004708469, 0.009794176, 0.05649823, 0.07786298, 0.022408307, 0.03327477, 0.0075696707, 0.014201999, 0.009543121, 0.037689924, 0.0032659173, 0.005299449, 0.035517514, 0.02857709, 0.04701501, 0.049293995, 0.044625163, 0.022955894, 0.001003027, 0.015955806, 0.003076315, 0.009058714, 0.026214898, 0.01158303, 0.019110382, 0.04448563, 0.049674153, 0.028257787, 0.0130675435, 0.050943553, 0.014799774, 0.011919379, 0.0074197054, 0.017997682, 0.010493338, 0.037412703, 0.06089288, 0.0005993247, 0.06582898, 0.027632952]
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: 2026-01-26T23:12:50.160
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=7 n=7 2026-01-26T23:12:50.160
[ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.163
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.163
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.164
[ Info: neardup> range: 65:80, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.164
[ Info: neardup> range: 81:96, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.164
[ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.164
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-26T23:12:50.164
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000007, 0x00000008, 0x00000009, 0x0000000e, 0x0000001a, 0x00000023, 0x00000027, 0x0000002d, 0x0000003c]
D.nn = Int32[1, 2, 3, 1, 2, 3, 7, 8, 9, 8, 7, 3, 7, 14, 7, 9, 14, 14, 2, 1, 7, 3, 7, 14, 7, 26, 7, 7, 2, 1, 7, 2, 7, 26, 35, 14, 14, 2, 39, 2, 9, 2, 3, 7, 45, 2, 1, 9, 14, 14, 26, 45, 2, 14, 14, 2, 3, 35, 7, 60, 1, 26, 9, 35, 26, 14, 7, 60, 7, 60, 9, 45, 3, 9, 26, 2, 7, 2, 7, 7, 9, 9, 7, 9, 3, 60, 2, 14, 60, 9, 60, 45, 7, 7, 7, 9, 60, 3, 60, 7]
D.dist = Float32[0.0, 0.0, 0.0, 0.046584427, 0.017930388, 0.039820433, 0.0, 0.0, 0.0, 0.042595983, 0.040593803, 0.049079478, 0.008853316, 0.0, 0.04933691, 0.025703669, 0.0954504, 0.06557578, 0.07545, 0.0013739467, 0.060035884, 0.030670583, 0.03664857, 0.07886708, 0.008301735, 0.0, 0.054170728, 0.031862617, 0.07494664, 0.025352895, 0.021870434, 0.08160746, 0.016626298, 0.012451649, 0.0, 0.061640203, 0.04744929, 0.01971519, 0.0, 0.07460189, 0.005433202, 0.08430928, 0.063548684, 0.038577676, 0.0, 0.012135446, 0.02699095, 0.0249089, 0.038006425, 0.069200754, 0.042927146, 0.04136455, 0.043478668, 0.040031195, 0.05086726, 0.058951795, 0.042244792, 0.076737165, 0.04267311, 0.0, 0.004708469, 0.009794176, 0.05649823, 0.07786298, 0.022408307, 0.06509495, 0.0142047405, 0.014201999, 0.024970233, 0.037689924, 0.0032659173, 0.005299449, 0.035517514, 0.045986414, 0.04701501, 0.07668048, 0.044625163, 0.027070463, 0.04232323, 0.0779832, 0.003076315, 0.009058714, 0.07914293, 0.01158303, 0.019110382, 0.04448563, 0.049674153, 0.028257787, 0.0130675435, 0.051024556, 0.014799774, 0.011919379, 0.0074197054, 0.024604678, 0.010493338, 0.037412703, 0.06089288, 0.051594317, 0.06582898, 0.086134136]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  4.7s
computing farthest point 1, dmax: Inf, imax: 17, n: 30
computing farthest point 2, dmax: 1.2237632, imax: 15, n: 30
computing farthest point 3, dmax: 1.14092, imax: 18, n: 30
computing farthest point 4, dmax: 0.9311101, imax: 26, n: 30
computing farthest point 5, dmax: 0.8826937, imax: 20, n: 30
computing farthest point 6, dmax: 0.74482816, imax: 6, n: 30
computing farthest point 7, dmax: 0.6496644, imax: 10, n: 30
computing farthest point 8, dmax: 0.6479751, imax: 29, n: 30
computing farthest point 9, dmax: 0.629233, imax: 9, n: 30
computing farthest point 10, dmax: 0.5304339, imax: 13, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.1s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.1s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:12:55.535
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch
BeamSearch(bsize=2, Δ=0.8809524, maxvisits=112) 2026-01-26T23:13:03.930
LOG n.size quantiles:[3.0, 3.0, 4.0, 4.0, 4.0]
(i, j, d) = (5, 128, -1.1920929f-7)
(i, j, d, :parallel) = (5, 128, -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 => 13.311542862, :exact => 0.603936297)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  14.3s
  4.154380 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.003250 seconds
SEARCH Exhaustive 2: 0.003250 seconds
SEARCH Exhaustive 3: 0.003542 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
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:13:23.734
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch
BeamSearch(bsize=10, Δ=1.1287501, maxvisits=194) 2026-01-26T23:13:27.320
LOG n.size quantiles:[2.0, 3.0, 4.0, 4.0, 7.0]
LOG add_vertex! sp=25510 ep=25514 n=25509 BeamSearch
BeamSearch(bsize=16, Δ=1.244447, maxvisits=588) 2026-01-26T23:13:28.320
LOG n.size quantiles:[5.0, 5.0, 8.0, 9.0, 11.0]
LOG add_vertex! sp=43480 ep=43484 n=43479 BeamSearch
BeamSearch(bsize=10, Δ=1.1, maxvisits=430) 2026-01-26T23:13:29.320
LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 10.0]
LOG add_vertex! sp=59205 ep=59209 n=59204 BeamSearch
BeamSearch(bsize=6, Δ=0.95, maxvisits=438) 2026-01-26T23:13:30.320
LOG n.size quantiles:[3.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=75370 ep=75374 n=75369 BeamSearch
BeamSearch(bsize=6, Δ=0.95, maxvisits=438) 2026-01-26T23:13:31.320
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=87780 ep=87784 n=87779 BeamSearch
BeamSearch(bsize=12, Δ=1.1287501, maxvisits=570) 2026-01-26T23:13:32.320
LOG n.size quantiles:[4.0, 5.0, 7.0, 7.0, 7.0]
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, 23.0, 88.0]
[ Info: minrecall: queries per second: 16282.85295579129, recall: 0.900125
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=8, Δ=1.1851876, maxvisits=676))
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, 23.0, 88.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.1851876, maxvisits=600)), 1000, 8)
[ Info: rebuild: queries per second: 16636.93313975929, recall: 0.900375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.1851876, maxvisits=600))
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
BeamSearch(bsize=10, Δ=1.19, maxvisits=710)), 1000, 8)
  1.364801 seconds (703.37 k allocations: 36.074 MiB, 95.30% compilation time)
[ Info: matrixhints: queries per second: 15308.896874111559, recall: 0.90025
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.19, maxvisits=710))
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, 23.0, 88.0]
  2.010255 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.002474 seconds
SEARCH Exhaustive 2: 0.002593 seconds
SEARCH Exhaustive 3: 0.001696 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
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-26T23:14:26.976
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch
BeamSearch(bsize=10, Δ=1.1287501, maxvisits=194) 2026-01-26T23:14:32.185
LOG n.size quantiles:[2.0, 3.0, 4.0, 4.0, 7.0]
LOG add_vertex! sp=17500 ep=17504 n=17499 BeamSearch
BeamSearch(bsize=4, Δ=1.025, maxvisits=358) 2026-01-26T23:14:33.186
LOG n.size quantiles:[4.0, 5.0, 5.0, 7.0, 8.0]
LOG add_vertex! sp=30350 ep=30354 n=30349 BeamSearch
BeamSearch(bsize=16, Δ=1.244447, maxvisits=588) 2026-01-26T23:14:34.186
LOG n.size quantiles:[4.0, 6.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=39945 ep=39949 n=39944 BeamSearch
BeamSearch(bsize=10, Δ=1.1, maxvisits=430) 2026-01-26T23:14:35.186
LOG n.size quantiles:[4.0, 4.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=50260 ep=50264 n=50259 BeamSearch
BeamSearch(bsize=10, Δ=1.1, maxvisits=430) 2026-01-26T23:14:36.186
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 10.0]
LOG add_vertex! sp=59365 ep=59369 n=59364 BeamSearch
BeamSearch(bsize=6, Δ=0.95, maxvisits=438) 2026-01-26T23:14:37.187
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=69820 ep=69824 n=69819 BeamSearch
BeamSearch(bsize=6, Δ=0.95, maxvisits=438) 2026-01-26T23:14:38.187
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 9.0]
LOG add_vertex! sp=79855 ep=79859 n=79854 BeamSearch
BeamSearch(bsize=6, Δ=0.95, maxvisits=438) 2026-01-26T23:14:39.187
LOG n.size quantiles:[3.0, 6.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=87390 ep=87394 n=87389 BeamSearch
BeamSearch(bsize=12, Δ=1.1287501, maxvisits=570) 2026-01-26T23:14:40.188
LOG n.size quantiles:[5.0, 7.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=95415 ep=95419 n=95414 BeamSearch
BeamSearch(bsize=12, Δ=1.1287501, maxvisits=570) 2026-01-26T23:14:41.188
LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 8.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 88.0]
[ Info: minrecall: queries per second: 10944.212359045112, recall: 0.900125
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=8, Δ=1.1851876, maxvisits=676))
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, 23.0, 88.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.1851876, maxvisits=600)), 1000, 8)
[ Info: rebuild: queries per second: 12912.784932866689, recall: 0.900375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.1851876, maxvisits=600))
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
BeamSearch(bsize=10, Δ=1.19, maxvisits=710)), 1000, 8)
  1.600871 seconds (654.85 k allocations: 33.746 MiB, 94.10% compilation time)
[ Info: matrixhints: queries per second: 10885.522920709458, recall: 0.90025
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.19, maxvisits=710))
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, 23.0, 88.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  2m21.7s
     Testing SimilaritySearch tests passed 

Testing completed after 698.09s

PkgEval succeeded after 784.34s