Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1601 (79ea5eb99c*) started at 2026-01-24T14:40:16.029


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

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

Set-up completed after 9.09s


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

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [053f045d] + SimilaritySearch v0.13.7
    Updating `~/.julia/environments/v1.14/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 v1.13.0
  [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 v0.3.29+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [8e850b90] + libblastrampoline_jll v5.15.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 4.2s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   5023.4 ms  ✓ SearchModels
   8826.7 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 15 seconds. 88 already precompiled.

Precompilation completed after 31.65s


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

     Testing SimilaritySearch
      Status `/tmp/jl_FTDYcn/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 v1.13.0
  [9a3f8284] Random v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_FTDYcn/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 v1.13.0
  [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 v0.3.29+0
  [458c3c95] OpenSSL_jll v3.5.4+0
  [efcefdf7] PCRE2_jll v10.47.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [3161d3a3] Zstd_jll v1.5.7+1
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.68.0+1
  [3f19e933] p7zip_jll v17.7.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Test Summary:              | Pass  Total  Time
test database abstractions |   56     56  8.8s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  2.7s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  1.6s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  0.8s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  2.586988 seconds (1000 allocations: 78.125 KiB)
  2.585878 seconds (1000 allocations: 78.125 KiB)
  1.908988 seconds (1000 allocations: 78.125 KiB)
  1.929469 seconds (1000 allocations: 78.125 KiB)
  1.888323 seconds (1000 allocations: 78.125 KiB)
  1.968674 seconds (1000 allocations: 78.125 KiB)
  1.975438 seconds (1000 allocations: 78.125 KiB)
  1.993037 seconds (1000 allocations: 78.125 KiB)
 11.050196 seconds (1000 allocations: 78.125 KiB)
 11.058218 seconds (1000 allocations: 78.125 KiB)
 22.744023 seconds (1000 allocations: 78.125 KiB)
 22.799610 seconds (1000 allocations: 78.125 KiB)
 12.364224 seconds (6.23 k allocations: 358.094 KiB)
 14.929123 seconds (1000 allocations: 78.125 KiB)
 12.163827 seconds (1.00 k allocations: 78.141 KiB)
 12.243585 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  2m24.2s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  2.437790 seconds (1000 allocations: 78.125 KiB)
  2.346930 seconds (1000 allocations: 78.125 KiB)
 15.959805 seconds (1000 allocations: 78.125 KiB)
 16.145395 seconds (1000 allocations: 78.125 KiB)
 14.898080 seconds (1000 allocations: 78.125 KiB)
 11.039600 seconds (1000 allocations: 78.125 KiB)
  1.709605 seconds (1000 allocations: 78.125 KiB)
  1.745534 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  1m08.8s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  8.507497 seconds (1000 allocations: 78.125 KiB)
  8.761458 seconds (1000 allocations: 78.125 KiB)
  8.603772 seconds (1000 allocations: 78.125 KiB)
  8.671913 seconds (1000 allocations: 78.125 KiB)
  8.670558 seconds (1000 allocations: 78.125 KiB)
  8.822864 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total   Time
indexing sets with ExhaustiveSearch | 3000   3000  54.3s
  0.047898 seconds (1.00 k allocations: 78.141 KiB)
  0.048798 seconds (1000 allocations: 78.125 KiB)
  0.019663 seconds (1000 allocations: 78.125 KiB)
  0.019534 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  1.9s
  0.022260 seconds (1000 allocations: 78.125 KiB)
  0.022088 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  0.9s
ExhaustiveSearch allknn: 3.408093 seconds (1.99 M allocations: 119.624 MiB, 2.38% gc time, 99.98% compilation time)
ParallelExhaustiveSearch allknn: 0.953804 seconds (527.95 k allocations: 28.784 MiB, 99.90% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  4.8s
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  2.1s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:36.698
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-24T14:46:36.915
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) 2026-01-24T14:46:38.354
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:38.631
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000005, 0x00000007, 0x00000008, 0x0000000b, 0x00000010, 0x00000014, 0x0000001b, 0x0000003b]
D.nn = Int32[1, 2, 3, 2, 5, 2, 7, 8, 5, 2, 11, 5, 3, 11, 5, 16, 2, 11, 8, 20, 3, 11, 3, 5, 8, 11, 27, 11, 3, 5, 5, 5, 20, 11, 11, 20, 11, 11, 11, 20, 5, 8, 5, 3, 20, 20, 11, 3, 5, 1, 27, 8, 3, 3, 16, 5, 20, 5, 59, 2, 20, 3, 8, 7, 20, 11, 5, 7, 7, 5, 1, 5, 2, 20, 8, 11, 2, 8, 2, 5, 20, 20, 59, 3, 8, 1, 16, 8, 1, 5, 1, 20, 11, 3, 20, 20, 2, 1, 7, 20]
D.dist = Float32[0.0, 0.0, 0.0, 0.046927452, 0.0, 0.06372422, 0.0, 0.0, 0.06624669, 0.03685081, 0.0, 0.037539065, 0.026457608, 0.01044625, 0.040866494, 0.0, 0.06592131, 0.07508016, 0.022847354, 0.0, 0.043043792, 0.0035911798, 0.050896585, 0.034175277, 0.028353453, 0.074849725, 0.0, 0.025431693, 0.080360234, 0.009773791, 0.039348602, 0.026046872, 0.035305202, 0.000792861, 0.03700912, 0.029581904, 0.013414025, 0.021108508, 0.016434431, 0.012836337, 0.037079513, 0.0076539516, 0.023442566, 0.039839447, 0.037861705, 0.04883963, 0.03902346, 0.032114446, 0.03379202, 0.050492823, 0.044565976, 0.021944463, 0.0343498, 0.015918732, 0.063480735, 0.0016440153, 0.041398466, 0.047579825, 0.0, 0.0669812, 0.0057932734, 0.029579818, 0.037379324, 0.047186017, 0.047609806, 0.051743925, 0.045862675, 0.040552616, 0.06038648, 0.07486391, 0.048509598, 0.049394786, 0.08426607, 0.058387756, 0.02843684, 0.01953429, 0.023162961, 0.02236092, 0.04276353, 0.013825834, 0.045439124, 0.020295203, 0.01175034, 0.06914753, 0.030169785, 0.0468114, 0.046453, 0.020508826, 0.012383163, 0.060205758, 0.016985893, 0.031386256, 0.026377857, 0.02157271, 0.058444142, 0.029092193, 0.033685744, 0.081100285, 0.024546921, 0.058542132]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  12.9s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.520
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-24T14:46:39.520
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: 2026-01-24T14:46:39.522
[ Info: neardup> range: 33:48, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.522
[ Info: neardup> range: 49:64, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.522
[ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.522
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.522
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.522
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.522
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000005, 0x00000007, 0x00000008, 0x0000000b, 0x00000010, 0x00000014, 0x0000001b, 0x0000003b]
D.nn = Int32[1, 2, 3, 2, 5, 2, 7, 8, 5, 2, 11, 5, 3, 11, 5, 16, 2, 11, 8, 20, 3, 11, 3, 5, 8, 11, 27, 11, 3, 5, 5, 5, 20, 11, 11, 20, 11, 11, 11, 20, 5, 8, 5, 3, 20, 20, 11, 3, 5, 1, 27, 8, 3, 3, 16, 5, 20, 5, 59, 2, 20, 3, 8, 7, 20, 11, 5, 7, 7, 5, 1, 5, 2, 20, 8, 11, 2, 8, 2, 5, 20, 20, 59, 3, 8, 1, 16, 8, 1, 5, 1, 20, 11, 3, 20, 20, 2, 1, 7, 20]
D.dist = Float32[0.0, 0.0, 0.0, 0.046927452, 0.0, 0.06372422, 0.0, 0.0, 0.06624669, 0.03685081, 0.0, 0.037539065, 0.026457608, 0.01044625, 0.040866494, 0.0, 0.06592131, 0.07508016, 0.022847354, 0.0, 0.043043792, 0.0035911798, 0.050896585, 0.034175277, 0.028353453, 0.074849725, 0.0, 0.025431693, 0.080360234, 0.009773791, 0.039348602, 0.026046872, 0.035305202, 0.000792861, 0.03700912, 0.029581904, 0.013414025, 0.021108508, 0.016434431, 0.012836337, 0.037079513, 0.0076539516, 0.023442566, 0.039839447, 0.037861705, 0.04883963, 0.03902346, 0.032114446, 0.03379202, 0.050492823, 0.044565976, 0.021944463, 0.0343498, 0.015918732, 0.063480735, 0.0016440153, 0.041398466, 0.047579825, 0.0, 0.0669812, 0.0057932734, 0.029579818, 0.037379324, 0.047186017, 0.047609806, 0.051743925, 0.045862675, 0.040552616, 0.06038648, 0.07486391, 0.048509598, 0.049394786, 0.08426607, 0.058387756, 0.02843684, 0.01953429, 0.023162961, 0.02236092, 0.04276353, 0.013825834, 0.045439124, 0.020295203, 0.01175034, 0.06914753, 0.030169785, 0.0468114, 0.046453, 0.020508826, 0.012383163, 0.060205758, 0.016985893, 0.031386256, 0.026377857, 0.02157271, 0.058444142, 0.029092193, 0.033685744, 0.081100285, 0.024546921, 0.058542132]
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: 2026-01-24T14:46:39.591
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-24T14:46:39.591
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: 2026-01-24T14:46:39.592
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.592
[ Info: neardup> range: 49:64, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.592
[ Info: neardup> range: 65:80, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.592
[ Info: neardup> range: 81:96, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.592
[ Info: neardup> range: 97:100, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.592
[ Info: neardup> finished current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:39.592
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000001b, 0x0000003b]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 10, 10, 8, 13, 3, 11, 3, 13, 8, 11, 27, 11, 13, 5, 12, 5, 13, 11, 11, 15, 11, 14, 11, 15, 15, 8, 5, 3, 10, 10, 11, 3, 9, 1, 27, 8, 3, 3, 16, 5, 10, 15, 59, 10, 10, 3, 8, 6, 10, 14, 5, 4, 9, 9, 1, 5, 4, 10, 8, 11, 10, 8, 10, 5, 10, 10, 59, 3, 8, 1, 16, 8, 1, 10, 1, 13, 11, 13, 15, 15, 2, 14, 7, 10]
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, 0.038246334, 0.03928435, 0.022847354, 0.056123257, 0.043043792, 0.0035911798, 0.050896585, 0.033406377, 0.028353453, 0.074849725, 0.0, 0.025431693, 0.04803884, 0.009773791, 0.017421365, 0.026046872, 0.008912265, 0.000792861, 0.03700912, 0.015791059, 0.013414025, 0.006863892, 0.016434431, 0.050445855, 0.010551035, 0.0076539516, 0.023442566, 0.039839447, 0.0476889, 0.010775387, 0.03902346, 0.032114446, 0.02628839, 0.050492823, 0.044565976, 0.021944463, 0.0343498, 0.015918732, 0.063480735, 0.0016440153, 0.03868699, 0.011585295, 0.0, 0.00740695, 0.06018734, 0.029579818, 0.037379324, 0.029998839, 0.03621745, 0.030089319, 0.045862675, 0.013847053, 0.03288555, 0.020977974, 0.048509598, 0.049394786, 0.014691949, 0.048497558, 0.02843684, 0.01953429, 0.007724762, 0.02236092, 0.03561139, 0.013825834, 0.022696018, 0.05182296, 0.01175034, 0.06914753, 0.030169785, 0.0468114, 0.046453, 0.020508826, 0.012383163, 0.031417668, 0.016985893, 0.0038129687, 0.026377857, 0.010637283, 0.01071012, 0.015219748, 0.033685744, 0.066464365, 0.024546921, 0.024342895]
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: 2026-01-24T14:46:44.974
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=8 n=8 2026-01-24T14:46:44.974
[ Info: neardup> range: 17:32, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
[ Info: neardup> range: 33:48, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
[ Info: neardup> range: 49:64, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
[ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-24T14:46:44.980
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000005, 0x00000007, 0x00000008, 0x0000000b, 0x00000010, 0x00000014, 0x0000001b, 0x0000003b]
D.nn = Int32[1, 2, 3, 2, 5, 2, 7, 8, 5, 2, 11, 5, 3, 11, 5, 16, 2, 11, 8, 20, 3, 11, 3, 5, 8, 11, 27, 11, 3, 5, 5, 5, 20, 11, 11, 20, 11, 11, 11, 20, 5, 8, 5, 3, 20, 20, 11, 3, 5, 1, 27, 8, 3, 3, 16, 5, 20, 5, 59, 2, 20, 3, 8, 7, 20, 11, 5, 7, 7, 5, 1, 5, 2, 20, 8, 11, 2, 8, 2, 5, 20, 20, 59, 3, 8, 1, 16, 8, 1, 5, 1, 20, 11, 3, 20, 20, 2, 1, 7, 20]
D.dist = Float32[0.0, 0.0, 0.0, 0.046927452, 0.0, 0.06372422, 0.0, 0.0, 0.06624669, 0.03685081, 0.0, 0.037539065, 0.026457608, 0.01044625, 0.040866494, 0.0, 0.06592131, 0.07508016, 0.022847354, 0.0, 0.043043792, 0.0035911798, 0.050896585, 0.034175277, 0.028353453, 0.074849725, 0.0, 0.025431693, 0.080360234, 0.009773791, 0.039348602, 0.026046872, 0.035305202, 0.000792861, 0.03700912, 0.029581904, 0.013414025, 0.021108508, 0.016434431, 0.012836337, 0.037079513, 0.0076539516, 0.023442566, 0.039839447, 0.037861705, 0.04883963, 0.03902346, 0.032114446, 0.03379202, 0.050492823, 0.044565976, 0.021944463, 0.0343498, 0.015918732, 0.063480735, 0.0016440153, 0.041398466, 0.047579825, 0.0, 0.0669812, 0.0057932734, 0.029579818, 0.037379324, 0.047186017, 0.047609806, 0.051743925, 0.045862675, 0.040552616, 0.06038648, 0.07486391, 0.048509598, 0.049394786, 0.08426607, 0.058387756, 0.02843684, 0.01953429, 0.023162961, 0.02236092, 0.04276353, 0.013825834, 0.045439124, 0.020295203, 0.01175034, 0.06914753, 0.030169785, 0.0468114, 0.046453, 0.020508826, 0.012383163, 0.060205758, 0.016985893, 0.031386256, 0.026377857, 0.02157271, 0.058444142, 0.029092193, 0.033685744, 0.081100285, 0.024546921, 0.058542132]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  5.4s
computing farthest point 1, dmax: Inf, imax: 16, n: 30
computing farthest point 2, dmax: 1.2771413, imax: 14, n: 30
computing farthest point 3, dmax: 0.97116727, imax: 4, n: 30
computing farthest point 4, dmax: 0.9027537, imax: 19, n: 30
computing farthest point 5, dmax: 0.79915863, imax: 27, n: 30
computing farthest point 6, dmax: 0.7800405, imax: 29, n: 30
computing farthest point 7, dmax: 0.74751323, imax: 12, n: 30
computing farthest point 8, dmax: 0.69366664, imax: 1, n: 30
computing farthest point 9, dmax: 0.6215835, imax: 20, n: 30
computing farthest point 10, dmax: 0.57114714, imax: 9, 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) 2026-01-24T14:46:50.228
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=0.7247617, maxvisits=122) 2026-01-24T14:46:57.983
LOG n.size quantiles:[3.0, 5.0, 5.0, 5.0, 6.0]
(i, j, d) = (19, 128, -1.1920929f-7)
(i, j, d, :parallel) = (19, 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 => 12.406826599, :exact => 0.731046233)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  13.6s
  1.949995 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001214 seconds
SEARCH Exhaustive 2: 0.001313 seconds
SEARCH Exhaustive 3: 0.000958 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) 2026-01-24T14:47:12.542
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=12, Δ=1.025, maxvisits=198) 2026-01-24T14:47:15.953
LOG n.size quantiles:[3.0, 3.0, 5.0, 6.0, 7.0]
LOG add_vertex! sp=35680 ep=35684 n=35679 BeamSearch
BeamSearch(bsize=4, Δ=1.025, maxvisits=392) 2026-01-24T14:47:16.953
LOG n.size quantiles:[5.0, 5.0, 5.0, 6.0, 6.0]
LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=482) 2026-01-24T14:47:18.001
LOG n.size quantiles:[5.0, 5.0, 8.0, 9.0, 10.0]
LOG add_vertex! sp=72615 ep=72619 n=72614 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=482) 2026-01-24T14:47:19.001
LOG n.size quantiles:[6.0, 6.0, 7.0, 8.0, 10.0]
LOG add_vertex! sp=85435 ep=85439 n=85434 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=524) 2026-01-24T14:47:20.299
LOG n.size quantiles:[5.0, 8.0, 8.0, 9.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 95.0]
[ Info: minrecall: queries per second: 20328.56572902241, recall: 0.90125
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=12, Δ=1.1287501, maxvisits=762))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 95.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=4, Δ=1.1287501, maxvisits=624)), 1000, 8)
[ Info: rebuild: queries per second: 23518.053928073557, recall: 0.897625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=4, Δ=1.1287501, maxvisits=624))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=13, Δ=1.1340001, maxvisits=738)), 1000, 8)
  0.994687 seconds (496.32 k allocations: 28.649 MiB, 94.71% compilation time)
[ Info: matrixhints: queries per second: 19992.96927242566, recall: 0.9015
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=13, Δ=1.1340001, maxvisits=738))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 95.0]
  1.904739 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001538 seconds
SEARCH Exhaustive 2: 0.001458 seconds
SEARCH Exhaustive 3: 0.001612 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) 2026-01-24T14:48:02.485
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=12, Δ=1.025, maxvisits=198) 2026-01-24T14:48:06.183
LOG n.size quantiles:[3.0, 3.0, 5.0, 6.0, 7.0]
LOG add_vertex! sp=34370 ep=34374 n=34369 BeamSearch
BeamSearch(bsize=4, Δ=1.025, maxvisits=392) 2026-01-24T14:48:07.183
LOG n.size quantiles:[4.0, 4.0, 5.0, 6.0, 9.0]
LOG add_vertex! sp=55145 ep=55149 n=55144 BeamSearch
BeamSearch(bsize=14, Δ=1.0, maxvisits=502) 2026-01-24T14:48:08.183
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 9.0]
LOG add_vertex! sp=70680 ep=70684 n=70679 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=482) 2026-01-24T14:48:09.183
LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 8.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=524) 2026-01-24T14:48:10.213
LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=99765 ep=99769 n=99764 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=524) 2026-01-24T14:48:11.213
LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 95.0]
[ Info: minrecall: queries per second: 20424.09697867763, recall: 0.90125
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=12, Δ=1.1287501, maxvisits=762))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 95.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=4, Δ=1.1287501, maxvisits=624)), 1000, 8)
[ Info: rebuild: queries per second: 22412.331587577057, recall: 0.897625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=4, Δ=1.1287501, maxvisits=624))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=13, Δ=1.1340001, maxvisits=738)), 1000, 8)
  1.100880 seconds (459.91 k allocations: 26.627 MiB, 95.81% compilation time)
[ Info: matrixhints: queries per second: 21344.12355617943, recall: 0.9015
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=13, Δ=1.1340001, maxvisits=738))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 95.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  1m38.1s
     Testing SimilaritySearch tests passed 

Testing completed after 452.29s

PkgEval succeeded after 510.84s