Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1613 (8dab3f0623*) started at 2026-01-25T17:50:10.584


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

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

Set-up completed after 9.67s


################################################################################
# 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 v0.3.30+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [8e850b90] + libblastrampoline_jll v5.15.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 4.34s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   5168.9 ms  ✓ SearchModels
   9305.3 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 16 seconds. 88 already precompiled.

Precompilation completed after 33.06s


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

     Testing SimilaritySearch
      Status `/tmp/jl_lsLa2z/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_lsLa2z/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 v0.3.30+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  8.6s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  2.6s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  1.7s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  0.8s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  3.244992 seconds (1000 allocations: 78.125 KiB)
  3.148576 seconds (1000 allocations: 78.125 KiB)
  1.947863 seconds (1000 allocations: 78.125 KiB)
  1.864233 seconds (1000 allocations: 78.125 KiB)
  1.537412 seconds (1000 allocations: 78.125 KiB)
  1.947753 seconds (1000 allocations: 78.125 KiB)
  1.854447 seconds (1000 allocations: 78.125 KiB)
  1.912107 seconds (1000 allocations: 78.125 KiB)
 10.803779 seconds (1000 allocations: 78.125 KiB)
 10.712279 seconds (1000 allocations: 78.125 KiB)
 22.756301 seconds (1000 allocations: 78.125 KiB)
 22.673001 seconds (1000 allocations: 78.125 KiB)
 14.585768 seconds (6.23 k allocations: 358.094 KiB)
 13.375809 seconds (1000 allocations: 78.125 KiB)
 10.125847 seconds (1.00 k allocations: 78.141 KiB)
 10.637528 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  2m21.3s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  2.120561 seconds (1000 allocations: 78.125 KiB)
  2.117658 seconds (1000 allocations: 78.125 KiB)
 16.246680 seconds (1000 allocations: 78.125 KiB)
 16.080677 seconds (1000 allocations: 78.125 KiB)
 16.025629 seconds (1000 allocations: 78.125 KiB)
 16.153414 seconds (1000 allocations: 78.125 KiB)
  2.445202 seconds (1000 allocations: 78.125 KiB)
  2.416585 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  1m16.7s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  8.595945 seconds (1000 allocations: 78.125 KiB)
  8.545205 seconds (1000 allocations: 78.125 KiB)
  8.731563 seconds (1000 allocations: 78.125 KiB)
  8.466687 seconds (1000 allocations: 78.125 KiB)
  8.642750 seconds (1000 allocations: 78.125 KiB)
  8.583438 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total   Time
indexing sets with ExhaustiveSearch | 3000   3000  54.0s
  0.040925 seconds (1.00 k allocations: 78.141 KiB)
  0.040660 seconds (1000 allocations: 78.125 KiB)
  0.011911 seconds (1000 allocations: 78.125 KiB)
  0.011981 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  1.7s
  0.022553 seconds (1000 allocations: 78.125 KiB)
  0.021844 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  0.8s
ExhaustiveSearch allknn: 3.565147 seconds (1.99 M allocations: 119.646 MiB, 8.75% gc time, 99.98% compilation time)
ParallelExhaustiveSearch allknn: 0.963581 seconds (527.95 k allocations: 28.793 MiB, 99.89% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  5.0s
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  2.2s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:39.524
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-25T17:56:39.764
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) 2026-01-25T17:56:40.963
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: 2026-01-25T17:56:41.251
D.map = UInt32[0x00000001, 0x00000002, 0x00000005, 0x00000007, 0x00000009, 0x0000000d, 0x0000000e, 0x0000001b, 0x00000025, 0x0000003d, 0x00000053, 0x0000005d]
D.nn = Int32[1, 2, 1, 2, 5, 1, 7, 5, 9, 7, 1, 9, 13, 14, 7, 9, 1, 7, 13, 9, 9, 9, 9, 2, 1, 7, 27, 1, 9, 7, 9, 7, 7, 1, 7, 7, 37, 27, 9, 9, 1, 7, 5, 7, 14, 9, 37, 1, 9, 7, 9, 7, 7, 7, 1, 7, 27, 2, 7, 9, 61, 1, 1, 13, 61, 9, 61, 5, 27, 27, 9, 5, 5, 13, 13, 37, 9, 7, 7, 27, 27, 9, 83, 7, 1, 83, 1, 1, 37, 37, 83, 9, 93, 7, 9, 7, 5, 1, 83, 37]
D.dist = Float32[0.0, 0.0, 0.05005628, 0.007234812, 0.0, 0.09920871, 0.0, 0.0052607656, 0.0, 0.06616205, 0.027607262, 0.079399586, 0.0, 0.0, 0.086114585, 0.010052741, 0.024175525, 0.014244318, 0.08567512, 0.08326429, 0.03564316, 0.010602415, 0.09692633, 0.03136915, 0.003827989, 0.024288774, 0.0, 0.035619378, 0.023313344, 0.009109497, 0.027906835, 0.05164373, 0.052657366, 0.012278378, 0.01678735, 0.01691717, 0.0, 0.031409144, 0.072190344, 0.018515289, 0.0065212846, 0.021220922, 0.025906146, 0.019126475, 0.0638206, 0.026536942, 0.042901635, 0.0794335, 0.00062698126, 0.025264978, 0.04949236, 0.018796206, 0.034655333, 0.044912755, 0.034016848, 0.04973042, 0.028784454, 0.038747907, 0.019455671, 0.052740276, 0.0, 0.034139633, 0.030852199, 0.051829755, 0.027954996, 0.060272872, 0.07394391, 0.034376204, 0.071358085, 0.04988885, 0.038422942, 0.005988896, 0.06743795, 0.05177176, 0.053693414, 0.012496173, 0.005437255, 0.026483238, 0.07527107, 0.005886674, 0.08487457, 0.019366741, 0.0, 0.0361557, 0.08680147, 0.025633276, 0.05163467, 0.06921047, 0.038219273, 0.041634977, 0.029209971, 0.027414262, 0.0, 0.030258358, 0.036163628, 0.050507605, 0.032928765, 0.035850704, 0.004875362, 0.0037232637]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  13.4s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.241
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-25T17:56:42.241
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: 2026-01-25T17:56:42.242
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.242
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.242
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.242
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.242
[ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.242
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.242
D.map = UInt32[0x00000001, 0x00000002, 0x00000005, 0x00000007, 0x00000009, 0x0000000d, 0x0000000e, 0x0000001b, 0x00000025, 0x0000003d, 0x00000053, 0x0000005d]
D.nn = Int32[1, 2, 1, 2, 5, 1, 7, 5, 9, 7, 1, 9, 13, 14, 7, 9, 1, 7, 13, 9, 9, 9, 9, 2, 1, 7, 27, 1, 9, 7, 9, 7, 7, 1, 7, 7, 37, 27, 9, 9, 1, 7, 5, 7, 14, 9, 1, 1, 9, 7, 9, 7, 7, 7, 1, 7, 27, 2, 7, 9, 61, 1, 1, 13, 61, 9, 61, 5, 27, 27, 9, 5, 5, 13, 13, 37, 9, 7, 7, 27, 27, 9, 83, 7, 1, 9, 1, 1, 37, 37, 7, 9, 93, 7, 9, 7, 5, 1, 83, 37]
D.dist = Float32[0.0, 0.0, 0.05005628, 0.007234812, 0.0, 0.09920871, 0.0, 0.0052607656, 0.0, 0.06616205, 0.027607262, 0.079399586, 0.0, 0.0, 0.086114585, 0.010052741, 0.024175525, 0.014244318, 0.08567512, 0.08326429, 0.03564316, 0.010602415, 0.09692633, 0.03136915, 0.003827989, 0.024288774, 0.0, 0.035619378, 0.023313344, 0.009109497, 0.027906835, 0.05164373, 0.052657366, 0.012278378, 0.01678735, 0.01691717, 0.0, 0.031409144, 0.072190344, 0.018515289, 0.0065212846, 0.021220922, 0.025906146, 0.019126475, 0.0638206, 0.026536942, 0.063959, 0.0794335, 0.00062698126, 0.025264978, 0.04949236, 0.018796206, 0.034655333, 0.044912755, 0.034016848, 0.04973042, 0.028784454, 0.038747907, 0.019455671, 0.052740276, 0.0, 0.034139633, 0.030852199, 0.051829755, 0.027954996, 0.060272872, 0.07394391, 0.034376204, 0.071358085, 0.04988885, 0.038422942, 0.005988896, 0.06743795, 0.05177176, 0.053693414, 0.012496173, 0.005437255, 0.026483238, 0.07527107, 0.005886674, 0.08487457, 0.019366741, 0.0, 0.0361557, 0.08680147, 0.03870493, 0.05163467, 0.06921047, 0.038219273, 0.041634977, 0.03432548, 0.027414262, 0.0, 0.030258358, 0.036163628, 0.050507605, 0.032928765, 0.035850704, 0.004875362, 0.0037232637]
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: 2026-01-25T17:56:42.316
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-25T17:56:42.317
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: 2026-01-25T17:56:42.317
[ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.317
[ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.317
[ Info: neardup> range: 65:80, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.317
[ Info: neardup> range: 81:96, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.317
[ Info: neardup> range: 97:100, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.317
[ Info: neardup> finished current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:42.317
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000003d, 0x0000005d]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 10, 7, 13, 6, 16, 16, 3, 4, 1, 16, 6, 3, 9, 7, 16, 10, 7, 11, 7, 7, 11, 6, 3, 9, 1, 7, 5, 7, 14, 9, 10, 3, 9, 3, 6, 7, 10, 7, 16, 6, 6, 2, 7, 9, 61, 3, 3, 12, 61, 9, 10, 11, 12, 12, 12, 5, 5, 13, 13, 11, 9, 7, 7, 6, 11, 9, 15, 10, 11, 6, 10, 11, 10, 11, 7, 6, 93, 6, 16, 7, 11, 10, 15, 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, 0.016439557, 0.014244318, 0.08567512, 0.04105413, 0.02335161, 0.0030264854, 0.047440708, 0.031085074, 0.003827989, 0.021244884, 0.048698068, 0.0014720559, 0.023313344, 0.009109497, 0.0057612658, 0.017598927, 0.052657366, 0.008261621, 0.01678735, 0.01691717, 0.07596904, 0.0204795, 0.055309117, 0.018515289, 0.0065212846, 0.021220922, 0.025906146, 0.019126475, 0.0638206, 0.026536942, 0.06272876, 0.033094108, 0.00062698126, 0.018396676, 0.025415123, 0.018796206, 0.014545798, 0.044912755, 0.017678678, 0.027254164, 0.015937686, 0.038747907, 0.019455671, 0.052740276, 0.0, 0.0039533973, 0.029214919, 0.019465268, 0.027954996, 0.060272872, 0.07344735, 0.017416, 0.09831756, 0.055181503, 0.026095152, 0.005988896, 0.06743795, 0.05177176, 0.053693414, 0.03583306, 0.005437255, 0.026483238, 0.07527107, 0.03357303, 0.06327498, 0.019366741, 0.026680827, 0.022082329, 0.051319897, 0.02050066, 0.034826696, 0.043128073, 0.042007565, 0.026343524, 0.03432548, 1.31726265f-5, 0.0, 0.028005421, 0.009409249, 0.050507605, 0.021044314, 0.014375627, 0.031371355, 0.07253897]
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: 2026-01-25T17:56:48.002
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=7 n=7 2026-01-25T17:56:48.002
[ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
[ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-25T17:56:48.007
D.map = UInt32[0x00000001, 0x00000002, 0x00000005, 0x00000007, 0x00000009, 0x0000000d, 0x0000000e, 0x0000001b, 0x00000025, 0x0000003d, 0x00000053, 0x0000005d]
D.nn = Int32[1, 2, 1, 2, 5, 1, 7, 5, 9, 7, 1, 9, 13, 14, 7, 9, 1, 7, 13, 9, 9, 9, 9, 2, 1, 7, 27, 1, 9, 7, 9, 7, 7, 1, 7, 7, 37, 27, 9, 9, 1, 7, 5, 7, 14, 9, 1, 1, 9, 7, 9, 7, 7, 7, 1, 7, 27, 2, 7, 9, 61, 1, 1, 13, 61, 9, 61, 5, 27, 27, 9, 5, 5, 13, 13, 37, 9, 7, 7, 27, 27, 9, 83, 7, 1, 9, 1, 1, 37, 37, 7, 9, 93, 7, 9, 7, 5, 1, 83, 37]
D.dist = Float32[0.0, 0.0, 0.05005628, 0.007234812, 0.0, 0.09920871, 0.0, 0.0052607656, 0.0, 0.06616205, 0.027607262, 0.079399586, 0.0, 0.0, 0.086114585, 0.010052741, 0.024175525, 0.014244318, 0.08567512, 0.08326429, 0.03564316, 0.010602415, 0.09692633, 0.03136915, 0.003827989, 0.024288774, 0.0, 0.035619378, 0.023313344, 0.009109497, 0.027906835, 0.05164373, 0.052657366, 0.012278378, 0.01678735, 0.01691717, 0.0, 0.031409144, 0.072190344, 0.018515289, 0.0065212846, 0.021220922, 0.025906146, 0.019126475, 0.0638206, 0.026536942, 0.063959, 0.0794335, 0.00062698126, 0.025264978, 0.04949236, 0.018796206, 0.034655333, 0.044912755, 0.034016848, 0.04973042, 0.028784454, 0.038747907, 0.019455671, 0.052740276, 0.0, 0.034139633, 0.030852199, 0.051829755, 0.027954996, 0.060272872, 0.07394391, 0.034376204, 0.071358085, 0.04988885, 0.038422942, 0.005988896, 0.06743795, 0.05177176, 0.053693414, 0.012496173, 0.005437255, 0.026483238, 0.07527107, 0.005886674, 0.08487457, 0.019366741, 0.0, 0.0361557, 0.08680147, 0.03870493, 0.05163467, 0.06921047, 0.038219273, 0.041634977, 0.03432548, 0.027414262, 0.0, 0.030258358, 0.036163628, 0.050507605, 0.032928765, 0.035850704, 0.004875362, 0.0037232637]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  5.7s
computing farthest point 1, dmax: Inf, imax: 28, n: 30
computing farthest point 2, dmax: 1.4906878, imax: 4, n: 30
computing farthest point 3, dmax: 1.1292846, imax: 19, n: 30
computing farthest point 4, dmax: 0.9236683, imax: 15, n: 30
computing farthest point 5, dmax: 0.88905144, imax: 14, n: 30
computing farthest point 6, dmax: 0.7418767, imax: 21, n: 30
computing farthest point 7, dmax: 0.7053568, imax: 11, n: 30
computing farthest point 8, dmax: 0.65499556, imax: 5, n: 30
computing farthest point 9, dmax: 0.567663, imax: 6, n: 30
computing farthest point 10, dmax: 0.56461155, imax: 23, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.2s
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) 2026-01-25T17:56:53.480
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=0.9, maxvisits=122) 2026-01-25T17:57:02.298
LOG n.size quantiles:[3.0, 3.0, 3.0, 5.0, 5.0]
(i, j, d) = (30, 374, -1.1920929f-7)
(i, j, d, :parallel) = (30, 374, -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 => 13.620241382, :exact => 0.744845584)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  14.9s
  2.038155 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001696 seconds
SEARCH Exhaustive 2: 0.001713 seconds
SEARCH Exhaustive 3: 0.001682 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) 2026-01-25T17:57:17.060
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=14, Δ=1.155, maxvisits=184) 2026-01-25T17:57:20.876
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 8.0]
LOG add_vertex! sp=27385 ep=27389 n=27384 BeamSearch
BeamSearch(bsize=16, Δ=1.05, maxvisits=424) 2026-01-25T17:57:21.876
LOG n.size quantiles:[8.0, 8.0, 8.0, 8.0, 12.0]
LOG add_vertex! sp=47760 ep=47764 n=47759 BeamSearch
BeamSearch(bsize=16, Δ=1.07625, maxvisits=390) 2026-01-25T17:57:22.876
LOG n.size quantiles:[4.0, 5.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=57775 ep=57779 n=57774 BeamSearch
BeamSearch(bsize=11, Δ=1.2733874, maxvisits=578) 2026-01-25T17:57:23.876
LOG n.size quantiles:[3.0, 6.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=74205 ep=74209 n=74204 BeamSearch
BeamSearch(bsize=11, Δ=1.2733874, maxvisits=578) 2026-01-25T17:57:24.876
LOG n.size quantiles:[4.0, 5.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=86875 ep=86879 n=86874 BeamSearch
BeamSearch(bsize=8, Δ=1.155, maxvisits=480) 2026-01-25T17:57:25.876
LOG n.size quantiles:[7.0, 7.0, 7.0, 9.0, 11.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 89.0]
[ Info: minrecall: queries per second: 18552.553177322316, recall: 0.90075
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.1025, maxvisits=748))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 89.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=6, Δ=1.1851876, maxvisits=562)), 1000, 8)
[ Info: rebuild: queries per second: 22680.883619101503, recall: 0.906375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=6, Δ=1.1851876, maxvisits=562))
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=1.11, maxvisits=688)), 1000, 8)
  1.475515 seconds (496.50 k allocations: 28.657 MiB, 24.42% gc time, 96.77% compilation time)
[ Info: matrixhints: queries per second: 20826.649280579848, recall: 0.901875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.11, maxvisits=688))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 89.0]
  1.816717 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001590 seconds
SEARCH Exhaustive 2: 0.001583 seconds
SEARCH Exhaustive 3: 0.001618 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) 2026-01-25T17:58:08.988
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=14, Δ=1.155, maxvisits=184) 2026-01-25T17:58:12.783
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 8.0]
LOG add_vertex! sp=28155 ep=28159 n=28154 BeamSearch
BeamSearch(bsize=16, Δ=1.05, maxvisits=424) 2026-01-25T17:58:13.783
LOG n.size quantiles:[7.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=48585 ep=48589 n=48584 BeamSearch
BeamSearch(bsize=16, Δ=1.07625, maxvisits=390) 2026-01-25T17:58:14.783
LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=64475 ep=64479 n=64474 BeamSearch
BeamSearch(bsize=11, Δ=1.2733874, maxvisits=578) 2026-01-25T17:58:15.784
LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=78295 ep=78299 n=78294 BeamSearch
BeamSearch(bsize=11, Δ=1.2733874, maxvisits=578) 2026-01-25T17:58:16.784
LOG n.size quantiles:[5.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=90980 ep=90984 n=90979 BeamSearch
BeamSearch(bsize=8, Δ=1.155, maxvisits=480) 2026-01-25T17:58:17.784
LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 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, 13.0, 15.0, 18.0, 23.0, 89.0]
[ Info: minrecall: queries per second: 22360.90105218549, recall: 0.90075
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.1025, maxvisits=748))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 89.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=6, Δ=1.1851876, maxvisits=562)), 1000, 8)
[ Info: rebuild: queries per second: 22678.806057019236, recall: 0.906375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=6, Δ=1.1851876, maxvisits=562))
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=1.11, maxvisits=688)), 1000, 8)
  1.085340 seconds (460.09 k allocations: 26.639 MiB, 95.84% compilation time)
[ Info: matrixhints: queries per second: 15958.639801722198, recall: 0.901875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.11, maxvisits=688))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 89.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  1m41.6s
     Testing SimilaritySearch tests passed 

Testing completed after 463.29s

PkgEval succeeded after 524.26s