Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1563 (14ca1abc72*) started at 2026-01-15T17:52:54.337


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

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

Set-up completed after 10.14s


################################################################################
# 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 4.4s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   5208.1 ms  ✓ SearchModels
   8824.3 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 16 seconds. 88 already precompiled.

Precompilation completed after 32.78s


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

     Testing SimilaritySearch
      Status `/tmp/jl_4mIfGd/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_4mIfGd/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  8.0s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  2.5s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.1s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  0.8s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  2.646928 seconds (1000 allocations: 78.125 KiB)
  2.771205 seconds (1000 allocations: 78.125 KiB)
  2.012824 seconds (1000 allocations: 78.125 KiB)
  1.954404 seconds (1000 allocations: 78.125 KiB)
  1.853223 seconds (1000 allocations: 78.125 KiB)
  1.837703 seconds (1000 allocations: 78.125 KiB)
  1.807164 seconds (1000 allocations: 78.125 KiB)
  1.794873 seconds (1000 allocations: 78.125 KiB)
 10.714416 seconds (1000 allocations: 78.125 KiB)
 10.520290 seconds (1000 allocations: 78.125 KiB)
 22.895971 seconds (1000 allocations: 78.125 KiB)
 22.693303 seconds (1000 allocations: 78.125 KiB)
 13.974559 seconds (6.23 k allocations: 358.094 KiB)
 14.049206 seconds (1000 allocations: 78.125 KiB)
 10.956781 seconds (1.00 k allocations: 78.141 KiB)
 10.681960 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  2m21.2s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  2.358539 seconds (1000 allocations: 78.125 KiB)
  2.420004 seconds (1000 allocations: 78.125 KiB)
 15.864661 seconds (1000 allocations: 78.125 KiB)
 15.812267 seconds (1000 allocations: 78.125 KiB)
 15.892043 seconds (1000 allocations: 78.125 KiB)
 15.790541 seconds (1000 allocations: 78.125 KiB)
  2.580945 seconds (1000 allocations: 78.125 KiB)
  2.570445 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  1m16.1s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  8.431404 seconds (1000 allocations: 78.125 KiB)
  8.603100 seconds (1000 allocations: 78.125 KiB)
  8.715708 seconds (1000 allocations: 78.125 KiB)
  8.586551 seconds (1000 allocations: 78.125 KiB)
  8.704026 seconds (1000 allocations: 78.125 KiB)
  8.700878 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total   Time
indexing sets with ExhaustiveSearch | 3000   3000  54.3s
  0.040570 seconds (1.00 k allocations: 78.141 KiB)
  0.040266 seconds (1000 allocations: 78.125 KiB)
  0.019207 seconds (1000 allocations: 78.125 KiB)
  0.019300 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  2.0s
  0.021843 seconds (1000 allocations: 78.125 KiB)
  0.021841 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  0.9s
ExhaustiveSearch allknn: 3.486919 seconds (1.99 M allocations: 119.660 MiB, 1.08% gc time, 99.96% compilation time)
ParallelExhaustiveSearch allknn: 1.021513 seconds (528.00 k allocations: 28.793 MiB, 5.53% gc time, 99.90% 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, 5.0]
Test Summary: | Total  Time
HSP           |     0  2.1s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:22.280
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-15T17:59:22.505
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) 2026-01-15T17:59:23.983
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
[ Info: neardup> finished current elements: 13, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:24.250
D.map = UInt32[0x00000001, 0x00000002, 0x00000007, 0x0000000f, 0x00000015, 0x00000016, 0x00000018, 0x0000001d, 0x00000024, 0x00000025, 0x0000002f, 0x0000003d, 0x00000055]
D.nn = Int32[1, 2, 2, 2, 2, 2, 7, 2, 7, 7, 7, 7, 2, 2, 15, 7, 2, 1, 2, 2, 21, 22, 22, 24, 21, 21, 21, 2, 29, 2, 2, 21, 24, 22, 29, 36, 37, 2, 37, 7, 2, 7, 22, 2, 1, 2, 47, 22, 22, 2, 47, 36, 1, 1, 1, 36, 7, 1, 47, 1, 61, 2, 37, 47, 1, 36, 15, 7, 2, 22, 7, 1, 29, 2, 2, 7, 21, 22, 21, 2, 29, 2, 21, 37, 85, 2, 85, 1, 2, 61, 36, 29, 36, 85, 36, 47, 2, 7, 37, 2]
D.dist = Float32[0.0, 0.0, 0.023296416, 0.042846084, 0.026309907, 0.07424939, 0.0, 0.017231107, 0.05812317, 0.05679834, 0.021820247, 0.029740393, 0.07174975, 0.03777927, 0.0, 0.020534694, 0.046500027, 0.009053588, 0.03173089, 0.05244541, 0.0, 0.0, 0.04497856, 0.0, 0.025662899, 0.055006683, 0.08514744, 0.061566293, 0.0, 0.015670776, 0.0034086108, 0.058662772, 0.024997413, 0.07780391, 0.058492005, 0.0, 0.0, 0.031372428, 0.041643143, 0.07324231, 0.037547827, 0.050773025, 0.021444619, 0.013415337, 0.015568495, 0.01859504, 0.0, 0.029607415, 0.0067096353, 0.08096993, 0.038048804, 0.030206025, 0.06158203, 0.038735986, 0.07799715, 0.01382041, 0.0632596, 0.08590585, 0.036767423, 0.042809486, 0.0, 0.066446304, 0.07411343, 0.016584456, 0.0050656796, 0.012616634, 0.013790429, 0.042088687, 0.022395194, 0.026049912, 0.054921985, 0.043462038, 0.060272753, 0.09824318, 0.055418253, 0.03067404, 0.04384184, 0.016010046, 0.038279474, 0.03063494, 0.01555568, 0.05397564, 0.02142185, 0.018712163, 0.0, 0.04195714, 0.051058948, 0.03660184, 0.02231735, 0.047223926, 0.046873033, 0.04463744, 0.023234367, 0.037753046, 0.006982863, 0.03783554, 0.029108942, 0.050863266, 0.004564047, 0.048759818]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  13.0s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.155
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-15T17:59:25.156
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 4, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
[ Info: neardup> range: 65:80, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
[ Info: neardup> range: 81:96, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
[ Info: neardup> range: 97:100, current elements: 13, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
[ Info: neardup> finished current elements: 13, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.156
D.map = UInt32[0x00000001, 0x00000002, 0x00000007, 0x0000000f, 0x00000015, 0x00000016, 0x00000018, 0x0000001d, 0x00000024, 0x00000025, 0x0000002f, 0x0000003d, 0x00000055]
D.nn = Int32[1, 2, 2, 2, 2, 2, 7, 2, 7, 7, 7, 7, 2, 2, 15, 7, 2, 1, 2, 2, 21, 22, 22, 24, 7, 21, 21, 2, 29, 2, 2, 21, 24, 22, 29, 36, 37, 2, 2, 7, 2, 7, 22, 2, 1, 2, 47, 22, 22, 2, 47, 36, 1, 1, 1, 36, 7, 1, 47, 1, 61, 2, 37, 47, 1, 36, 15, 7, 2, 22, 7, 1, 29, 2, 2, 7, 21, 22, 21, 2, 29, 2, 21, 37, 85, 2, 2, 1, 2, 61, 36, 29, 36, 2, 36, 47, 2, 7, 37, 2]
D.dist = Float32[0.0, 0.0, 0.023296416, 0.042846084, 0.026309907, 0.07424939, 0.0, 0.017231107, 0.05812317, 0.05679834, 0.021820247, 0.029740393, 0.07174975, 0.03777927, 0.0, 0.020534694, 0.046500027, 0.009053588, 0.03173089, 0.05244541, 0.0, 0.0, 0.04497856, 0.0, 0.0903548, 0.055006683, 0.08514744, 0.061566293, 0.0, 0.015670776, 0.0034086108, 0.058662772, 0.024997413, 0.07780391, 0.058492005, 0.0, 0.0, 0.031372428, 0.063321054, 0.07324231, 0.037547827, 0.050773025, 0.021444619, 0.013415337, 0.015568495, 0.01859504, 0.0, 0.029607415, 0.0067096353, 0.08096993, 0.038048804, 0.030206025, 0.06158203, 0.038735986, 0.07799715, 0.01382041, 0.0632596, 0.08590585, 0.036767423, 0.042809486, 0.0, 0.066446304, 0.07411343, 0.016584456, 0.0050656796, 0.012616634, 0.013790429, 0.042088687, 0.022395194, 0.026049912, 0.054921985, 0.043462038, 0.060272753, 0.09824318, 0.055418253, 0.03067404, 0.04384184, 0.016010046, 0.038279474, 0.03063494, 0.01555568, 0.05397564, 0.02142185, 0.018712163, 0.0, 0.04195714, 0.065524936, 0.03660184, 0.02231735, 0.047223926, 0.046873033, 0.04463744, 0.023234367, 0.06516409, 0.006982863, 0.03783554, 0.029108942, 0.050863266, 0.004564047, 0.048759818]
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: 2026-01-15T17:59:25.224
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-15T17:59:25.225
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: 2026-01-15T17:59:25.225
[ Info: neardup> range: 33:48, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.225
[ Info: neardup> range: 49:64, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.225
[ Info: neardup> range: 65:80, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.225
[ Info: neardup> range: 81:96, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.225
[ Info: neardup> range: 97:100, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.226
[ Info: neardup> finished current elements: 19, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:25.226
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000015, 0x00000018, 0x00000024]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 5, 1, 2, 14, 21, 6, 6, 24, 16, 10, 5, 13, 14, 14, 2, 10, 24, 4, 5, 36, 5, 5, 5, 16, 5, 12, 8, 2, 1, 14, 9, 2, 6, 13, 9, 36, 3, 1, 3, 36, 12, 1, 4, 1, 10, 10, 14, 4, 1, 36, 15, 16, 3, 6, 12, 1, 14, 13, 3, 9, 12, 6, 21, 8, 14, 14, 21, 5, 3, 6, 13, 1, 5, 9, 36, 13, 36, 5, 36, 4, 5, 4, 5, 14]
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, 0.008909106, 0.009053588, 0.03173089, 0.017468274, 0.0, 0.037407935, 0.07086533, 0.0, 0.034655333, 0.028700173, 0.028816879, 0.015093982, 0.09266865, 0.0141816735, 0.0034086108, 0.0403229, 0.024997413, 0.07618028, 0.029273093, 0.0, 0.08829546, 0.020314038, 0.01610136, 0.031249583, 0.008542359, 0.006301403, 0.019461274, 0.013415337, 0.015568495, 0.00982517, 0.021701396, 0.081113875, 0.03838533, 0.050712943, 0.0339455, 0.030206025, 0.03785318, 0.038735986, 0.06999284, 0.01382041, 0.009440243, 0.08590585, 0.029032648, 0.042809486, 0.060211957, 0.022089303, 0.065723, 0.01992166, 0.0050656796, 0.012616634, 0.013790429, 0.013973534, 0.01061815, 0.019694626, 0.008443773, 0.043462038, 0.008770883, 0.032693386, 0.024077833, 0.027191281, 0.017031789, 0.041431665, 0.038279474, 0.030634642, 0.037962615, 0.038048863, 0.02142185, 0.070489705, 0.08772975, 0.0050752163, 0.0056081414, 0.03660184, 0.0024154186, 0.072968245, 0.046873033, 0.03745246, 0.023234367, 0.055571854, 0.006982863, 0.028620899, 0.010886908, 0.028662026, 0.06533617, 0.002945006]
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: 2026-01-15T17:59:30.772
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=4 n=4 2026-01-15T17:59:30.772
[ Info: neardup> range: 17:32, current elements: 4, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.779
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.779
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.779
[ Info: neardup> range: 65:80, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.779
[ Info: neardup> range: 81:96, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.780
[ Info: neardup> range: 97:100, current elements: 13, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.780
[ Info: neardup> finished current elements: 13, n: 100, ϵ: 0.1, timestamp: 2026-01-15T17:59:30.780
D.map = UInt32[0x00000001, 0x00000002, 0x00000007, 0x0000000f, 0x00000015, 0x00000016, 0x00000018, 0x0000001d, 0x00000024, 0x00000025, 0x0000002f, 0x0000003d, 0x00000055]
D.nn = Int32[1, 2, 2, 2, 2, 2, 7, 2, 7, 7, 7, 7, 2, 2, 15, 7, 2, 1, 2, 2, 21, 22, 22, 24, 7, 21, 21, 2, 29, 2, 2, 21, 24, 22, 29, 36, 37, 2, 2, 7, 2, 7, 22, 2, 1, 2, 47, 22, 22, 2, 47, 36, 1, 1, 1, 36, 7, 1, 47, 1, 61, 2, 37, 47, 1, 36, 15, 7, 2, 22, 7, 1, 29, 2, 2, 7, 21, 22, 21, 2, 29, 2, 21, 37, 85, 2, 2, 1, 2, 61, 36, 29, 36, 2, 36, 47, 2, 7, 37, 2]
D.dist = Float32[0.0, 0.0, 0.023296416, 0.042846084, 0.026309907, 0.07424939, 0.0, 0.017231107, 0.05812317, 0.05679834, 0.021820247, 0.029740393, 0.07174975, 0.03777927, 0.0, 0.020534694, 0.046500027, 0.009053588, 0.03173089, 0.05244541, 0.0, 0.0, 0.04497856, 0.0, 0.0903548, 0.055006683, 0.08514744, 0.061566293, 0.0, 0.015670776, 0.0034086108, 0.058662772, 0.024997413, 0.07780391, 0.058492005, 0.0, 0.0, 0.031372428, 0.063321054, 0.07324231, 0.037547827, 0.050773025, 0.021444619, 0.013415337, 0.015568495, 0.01859504, 0.0, 0.029607415, 0.0067096353, 0.08096993, 0.038048804, 0.030206025, 0.06158203, 0.038735986, 0.07799715, 0.01382041, 0.0632596, 0.08590585, 0.036767423, 0.042809486, 0.0, 0.066446304, 0.07411343, 0.016584456, 0.0050656796, 0.012616634, 0.013790429, 0.042088687, 0.022395194, 0.026049912, 0.054921985, 0.043462038, 0.060272753, 0.09824318, 0.055418253, 0.03067404, 0.04384184, 0.016010046, 0.038279474, 0.03063494, 0.01555568, 0.05397564, 0.02142185, 0.018712163, 0.0, 0.04195714, 0.065524936, 0.03660184, 0.02231735, 0.047223926, 0.046873033, 0.04463744, 0.023234367, 0.06516409, 0.006982863, 0.03783554, 0.029108942, 0.050863266, 0.004564047, 0.048759818]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  5.6s
computing farthest point 1, dmax: Inf, imax: 21, n: 30
computing farthest point 2, dmax: 1.1627401, imax: 18, n: 30
computing farthest point 3, dmax: 0.8769404, imax: 11, n: 30
computing farthest point 4, dmax: 0.8663582, imax: 14, n: 30
computing farthest point 5, dmax: 0.8333144, imax: 22, n: 30
computing farthest point 6, dmax: 0.65798104, imax: 15, n: 30
computing farthest point 7, dmax: 0.5540813, imax: 8, n: 30
computing farthest point 8, dmax: 0.5322868, imax: 28, n: 30
computing farthest point 9, dmax: 0.50157666, imax: 16, n: 30
computing farthest point 10, dmax: 0.48481908, imax: 24, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.1s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.0s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-15T17:59:36.013
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=0.99999994, maxvisits=108) 2026-01-15T17:59:44.809
LOG n.size quantiles:[4.0, 4.0, 5.0, 5.0, 6.0]
(i, j, d) = (15, 883, -1.1920929f-7)
(i, j, d, :parallel) = (15, 883, -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 => 13.502516817, :exact => 0.735650791)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  14.7s
  1.976930 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001686 seconds
SEARCH Exhaustive 2: 0.001710 seconds
SEARCH Exhaustive 3: 0.001726 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) 2026-01-15T17:59:59.373
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=1.1851876, maxvisits=192) 2026-01-15T18:00:03.350
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 6.0]
LOG add_vertex! sp=28275 ep=28279 n=28274 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=442) 2026-01-15T18:00:04.350
LOG n.size quantiles:[5.0, 5.0, 5.0, 6.0, 6.0]
LOG add_vertex! sp=47190 ep=47194 n=47189 BeamSearch
BeamSearch(bsize=6, Δ=1.21275, maxvisits=446) 2026-01-15T18:00:05.351
LOG n.size quantiles:[5.0, 6.0, 7.0, 9.0, 10.0]
LOG add_vertex! sp=62405 ep=62409 n=62404 BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=466) 2026-01-15T18:00:06.351
LOG n.size quantiles:[5.0, 7.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=76990 ep=76994 n=76989 BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=466) 2026-01-15T18:00:07.351
LOG n.size quantiles:[4.0, 5.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=90185 ep=90189 n=90184 BeamSearch
BeamSearch(bsize=14, Δ=1.075, maxvisits=476) 2026-01-15T18:00:08.351
LOG n.size quantiles:[4.0, 4.0, 7.0, 7.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 98.0]
[ Info: minrecall: queries per second: 18639.55168597634, recall: 0.901375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=5, Δ=1.075, maxvisits=642))
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, 98.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.13, maxvisits=580)), 1000, 8)
[ Info: rebuild: queries per second: 22534.89793730643, recall: 0.89875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.13, maxvisits=580))
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=9, Δ=1.075, maxvisits=662)), 1000, 8)
  1.103625 seconds (496.50 k allocations: 28.661 MiB, 94.78% compilation time)
[ Info: matrixhints: queries per second: 21213.086921832808, recall: 0.901375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=9, Δ=1.075, maxvisits=662))
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, 98.0]
  1.795237 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001462 seconds
SEARCH Exhaustive 2: 0.001535 seconds
SEARCH Exhaustive 3: 0.001460 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) 2026-01-15T18:00:48.176
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=1.1851876, maxvisits=192) 2026-01-15T18:00:51.759
LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 6.0]
LOG add_vertex! sp=30265 ep=30269 n=30264 BeamSearch
BeamSearch(bsize=14, Δ=1.1, maxvisits=442) 2026-01-15T18:00:52.759
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=49575 ep=49579 n=49574 BeamSearch
BeamSearch(bsize=6, Δ=1.21275, maxvisits=446) 2026-01-15T18:00:53.759
LOG n.size quantiles:[7.0, 7.0, 8.0, 11.0, 11.0]
LOG add_vertex! sp=66040 ep=66044 n=66039 BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=466) 2026-01-15T18:00:54.759
LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=81305 ep=81309 n=81304 BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=466) 2026-01-15T18:00:55.759
LOG n.size quantiles:[5.0, 5.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=95810 ep=95814 n=95809 BeamSearch
BeamSearch(bsize=14, Δ=1.075, maxvisits=476) 2026-01-15T18:00:56.759
LOG n.size quantiles:[6.0, 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, 13.0, 15.0, 18.0, 23.0, 98.0]
[ Info: minrecall: queries per second: 21868.714931328734, recall: 0.901375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=5, Δ=1.075, maxvisits=642))
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, 98.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.13, maxvisits=580)), 1000, 8)
[ Info: rebuild: queries per second: 26339.919612672536, recall: 0.89875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.13, maxvisits=580))
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=9, Δ=1.075, maxvisits=662)), 1000, 8)
  1.057312 seconds (460.09 k allocations: 26.639 MiB, 95.80% compilation time)
[ Info: matrixhints: queries per second: 22625.310736017647, recall: 0.901375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=9, Δ=1.075, maxvisits=662))
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, 98.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  1m33.7s
     Testing SimilaritySearch tests passed 

Testing completed after 453.0s

PkgEval succeeded after 515.46s