Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1720 (f38c537ec6*) started at 2026-02-15T16:58:36.239


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

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

Set-up completed after 11.98s


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

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [053f045d] + SimilaritySearch v0.13.8
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [7d9f7c33] + Accessors v0.1.43
  [79e6a3ab] + Adapt v4.4.0
  [4fba245c] + ArrayInterface v7.22.0
  [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
  [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
  [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 v0.5.0
  [053f045d] + SimilaritySearch v0.13.8
  [a2af1166] + SortingAlgorithms v1.2.2
  [aedffcd0] + Static v1.3.1
  [0d7ed370] + StaticArrayInterface v1.9.0
  [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
  [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 4.73s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   3202.4 ms  ✓ SearchModels
   7273.2 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 11 seconds. 81 already precompiled.

Precompilation completed after 33.02s


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

     Testing SimilaritySearch
      Status `/tmp/jl_esI0Ou/Project.toml`
  [7d9f7c33] Accessors v0.1.43
  [4c88cf16] Aqua v0.8.14
  [b4f34e82] Distances v0.10.12
  [92933f4c] ProgressMeter v1.11.0
  [0e966ebe] SearchModels v0.5.0
  [053f045d] SimilaritySearch v0.13.8
  [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_esI0Ou/Manifest.toml`
  [7d9f7c33] Accessors v0.1.43
  [79e6a3ab] Adapt v4.4.0
  [4c88cf16] Aqua v0.8.14
  [4fba245c] ArrayInterface v7.22.0
  [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
  [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
  [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 v0.5.0
  [053f045d] SimilaritySearch v0.13.8
  [a2af1166] SortingAlgorithms v1.2.2
  [aedffcd0] Static v1.3.1
  [0d7ed370] StaticArrayInterface v1.9.0
  [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
  [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 v3.5.5+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 |   57     57  17.1s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  4.1s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  3.0s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  5.923301 seconds (400.99 k allocations: 24.719 MiB, 36.85% compilation time)
  3.688531 seconds (7 allocations: 512 bytes)
  5.772651 seconds (255.89 k allocations: 16.082 MiB, 35.43% compilation time)
  3.853388 seconds (7 allocations: 512 bytes)
  5.709713 seconds (239.65 k allocations: 15.180 MiB, 0.49% gc time, 36.35% compilation time)
  3.749429 seconds (7 allocations: 512 bytes)
  5.696533 seconds (235.08 k allocations: 14.919 MiB, 35.68% compilation time)
  3.687126 seconds (7 allocations: 512 bytes)
 16.065927 seconds (247.56 k allocations: 15.590 MiB, 11.17% compilation time)
 14.155293 seconds (7 allocations: 512 bytes)
 27.476873 seconds (7 allocations: 512 bytes)
 27.259785 seconds (7 allocations: 512 bytes)
 20.459512 seconds (511.71 k allocations: 31.515 MiB, 0.39% gc time, 8.43% compilation time)
 19.027441 seconds (7 allocations: 512 bytes)
 18.499920 seconds (406.88 k allocations: 25.467 MiB, 0.36% gc time, 6.92% compilation time)
 17.271870 seconds (7 allocations: 512 bytes)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m23.7s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  4.433599 seconds (169.02 k allocations: 11.273 MiB, 39.71% compilation time)
  2.611224 seconds (7 allocations: 512 bytes)
 28.365523 seconds (210.48 k allocations: 13.628 MiB, 6.58% compilation time)
 28.385565 seconds (7 allocations: 528 bytes)
 28.079756 seconds (7 allocations: 528 bytes)
 28.053860 seconds (7 allocations: 528 bytes)
  4.741454 seconds (152.92 k allocations: 9.926 MiB, 38.36% compilation time)
  3.517333 seconds (7 allocations: 512 bytes)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m10.3s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 11.285576 seconds (165.79 k allocations: 10.783 MiB, 14.53% compilation time)
  9.765663 seconds (7 allocations: 512 bytes)
 11.638367 seconds (154.66 k allocations: 10.078 MiB, 13.08% compilation time)
 10.069008 seconds (7 allocations: 512 bytes)
 11.415073 seconds (154.57 k allocations: 10.074 MiB, 0.70% gc time, 12.98% compilation time)
  9.784004 seconds (7 allocations: 512 bytes)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m05.9s
  1.104516 seconds (227.56 k allocations: 14.251 MiB, 96.36% compilation time)
  0.040289 seconds (7 allocations: 512 bytes)
  1.997059 seconds (235.80 k allocations: 15.068 MiB, 1.31% gc time, 98.09% compilation time)
  0.038391 seconds (7 allocations: 512 bytes)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  5.0s
  2.068857 seconds (289.77 k allocations: 17.787 MiB, 97.21% compilation time)
  0.057737 seconds (7 allocations: 512 bytes)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  2.7s

allknn   2%|▉                                            |  ETA: 0:03:37
allknn 100%|█████████████████████████████████████████████| Time: 0:00:04
ExhaustiveSearch allknn: 5.078995 seconds (1.81 M allocations: 110.522 MiB, 2.21% gc time, 99.95% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    1      1  5.3s
quantile(length.(hsp_knns), 0:0.1:1) = [2.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 5.0, 5.0, 6.0]
Test Summary: | Total  Time
HSP           |     0  5.4s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:21.102
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:21.843
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:24.744
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=5 ep=9 n=4 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:26.675
LOG n.size quantiles:[2.0, 2.0, 2.0, 2.0, 2.0]
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:27.123
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x0000000b, 0x0000000e, 0x0000003d, 0x00000041]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 1, 1, 7, 11, 7, 11, 14, 11, 2, 1, 5, 1, 2, 5, 5, 4, 7, 1, 14, 7, 5, 3, 4, 7, 2, 14, 3, 1, 1, 14, 14, 7, 14, 1, 4, 2, 2, 7, 7, 2, 2, 1, 3, 7, 6, 5, 14, 11, 5, 1, 4, 2, 5, 61, 1, 61, 2, 65, 2, 61, 2, 65, 65, 1, 61, 65, 7, 65, 14, 1, 3, 11, 14, 14, 3, 1, 1, 1, 2, 7, 1, 2, 6, 2, 65, 1, 5, 11, 2, 7, 14, 65, 1]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03246081, 0.068302274, 0.025580585, 0.0, 0.016263366, 0.03574884, 0.0, 0.0041419864, 0.05979854, 0.06434667, 0.026638329, 0.0050808787, 0.049551606, 0.023579955, 0.039823234, 0.022727966, 0.04854542, 0.043287933, 0.094234765, 0.054024816, 0.033644855, 0.054838, 0.003930807, 0.023542166, 0.075333476, 0.037149847, 0.056280673, 0.027753055, 0.06395167, 0.08402997, 0.00816381, 0.010761201, 0.03609878, 0.027166009, 0.030774713, 0.034011662, 0.08775306, 0.08686787, 0.02284807, 0.061442316, 0.019521832, 0.05033195, 0.08125287, 0.011749327, 0.047091246, 0.034899354, 0.09789801, 0.05880958, 0.01100558, 0.020544171, 0.049169242, 0.026368737, 0.05074215, 0.0, 0.017629087, 0.024067938, 0.07359195, 0.0, 0.07360673, 0.033194065, 0.02568245, 0.013284564, 0.02014321, 0.025553644, 0.0065392256, 0.025885582, 0.037466884, 0.012745261, 0.05602616, 0.035433352, 0.05735284, 0.023595273, 0.045698702, 0.03566259, 0.020029724, 0.018760562, 0.058921933, 0.02785939, 0.058885872, 0.0210312, 0.010736644, 0.053366065, 0.05342543, 0.030234277, 0.043393433, 0.031288147, 0.019553185, 0.038288474, 0.05643958, 0.068656385, 0.033792138, 0.04894781, 0.02787596]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  20.9s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:28.224
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:28.224
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.376
[ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.376
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.376
LOG add_vertex! sp=10 ep=10 n=9 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:31.376
LOG n.size quantiles:[3.0, 3.0, 3.0, 3.0, 3.0]
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.377
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.378
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.668
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.668
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x0000000b, 0x0000000e, 0x0000003d, 0x00000041]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 1, 1, 7, 11, 7, 11, 14, 11, 2, 1, 5, 1, 2, 5, 5, 4, 7, 1, 14, 7, 5, 3, 4, 7, 2, 14, 3, 1, 1, 14, 14, 7, 14, 1, 4, 2, 2, 7, 7, 2, 2, 1, 3, 7, 6, 5, 14, 11, 5, 1, 4, 2, 5, 61, 1, 61, 2, 65, 2, 61, 2, 5, 2, 1, 61, 5, 7, 5, 14, 1, 3, 11, 14, 14, 3, 1, 1, 1, 2, 7, 1, 2, 6, 2, 65, 1, 5, 11, 2, 7, 14, 65, 1]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03246081, 0.068302274, 0.025580585, 0.0, 0.016263366, 0.03574884, 0.0, 0.0041419864, 0.05979854, 0.06434667, 0.026638329, 0.0050808787, 0.049551606, 0.023579955, 0.039823234, 0.022727966, 0.04854542, 0.043287933, 0.094234765, 0.054024816, 0.033644855, 0.054838, 0.003930807, 0.023542166, 0.075333476, 0.037149847, 0.056280673, 0.027753055, 0.06395167, 0.08402997, 0.00816381, 0.010761201, 0.03609878, 0.027166009, 0.030774713, 0.034011662, 0.08775306, 0.08686787, 0.02284807, 0.061442316, 0.019521832, 0.05033195, 0.08125287, 0.011749327, 0.047091246, 0.034899354, 0.09789801, 0.05880958, 0.01100558, 0.020544171, 0.049169242, 0.026368737, 0.05074215, 0.0, 0.017629087, 0.024067938, 0.07359195, 0.0, 0.07360673, 0.033194065, 0.02568245, 0.062577605, 0.060837388, 0.025553644, 0.0065392256, 0.054804146, 0.037466884, 0.08222771, 0.05602616, 0.035433352, 0.05735284, 0.023595273, 0.045698702, 0.03566259, 0.020029724, 0.018760562, 0.058921933, 0.02785939, 0.058885872, 0.0210312, 0.010736644, 0.053366065, 0.05342543, 0.030234277, 0.043393433, 0.031288147, 0.019553185, 0.038288474, 0.05643958, 0.068656385, 0.033792138, 0.04894781, 0.02787596]
Test Summary:       | Pass  Total  Time
neardup small block |    3      3  3.5s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.761
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:31.761
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: 2026-02-15T17:07:31.762
[ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.762
[ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.762
[ Info: neardup> range: 65:80, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.762
[ Info: neardup> range: 81:96, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.762
[ Info: neardup> range: 97:100, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.762
[ Info: neardup> finished current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:31.762
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000041]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 5, 1, 2, 5, 5, 8, 12, 1, 9, 12, 5, 3, 4, 12, 12, 14, 3, 1, 1, 16, 14, 7, 14, 9, 4, 2, 16, 10, 7, 16, 2, 8, 9, 7, 6, 5, 9, 15, 5, 1, 4, 2, 5, 16, 1, 10, 2, 65, 2, 16, 2, 5, 2, 1, 16, 5, 12, 5, 14, 8, 3, 15, 14, 9, 3, 1, 8, 1, 16, 7, 1, 2, 6, 2, 65, 9, 5, 11, 2, 9, 14, 65, 9]
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, 0.06434667, 0.026638329, 0.0050808787, 0.049551606, 0.023579955, 0.039823234, 0.0107216835, 0.039362907, 0.043287933, 0.03859198, 0.03338653, 0.033644855, 0.054838, 0.003930807, 0.007884145, 0.074246526, 0.037149847, 0.056280673, 0.027753055, 0.06395167, 0.0756318, 0.00816381, 0.010761201, 0.03609878, 0.012681365, 0.030774713, 0.034011662, 0.02749914, 0.02139473, 0.02284807, 0.03265214, 0.019521832, 0.020314813, 0.03940326, 0.011749327, 0.047091246, 0.034899354, 0.08987403, 0.046535194, 0.01100558, 0.020544171, 0.049169242, 0.026368737, 0.05074215, 0.011494994, 0.017629087, 0.026928902, 0.07359195, 0.0, 0.07360673, 0.011757731, 0.02568245, 0.062577605, 0.060837388, 0.025553644, 0.0036008358, 0.054804146, 0.030346036, 0.08222771, 0.05602616, 0.009167135, 0.05735284, 0.019939959, 0.045698702, 0.0019461513, 0.020029724, 0.018760562, 0.017647088, 0.02785939, 0.055755496, 0.0210312, 0.010736644, 0.053366065, 0.05342543, 0.030234277, 0.043393433, 0.025568724, 0.019553185, 0.038288474, 0.05643958, 0.029752135, 0.033792138, 0.04894781, 0.013919413]
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: 2026-02-15T17:07:36.662
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=9 n=9 2026-02-15T17:07:37.317
[ Info: neardup> range: 17:32, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:38.494
[ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:38.495
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:38.495
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=9 ep=10 n=10 2026-02-15T17:07:38.495
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:38.501
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:38.501
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:39.709
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-15T17:07:39.709
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x0000000b, 0x0000000e, 0x0000003d, 0x00000041]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 1, 1, 7, 11, 7, 11, 14, 11, 2, 1, 5, 1, 2, 5, 5, 4, 7, 1, 14, 7, 5, 3, 4, 7, 2, 14, 3, 1, 1, 14, 14, 7, 14, 1, 4, 2, 2, 7, 7, 2, 2, 1, 3, 7, 6, 5, 14, 11, 5, 1, 4, 2, 5, 61, 1, 61, 2, 65, 2, 61, 2, 5, 2, 1, 61, 5, 7, 5, 14, 1, 3, 11, 14, 14, 3, 1, 1, 1, 2, 7, 1, 2, 6, 2, 65, 1, 5, 11, 2, 7, 14, 65, 1]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03246081, 0.068302274, 0.025580585, 0.0, 0.016263366, 0.03574884, 0.0, 0.0041419864, 0.05979854, 0.06434667, 0.026638329, 0.0050808787, 0.049551606, 0.023579955, 0.039823234, 0.022727966, 0.04854542, 0.043287933, 0.094234765, 0.054024816, 0.033644855, 0.054838, 0.003930807, 0.023542166, 0.075333476, 0.037149847, 0.056280673, 0.027753055, 0.06395167, 0.08402997, 0.00816381, 0.010761201, 0.03609878, 0.027166009, 0.030774713, 0.034011662, 0.08775306, 0.08686787, 0.02284807, 0.061442316, 0.019521832, 0.05033195, 0.08125287, 0.011749327, 0.047091246, 0.034899354, 0.09789801, 0.05880958, 0.01100558, 0.020544171, 0.049169242, 0.026368737, 0.05074215, 0.0, 0.017629087, 0.024067938, 0.07359195, 0.0, 0.07360673, 0.033194065, 0.02568245, 0.062577605, 0.060837388, 0.025553644, 0.0065392256, 0.054804146, 0.037466884, 0.08222771, 0.05602616, 0.035433352, 0.05735284, 0.023595273, 0.045698702, 0.03566259, 0.020029724, 0.018760562, 0.058921933, 0.02785939, 0.058885872, 0.0210312, 0.010736644, 0.053366065, 0.05342543, 0.030234277, 0.043393433, 0.031288147, 0.019553185, 0.038288474, 0.05643958, 0.068656385, 0.033792138, 0.04894781, 0.02787596]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  7.9s
computing farthest point 1, dmax: Inf, imax: 2, n: 30
computing farthest point 2, dmax: 1.250979, imax: 11, n: 30
computing farthest point 3, dmax: 0.97600687, imax: 27, n: 30
computing farthest point 4, dmax: 0.83734626, imax: 30, n: 30
computing farthest point 5, dmax: 0.8129251, imax: 5, n: 30
computing farthest point 6, dmax: 0.8115292, imax: 3, n: 30
computing farthest point 7, dmax: 0.6970329, imax: 29, n: 30
computing farthest point 8, dmax: 0.6069593, imax: 6, n: 30
computing farthest point 9, dmax: 0.5972518, imax: 24, n: 30
computing farthest point 10, dmax: 0.5852695, imax: 4, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  2.1s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.6s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:48.798
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:07:50.602
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=2, Δ=0.7990498, maxvisits=104) 2026-02-15T17:08:04.478
LOG n.size quantiles:[3.0, 3.0, 4.0, 4.0, 4.0]
(i, j, d) = (4, 397, -1.1920929f-7)
(i, j, d, :parallel) = (4, 397, -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 => 23.510732596, :exact => 0.992123255)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  25.0s
  8.086311 seconds (196.78 k allocations: 12.325 MiB, 22.56% compilation time)
SEARCH Exhaustive 1: 0.005538 seconds
SEARCH Exhaustive 2: 0.005209 seconds
SEARCH Exhaustive 3: 0.006029 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(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:08:34.327
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:08:36.221
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=14, Δ=1.025, maxvisits=196) 2026-02-15T17:08:47.450
LOG n.size quantiles:[2.0, 3.0, 4.0, 5.0, 5.0]
LOG add_vertex! sp=14895 ep=14899 n=14894 BeamSearch(bsize=8, Δ=1.155, maxvisits=408) 2026-02-15T17:08:48.450
LOG n.size quantiles:[3.0, 4.0, 5.0, 5.0, 5.0]
LOG add_vertex! sp=27610 ep=27614 n=27609 BeamSearch(bsize=6, Δ=1.1, maxvisits=500) 2026-02-15T17:08:49.450
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=37880 ep=37884 n=37879 BeamSearch(bsize=12, Δ=1.1, maxvisits=456) 2026-02-15T17:08:50.472
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=48645 ep=48649 n=48644 BeamSearch(bsize=12, Δ=1.1, maxvisits=456) 2026-02-15T17:08:51.472
LOG n.size quantiles:[5.0, 7.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=57390 ep=57394 n=57389 BeamSearch(bsize=11, Δ=1.06, maxvisits=446) 2026-02-15T17:08:52.472
LOG n.size quantiles:[4.0, 4.0, 6.0, 6.0, 6.0]
LOG add_vertex! sp=66930 ep=66934 n=66929 BeamSearch(bsize=11, Δ=1.06, maxvisits=446) 2026-02-15T17:08:53.472
LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=76475 ep=76479 n=76474 BeamSearch(bsize=11, Δ=1.06, maxvisits=446) 2026-02-15T17:08:54.472
LOG n.size quantiles:[4.0, 6.0, 8.0, 8.0, 10.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch(bsize=14, Δ=1.0, maxvisits=466) 2026-02-15T17:08:55.645
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 7.0]
LOG add_vertex! sp=94470 ep=94474 n=94469 BeamSearch(bsize=14, Δ=1.0, maxvisits=466) 2026-02-15T17:08:56.645
LOG n.size quantiles:[6.0, 7.0, 8.0, 9.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 92.0]
[ Info: minrecall: queries per second: 2986.93894040874, recall: 0.903
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.155, maxvisits=748))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 92.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.1287501, maxvisits=592)), 1000, 8)
[ Info: rebuild: queries per second: 14305.500632367504, recall: 0.901
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.1287501, maxvisits=592))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 32.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.1851876, maxvisits=834)), 1000, 8)
  0.628296 seconds (92.96 k allocations: 5.463 MiB, 86.51% compilation time)
[ Info: matrixhints: queries per second: 11741.849474444798, recall: 0.906625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.1851876, maxvisits=834))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 92.0]
  3.222802 seconds (158.42 k allocations: 10.370 MiB, 55.95% compilation time)
SEARCH Exhaustive 1: 0.002063 seconds
SEARCH Exhaustive 2: 0.002289 seconds
SEARCH Exhaustive 3: 0.002482 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(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:10:12.985
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-15T17:10:14.595
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=14, Δ=1.025, maxvisits=196) 2026-02-15T17:10:24.615
LOG n.size quantiles:[2.0, 3.0, 4.0, 5.0, 5.0]
LOG add_vertex! sp=16875 ep=16879 n=16874 BeamSearch(bsize=8, Δ=1.155, maxvisits=408) 2026-02-15T17:10:25.615
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=29355 ep=29359 n=29354 BeamSearch(bsize=6, Δ=1.1, maxvisits=500) 2026-02-15T17:10:26.615
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=41120 ep=41124 n=41119 BeamSearch(bsize=12, Δ=1.1, maxvisits=456) 2026-02-15T17:10:27.615
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 10.0]
LOG add_vertex! sp=52170 ep=52174 n=52169 BeamSearch(bsize=12, Δ=1.1, maxvisits=456) 2026-02-15T17:10:28.616
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=59875 ep=59879 n=59874 BeamSearch(bsize=11, Δ=1.06, maxvisits=446) 2026-02-15T17:10:29.798
LOG n.size quantiles:[5.0, 5.0, 7.0, 8.0, 10.0]
LOG add_vertex! sp=69925 ep=69929 n=69924 BeamSearch(bsize=11, Δ=1.06, maxvisits=446) 2026-02-15T17:10:30.798
LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 10.0]
LOG add_vertex! sp=79595 ep=79599 n=79594 BeamSearch(bsize=11, Δ=1.06, maxvisits=446) 2026-02-15T17:10:31.798
LOG n.size quantiles:[4.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=88405 ep=88409 n=88404 BeamSearch(bsize=14, Δ=1.0, maxvisits=466) 2026-02-15T17:10:32.798
LOG n.size quantiles:[5.0, 5.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=98045 ep=98049 n=98044 BeamSearch(bsize=14, Δ=1.0, maxvisits=466) 2026-02-15T17:10:33.799
LOG n.size quantiles:[5.0, 6.0, 8.0, 9.0, 13.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 92.0]
[ Info: minrecall: queries per second: 2970.8666742683226, recall: 0.903
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.155, maxvisits=748))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 92.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.1287501, maxvisits=592)), 1000, 8)
[ Info: rebuild: queries per second: 16020.29065933749, recall: 0.901
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.1287501, maxvisits=592))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 32.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.1851876, maxvisits=834)), 1000, 8)
  0.634355 seconds (94.04 k allocations: 5.615 MiB, 88.45% compilation time)
[ Info: matrixhints: queries per second: 13070.448449308273, recall: 0.906625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.1851876, maxvisits=834))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 15.0, 18.0, 23.0, 92.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  3m06.8s
     Testing SimilaritySearch tests passed 

Testing completed after 706.72s

PkgEval succeeded after 771.05s