Package evaluation to test SimilaritySearch on Julia 1.11.8 (29b3528cce*) started at 2026-01-20T07:07:47.361


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

Installing PkgEval dependencies (TestEnv)...
  Activating project at `~/.julia/environments/v1.11`

Set-up completed after 8.6s


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

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.11/Project.toml`
  [053f045d] + SimilaritySearch v0.13.7
    Updating `~/.julia/environments/v1.11/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 v1.2.1
  [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
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.11.0
  [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 v1.11.0
  [fa267f1f] + TOML v1.0.3
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0
  [4536629a] + OpenBLAS_jll v0.3.27+1
  [bea87d4a] + SuiteSparse_jll v7.7.0+0
  [8e850b90] + libblastrampoline_jll v5.11.0+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 5.59s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling project...
   3959.3 ms  ✓ SearchModels
  17638.3 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 23 seconds. 85 already precompiled.

Precompilation completed after 37.46s


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

     Testing SimilaritySearch
      Status `/tmp/jl_rDNLN9/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 v1.11.0
  [9a3f8284] Random v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_rDNLN9/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 v1.2.1
  [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 v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg 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 v1.11.0
  [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 v1.1.1+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
        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  9.0s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.0s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  4.2s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.8s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.3s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  4.739088 seconds (1000 allocations: 78.125 KiB)
  4.744948 seconds (1000 allocations: 78.125 KiB)
  4.571317 seconds (1000 allocations: 78.125 KiB)
  4.591309 seconds (1000 allocations: 78.125 KiB)
  4.716510 seconds (1000 allocations: 78.125 KiB)
  4.704626 seconds (1000 allocations: 78.125 KiB)
  4.767349 seconds (1000 allocations: 78.125 KiB)
  4.373973 seconds (1000 allocations: 78.125 KiB)
 12.417135 seconds (1000 allocations: 78.125 KiB)
 12.630479 seconds (1000 allocations: 78.125 KiB)
 25.705365 seconds (1000 allocations: 78.125 KiB)
 25.502746 seconds (1000 allocations: 78.125 KiB)
 19.457999 seconds (1000 allocations: 78.125 KiB)
 19.985892 seconds (1000 allocations: 78.125 KiB)
 18.068770 seconds (1000 allocations: 78.125 KiB)
 18.314132 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m24.3s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.292441 seconds (1000 allocations: 78.125 KiB)
  3.290868 seconds (1000 allocations: 78.125 KiB)
 45.191037 seconds (1000 allocations: 78.125 KiB)
 44.984885 seconds (1000 allocations: 78.125 KiB)
 45.053965 seconds (1000 allocations: 78.125 KiB)
 28.633938 seconds (1000 allocations: 78.125 KiB)
  4.869689 seconds (1000 allocations: 78.125 KiB)
  4.815021 seconds (1000 allocations: 78.125 KiB, 1.01% gc time)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  3m04.5s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  8.724924 seconds (1000 allocations: 78.125 KiB)
  8.328960 seconds (1000 allocations: 78.125 KiB)
  8.230382 seconds (1000 allocations: 78.125 KiB)
  8.304908 seconds (1000 allocations: 78.125 KiB)
  8.226313 seconds (1000 allocations: 78.125 KiB)
  8.125363 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total   Time
indexing sets with ExhaustiveSearch | 3000   3000  53.4s
  0.043027 seconds (1000 allocations: 78.125 KiB)
  0.043193 seconds (1000 allocations: 78.125 KiB)
  0.041055 seconds (1000 allocations: 78.125 KiB)
  0.040255 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  0.2s
  0.050404 seconds (1000 allocations: 78.125 KiB)
  0.051661 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.7s
ExhaustiveSearch allknn: 0.429753 seconds (146.10 k allocations: 7.492 MiB, 3.36% gc time, 99.76% compilation time)
ParallelExhaustiveSearch allknn: 1.342774 seconds (596.44 k allocations: 29.583 MiB, 99.90% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  1.9s
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  4.6s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:08.927
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-20T07:17:09.290
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:10.547
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x0000000e, 0x00000011, 0x00000013, 0x0000001d, 0x00000020]
D.nn = Int32[1, 2, 3, 1, 2, 6, 2, 3, 1, 1, 2, 1, 2, 14, 2, 2, 17, 2, 19, 2, 14, 14, 2, 1, 1, 19, 3, 19, 29, 3, 2, 32, 3, 14, 6, 1, 14, 2, 19, 6, 3, 19, 2, 19, 14, 14, 2, 2, 14, 6, 2, 19, 6, 1, 2, 19, 3, 14, 14, 14, 14, 1, 32, 14, 14, 3, 3, 3, 1, 19, 3, 3, 3, 1, 19, 32, 2, 32, 2, 19, 17, 3, 2, 2, 29, 2, 3, 32, 17, 14, 14, 14, 3, 1, 1, 2, 2, 19, 2, 29]
D.dist = Float32[0.0, 0.0, 0.0, 0.04803914, 0.056531906, 0.0, 0.021585166, 0.044174016, 0.064144015, 0.050103962, 0.055961788, 0.013631761, 0.024399579, 0.0, 0.030998588, 0.03281367, 0.0, 0.043511868, 0.0, 0.036752224, 0.020038545, 0.009558499, 0.02684474, 0.007530451, 0.017584682, 0.05379778, 0.02945745, 0.049998164, 0.0, 0.035831094, 0.074436486, 0.0, 0.040326774, 0.029928923, 0.023819149, 0.08244729, 0.009993017, 0.039766014, 0.06497717, 0.030576587, 0.0353508, 0.053747594, 0.015236437, 0.024392784, 0.009640515, 0.03499508, 0.052380085, 0.06324613, 0.007906973, 0.015211105, 0.022139132, 0.048062384, 0.019455314, 0.027607858, 0.021919906, 0.05005622, 0.026073754, 0.016073346, 0.0015266538, 0.019443333, 0.035532296, 0.034063697, 0.014917195, 0.025622904, 0.0202564, 0.055781364, 0.047641873, 0.08181703, 0.017187715, 0.009236813, 0.024267673, 0.037450254, 0.036227882, 0.057956696, 0.039866626, 0.02376926, 0.05614221, 0.06747991, 0.01726365, 0.026480973, 0.077969074, 0.058586538, 0.027904868, 0.00067317486, 0.042372882, 0.021401823, 0.0021539927, 0.02309233, 0.0071529746, 0.08412123, 0.061084628, 0.048891902, 0.03077513, 0.022985816, 0.03178668, 0.023408234, 0.040928602, 0.05879885, 0.030178308, 0.04845941]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  19.5s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.190
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-20T07:17:12.190
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
[ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
[ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
[ Info: neardup> range: 97:100, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
[ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.191
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x0000000e, 0x00000011, 0x00000013, 0x0000001d, 0x00000020]
D.nn = Int32[1, 2, 3, 1, 2, 6, 2, 3, 1, 1, 2, 1, 2, 14, 2, 2, 17, 2, 19, 2, 14, 14, 2, 1, 1, 3, 3, 19, 29, 3, 2, 32, 3, 14, 6, 1, 14, 2, 19, 6, 3, 19, 2, 19, 14, 14, 2, 2, 14, 6, 2, 19, 6, 1, 2, 19, 3, 14, 14, 14, 14, 1, 32, 14, 14, 3, 3, 3, 1, 19, 3, 3, 3, 1, 19, 32, 2, 32, 2, 19, 17, 3, 2, 2, 29, 2, 3, 32, 17, 14, 14, 14, 3, 1, 1, 2, 2, 19, 2, 29]
D.dist = Float32[0.0, 0.0, 0.0, 0.04803914, 0.056531906, 0.0, 0.021585166, 0.044174016, 0.064144015, 0.050103962, 0.055961788, 0.013631761, 0.024399579, 0.0, 0.030998588, 0.03281367, 0.0, 0.043511868, 0.0, 0.036752224, 0.020038545, 0.009558499, 0.02684474, 0.007530451, 0.017584682, 0.081044555, 0.02945745, 0.049998164, 0.0, 0.035831094, 0.074436486, 0.0, 0.040326774, 0.029928923, 0.023819149, 0.08244729, 0.009993017, 0.039766014, 0.06497717, 0.030576587, 0.0353508, 0.053747594, 0.015236437, 0.024392784, 0.009640515, 0.03499508, 0.052380085, 0.06324613, 0.007906973, 0.015211105, 0.022139132, 0.048062384, 0.019455314, 0.027607858, 0.021919906, 0.05005622, 0.026073754, 0.016073346, 0.0015266538, 0.019443333, 0.035532296, 0.034063697, 0.014917195, 0.025622904, 0.0202564, 0.055781364, 0.047641873, 0.08181703, 0.017187715, 0.009236813, 0.024267673, 0.037450254, 0.036227882, 0.057956696, 0.039866626, 0.02376926, 0.05614221, 0.06747991, 0.01726365, 0.026480973, 0.077969074, 0.058586538, 0.027904868, 0.00067317486, 0.042372882, 0.021401823, 0.0021539927, 0.02309233, 0.0071529746, 0.08412123, 0.061084628, 0.048891902, 0.03077513, 0.022985816, 0.03178668, 0.023408234, 0.040928602, 0.05879885, 0.030178308, 0.04845941]
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: 2026-01-20T07:17:12.277
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-20T07:17:12.277
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: 2026-01-20T07:17:12.277
[ Info: neardup> range: 33:48, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.277
[ Info: neardup> range: 49:64, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.277
[ Info: neardup> range: 65:80, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.277
[ Info: neardup> range: 81:96, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.278
[ Info: neardup> range: 97:100, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.278
[ Info: neardup> finished current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:12.278
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000013, 0x0000001c, 0x0000001d]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 11, 2, 19, 13, 5, 14, 13, 12, 10, 8, 8, 28, 29, 11, 16, 5, 13, 5, 6, 8, 14, 15, 19, 6, 3, 19, 15, 19, 14, 14, 9, 13, 14, 6, 13, 28, 6, 1, 13, 9, 3, 14, 14, 14, 9, 4, 5, 14, 14, 13, 4, 8, 16, 19, 3, 4, 13, 1, 28, 15, 7, 2, 13, 19, 11, 3, 15, 2, 29, 7, 3, 5, 11, 10, 14, 10, 13, 12, 10, 7, 13, 19, 16, 29]
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, 0.05335951, 0.043511868, 0.0, 0.017419994, 0.017496645, 0.009558499, 0.012435377, 0.0036364794, 0.01129818, 0.039806962, 0.025036395, 0.0, 0.0, 0.009805858, 0.019604325, 0.08153355, 0.023670733, 0.014862418, 0.023819149, 0.008739114, 0.009993017, 0.008389771, 0.06497717, 0.030576587, 0.0353508, 0.053747594, 0.00754416, 0.024392784, 0.009640515, 0.03499508, 0.022265494, 0.026657462, 0.007906973, 0.015211105, 0.018835485, 0.02028203, 0.019455314, 0.027607858, 0.007523954, 0.0403893, 0.026073754, 0.016073346, 0.0015266538, 0.019443333, 0.0062668324, 0.0087682605, 0.04728037, 0.025622904, 0.0202564, 0.022193313, 0.0031253695, 0.03166467, 0.013130605, 0.009236813, 0.024267673, 0.0038090944, 0.012364805, 0.057956696, 0.036876023, 0.03396243, 0.016498625, 0.06793362, 0.0025024414, 0.026480973, 0.041543007, 0.058586538, 0.022059202, 0.00067317486, 0.042372882, 0.012841463, 0.0021539927, 0.020248294, 0.0657323, 0.03381419, 0.061084628, 0.023513973, 0.010564387, 0.021769524, 0.0051059127, 0.0075660944, 0.019580245, 0.05879885, 0.005286634, 0.04845941]
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: 2026-01-20T07:17:18.838
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=5 n=5 2026-01-20T07:17:18.838
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
[ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
[ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
[ Info: neardup> range: 97:100, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
[ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-20T07:17:18.841
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x0000000e, 0x00000011, 0x00000013, 0x0000001d, 0x00000020]
D.nn = Int32[1, 2, 3, 1, 2, 6, 2, 3, 1, 1, 2, 1, 2, 14, 2, 2, 17, 2, 19, 2, 14, 14, 2, 1, 1, 3, 3, 19, 29, 3, 2, 32, 3, 14, 6, 1, 14, 2, 19, 6, 3, 19, 2, 19, 14, 14, 2, 2, 14, 6, 2, 19, 6, 1, 2, 19, 3, 14, 14, 14, 14, 1, 32, 14, 14, 3, 3, 3, 1, 19, 3, 3, 3, 1, 19, 32, 2, 32, 2, 19, 17, 3, 2, 2, 29, 2, 3, 32, 17, 14, 14, 14, 3, 1, 1, 2, 2, 19, 2, 29]
D.dist = Float32[0.0, 0.0, 0.0, 0.04803914, 0.056531906, 0.0, 0.021585166, 0.044174016, 0.064144015, 0.050103962, 0.055961788, 0.013631761, 0.024399579, 0.0, 0.030998588, 0.03281367, 0.0, 0.043511868, 0.0, 0.036752224, 0.020038545, 0.009558499, 0.02684474, 0.007530451, 0.017584682, 0.081044555, 0.02945745, 0.049998164, 0.0, 0.035831094, 0.074436486, 0.0, 0.040326774, 0.029928923, 0.023819149, 0.08244729, 0.009993017, 0.039766014, 0.06497717, 0.030576587, 0.0353508, 0.053747594, 0.015236437, 0.024392784, 0.009640515, 0.03499508, 0.052380085, 0.06324613, 0.007906973, 0.015211105, 0.022139132, 0.048062384, 0.019455314, 0.027607858, 0.021919906, 0.05005622, 0.026073754, 0.016073346, 0.0015266538, 0.019443333, 0.035532296, 0.034063697, 0.014917195, 0.025622904, 0.0202564, 0.055781364, 0.047641873, 0.08181703, 0.017187715, 0.009236813, 0.024267673, 0.037450254, 0.036227882, 0.057956696, 0.039866626, 0.02376926, 0.05614221, 0.06747991, 0.01726365, 0.026480973, 0.077969074, 0.058586538, 0.027904868, 0.00067317486, 0.042372882, 0.021401823, 0.0021539927, 0.02309233, 0.0071529746, 0.08412123, 0.061084628, 0.048891902, 0.03077513, 0.022985816, 0.03178668, 0.023408234, 0.040928602, 0.05879885, 0.030178308, 0.04845941]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  6.6s
computing farthest point 1, dmax: Inf, imax: 15, n: 30
computing farthest point 2, dmax: 1.1448392, imax: 26, n: 30
computing farthest point 3, dmax: 1.0001801, imax: 6, n: 30
computing farthest point 4, dmax: 0.93736196, imax: 20, n: 30
computing farthest point 5, dmax: 0.91499513, imax: 22, n: 30
computing farthest point 6, dmax: 0.72576624, imax: 24, n: 30
computing farthest point 7, dmax: 0.6899008, imax: 28, n: 30
computing farthest point 8, dmax: 0.64454114, imax: 17, n: 30
computing farthest point 9, dmax: 0.5922393, imax: 23, n: 30
computing farthest point 10, dmax: 0.5288897, imax: 3, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.7s
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) 2026-01-20T07:17:27.055
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=0.94, maxvisits=120) 2026-01-20T07:17:35.184
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 5.0]
(i, j, d) = (97, 248, -1.1920929f-7)
(i, j, d, :parallel) = (97, 248, -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 => 8.177769618, :exact => 0.074803927)
Test Summary: | Pass  Total  Time
closestpair   |    4      4  8.5s
  3.096707 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.003568 seconds
SEARCH Exhaustive 2: 0.003707 seconds
SEARCH Exhaustive 3: 0.003584 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) 2026-01-20T07:17:49.732
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=8, Δ=1.075, maxvisits=182) 2026-01-20T07:17:54.123
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 6.0]
LOG add_vertex! sp=25255 ep=25259 n=25254 BeamSearch
BeamSearch(bsize=4, Δ=1.3370568, maxvisits=508) 2026-01-20T07:17:55.152
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=41495 ep=41499 n=41494 BeamSearch
BeamSearch(bsize=14, Δ=1.1287501, maxvisits=416) 2026-01-20T07:17:56.152
LOG n.size quantiles:[5.0, 5.0, 6.0, 8.0, 10.0]
LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=516) 2026-01-20T07:17:57.205
LOG n.size quantiles:[6.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=71185 ep=71189 n=71184 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=516) 2026-01-20T07:17:58.205
LOG n.size quantiles:[4.0, 6.0, 6.0, 8.0, 10.0]
LOG add_vertex! sp=84190 ep=84194 n=84189 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=516) 2026-01-20T07:17:59.205
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 7.0]
LOG add_vertex! sp=96995 ep=96999 n=96994 BeamSearch
BeamSearch(bsize=16, Δ=0.9, maxvisits=398) 2026-01-20T07:18:00.205
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 83.0]
[ Info: minrecall: queries per second: 16907.872687641287, recall: 0.903625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=6, Δ=1.1287501, maxvisits=766))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 83.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=14, Δ=1.155, maxvisits=552)), 1000, 8)
[ Info: rebuild: queries per second: 20437.558313463258, recall: 0.90175
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=14, Δ=1.155, maxvisits=552))
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, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=802)), 1000, 8)
  1.379682 seconds (657.97 k allocations: 33.339 MiB, 1.05% gc time, 95.99% compilation time)
[ Info: matrixhints: queries per second: 20090.10573141385, recall: 0.899125
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=802))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 83.0]
  2.004236 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001699 seconds
SEARCH Exhaustive 2: 0.001691 seconds
SEARCH Exhaustive 3: 0.001804 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) 2026-01-20T07:18:44.400
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=8, Δ=1.075, maxvisits=182) 2026-01-20T07:18:48.555
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 6.0]
LOG add_vertex! sp=26545 ep=26549 n=26544 BeamSearch
BeamSearch(bsize=4, Δ=1.3370568, maxvisits=508) 2026-01-20T07:18:49.555
LOG n.size quantiles:[5.0, 5.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=43910 ep=43914 n=43909 BeamSearch
BeamSearch(bsize=14, Δ=1.1287501, maxvisits=416) 2026-01-20T07:18:50.555
LOG n.size quantiles:[5.0, 7.0, 9.0, 9.0, 11.0]
LOG add_vertex! sp=58820 ep=58824 n=58819 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=516) 2026-01-20T07:18:51.555
LOG n.size quantiles:[6.0, 8.0, 9.0, 9.0, 13.0]
LOG add_vertex! sp=72990 ep=72994 n=72989 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=516) 2026-01-20T07:18:52.555
LOG n.size quantiles:[6.0, 6.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch
BeamSearch(bsize=16, Δ=0.9, maxvisits=398) 2026-01-20T07:18:53.581
LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=99305 ep=99309 n=99304 BeamSearch
BeamSearch(bsize=16, Δ=0.9, maxvisits=398) 2026-01-20T07:18:54.581
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 83.0]
[ Info: minrecall: queries per second: 17625.900795895788, recall: 0.903625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=6, Δ=1.1287501, maxvisits=766))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 83.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=14, Δ=1.155, maxvisits=552)), 1000, 8)
[ Info: rebuild: queries per second: 19615.714808220884, recall: 0.90175
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=14, Δ=1.155, maxvisits=552))
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, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=802)), 1000, 8)
  1.195745 seconds (639.11 k allocations: 32.331 MiB, 95.45% compilation time)
[ Info: matrixhints: queries per second: 18762.01402115327, recall: 0.899125
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=802))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 83.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  1m45.0s
     Testing SimilaritySearch tests passed 

Testing completed after 637.83s

PkgEval succeeded after 700.14s