Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1688 (ee54f91d68*) started at 2026-02-10T04:18:40.904


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

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

Set-up completed after 11.53s


################################################################################
# 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 4.24s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   3813.7 ms  ✓ SearchModels
   6967.2 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 11 seconds. 81 already precompiled.

Precompilation completed after 30.55s


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

     Testing SimilaritySearch
      Status `/tmp/jl_j6FHQd/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_j6FHQd/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 v3.5.4+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 |   57     57  16.3s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  3.7s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.9s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  5.698422 seconds (399.06 k allocations: 24.587 MiB, 33.78% compilation time)
  4.158692 seconds (7 allocations: 512 bytes)
  5.787412 seconds (254.63 k allocations: 16.010 MiB, 31.48% compilation time)
  3.973799 seconds (7 allocations: 512 bytes)
  5.731621 seconds (238.56 k allocations: 15.120 MiB, 32.23% compilation time)
  3.703437 seconds (7 allocations: 512 bytes)
  5.386206 seconds (234.13 k allocations: 14.865 MiB, 1.56% gc time, 33.71% compilation time)
  3.610276 seconds (7 allocations: 512 bytes)
 16.521606 seconds (246.34 k allocations: 15.516 MiB, 9.86% compilation time)
 14.499842 seconds (7 allocations: 512 bytes)
 27.378600 seconds (7 allocations: 512 bytes)
 26.814569 seconds (7 allocations: 512 bytes)
 20.037586 seconds (509.65 k allocations: 31.381 MiB, 8.47% compilation time)
 17.918041 seconds (7 allocations: 512 bytes)
 17.574250 seconds (405.34 k allocations: 25.376 MiB, 0.36% gc time, 7.63% compilation time)
 16.307474 seconds (7 allocations: 512 bytes)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m20.5s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  4.190893 seconds (168.62 k allocations: 11.248 MiB, 1.64% gc time, 40.82% compilation time)
  2.579018 seconds (7 allocations: 512 bytes)
 30.214441 seconds (209.48 k allocations: 13.560 MiB, 5.93% compilation time)
 28.732054 seconds (7 allocations: 528 bytes)
 27.612801 seconds (7 allocations: 528 bytes)
 28.980019 seconds (7 allocations: 528 bytes)
  5.317726 seconds (152.56 k allocations: 9.903 MiB, 32.14% compilation time)
  3.692364 seconds (7 allocations: 512 bytes)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m13.4s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 11.111837 seconds (165.36 k allocations: 10.757 MiB, 12.44% compilation time)
 10.023705 seconds (7 allocations: 512 bytes)
 11.246671 seconds (154.30 k allocations: 10.055 MiB, 14.04% compilation time)
  9.724579 seconds (7 allocations: 512 bytes)
 11.509884 seconds (154.21 k allocations: 10.051 MiB, 13.42% compilation time)
  9.960092 seconds (7 allocations: 512 bytes)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m05.7s
  1.185296 seconds (226.83 k allocations: 14.203 MiB, 96.73% compilation time)
  0.038478 seconds (7 allocations: 512 bytes)
  1.902544 seconds (234.93 k allocations: 15.013 MiB, 97.52% compilation time)
  0.048088 seconds (7 allocations: 512 bytes)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  5.1s
  1.912088 seconds (288.31 k allocations: 17.697 MiB, 1.15% gc time, 97.52% compilation time)
  0.059740 seconds (7 allocations: 512 bytes)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  2.6s

allknn   2%|▉                                            |  ETA: 0:03:32
allknn 100%|█████████████████████████████████████████████| Time: 0:00:04
ExhaustiveSearch allknn: 5.013605 seconds (1.80 M allocations: 110.033 MiB, 0.72% gc time, 99.96% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    1      1  5.2s
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  4.9s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:22.816
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-10T04:27:23.571
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) 2026-02-10T04:27:26.600
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) 2026-02-10T04:27:28.492
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: 2026-02-10T04:27:28.939
D.map = UInt32[0x00000001, 0x00000003, 0x00000006, 0x0000000d, 0x0000001a, 0x0000001d, 0x00000021, 0x00000026, 0x0000003f, 0x00000041, 0x00000051]
D.nn = Int32[1, 1, 3, 1, 3, 6, 3, 1, 3, 6, 1, 3, 13, 6, 13, 6, 1, 13, 13, 6, 3, 13, 3, 6, 13, 26, 6, 3, 29, 3, 6, 13, 33, 26, 1, 26, 13, 38, 1, 1, 3, 33, 29, 33, 13, 1, 1, 29, 3, 1, 29, 1, 3, 3, 13, 3, 1, 1, 29, 26, 29, 6, 63, 3, 65, 26, 6, 6, 13, 63, 29, 65, 26, 3, 13, 1, 38, 13, 65, 6, 81, 29, 33, 6, 29, 6, 13, 3, 1, 29, 63, 81, 3, 26, 63, 13, 13, 3, 1, 29]
D.dist = Float32[0.0, 0.08760345, 0.0, 0.08413553, 0.06768513, 0.0, 0.04992515, 0.010093391, 0.022837639, 0.04922837, 0.038600743, 0.033040643, 0.0, 0.02257669, 0.09799492, 0.081245065, 0.025685012, 0.03528911, 0.028491557, 0.029711008, 0.022977412, 0.0068930387, 0.025635958, 0.06626886, 0.041803002, 0.0, 0.09530264, 0.05997938, 0.0, 0.03374642, 0.05414605, 0.0043727756, 0.0, 0.055583477, 0.018042445, 0.08811861, 0.07158053, 0.0, 0.019595563, 0.02816999, 0.005896449, 0.06065619, 0.026641488, 0.01799643, 0.037272036, 0.0427441, 0.05345863, 0.028960168, 0.018541157, 0.05710572, 0.03330809, 0.045390606, 0.09219867, 0.020471573, 0.037344873, 0.016843915, 0.013934195, 0.04100591, 0.0052962303, 0.012221694, 0.04409361, 0.060159206, 0.0, 0.025313854, 0.0, 0.030286133, 0.030404866, 0.061503053, 0.033174157, 0.09190261, 0.037376225, 0.042771876, 0.07736951, 0.042601228, 0.0050098896, 0.009212971, 0.006582856, 0.06139052, 0.04130566, 0.020214975, 0.0, 0.018310249, 0.032878637, 0.02904439, 0.08179039, 0.008676529, 0.007476449, 0.006223023, 0.02581942, 0.06506908, 0.07537991, 0.018767357, 0.046954572, 0.025684953, 0.03836894, 0.007631004, 0.05922109, 0.00268054, 0.042244554, 0.07021892]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  22.4s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:30.220
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-10T04:27:30.220
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: 2026-02-10T04:27:33.439
LOG add_vertex! sp=5 ep=6 n=4 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-10T04:27:33.439
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
[ Info: neardup> range: 33:48, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.439
[ Info: neardup> range: 49:64, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.439
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.439
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.440
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.729
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.729
D.map = UInt32[0x00000001, 0x00000003, 0x00000006, 0x0000000d, 0x0000001a, 0x0000001d, 0x00000021, 0x00000026, 0x0000003f, 0x00000041, 0x00000051]
D.nn = Int32[1, 1, 3, 1, 3, 6, 3, 1, 3, 6, 1, 3, 13, 6, 13, 6, 1, 13, 13, 6, 3, 13, 3, 6, 13, 26, 6, 3, 29, 3, 6, 13, 33, 26, 1, 26, 13, 38, 1, 1, 3, 1, 29, 33, 13, 1, 1, 29, 3, 1, 29, 1, 3, 3, 13, 3, 1, 1, 29, 26, 29, 6, 63, 3, 65, 26, 6, 6, 13, 63, 29, 1, 26, 3, 13, 1, 38, 13, 1, 6, 81, 29, 33, 6, 29, 6, 13, 3, 1, 29, 63, 13, 3, 26, 63, 13, 13, 3, 1, 29]
D.dist = Float32[0.0, 0.08760345, 0.0, 0.08413553, 0.06768513, 0.0, 0.04992515, 0.010093391, 0.022837639, 0.04922837, 0.038600743, 0.033040643, 0.0, 0.02257669, 0.09799492, 0.081245065, 0.025685012, 0.03528911, 0.028491557, 0.029711008, 0.022977412, 0.0068930387, 0.025635958, 0.06626886, 0.041803002, 0.0, 0.09530264, 0.05997938, 0.0, 0.03374642, 0.05414605, 0.0043727756, 0.0, 0.055583477, 0.018042445, 0.08811861, 0.07158053, 0.0, 0.019595563, 0.02816999, 0.005896449, 0.06658864, 0.026641488, 0.01799643, 0.037272036, 0.0427441, 0.05345863, 0.028960168, 0.018541157, 0.05710572, 0.03330809, 0.045390606, 0.09219867, 0.020471573, 0.037344873, 0.016843915, 0.013934195, 0.04100591, 0.0052962303, 0.012221694, 0.04409361, 0.060159206, 0.0, 0.025313854, 0.0, 0.030286133, 0.030404866, 0.061503053, 0.033174157, 0.09190261, 0.037376225, 0.06237656, 0.07736951, 0.042601228, 0.0050098896, 0.009212971, 0.006582856, 0.06139052, 0.057813644, 0.020214975, 0.0, 0.018310249, 0.032878637, 0.02904439, 0.08179039, 0.008676529, 0.007476449, 0.006223023, 0.02581942, 0.06506908, 0.07537991, 0.09161174, 0.046954572, 0.025684953, 0.03836894, 0.007631004, 0.05922109, 0.00268054, 0.042244554, 0.07021892]
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: 2026-02-10T04:27:33.820
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-10T04:27:33.820
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: 2026-02-10T04:27:33.820
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.821
[ Info: neardup> range: 49:64, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.821
[ Info: neardup> range: 65:80, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.821
[ Info: neardup> range: 81:96, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.821
[ Info: neardup> range: 97:100, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.821
[ Info: neardup> finished current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:33.821
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000001a, 0x00000021, 0x00000026, 0x0000002c]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 8, 13, 5, 14, 3, 13, 3, 14, 11, 26, 5, 9, 4, 11, 16, 13, 33, 26, 11, 26, 5, 38, 1, 4, 3, 4, 2, 44, 13, 2, 1, 4, 9, 15, 4, 4, 7, 11, 13, 3, 8, 11, 4, 26, 4, 10, 15, 9, 44, 26, 4, 16, 13, 2, 2, 8, 15, 5, 13, 8, 38, 11, 44, 14, 7, 4, 33, 4, 12, 6, 13, 3, 1, 2, 15, 7, 5, 26, 1, 13, 11, 3, 11, 2]
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, 0.004003465, 0.03528911, 0.012125969, 0.026059926, 0.022977412, 0.0068930387, 0.025635958, 0.018829107, 0.008237779, 0.0, 0.034350276, 0.01366657, 0.06817955, 0.0106134415, 0.014634132, 0.0043727756, 0.0, 0.055583477, 0.0060117245, 0.08811861, 0.01325047, 0.0, 0.019595563, 0.018054724, 0.005896449, 0.048210144, 0.07139361, 0.0, 0.037272036, 0.02265662, 0.05345863, 0.013931036, 0.01531893, 0.040570974, 0.048892796, 0.0070340633, 0.033596158, 0.020086706, 0.037344873, 0.016843915, 0.0012995601, 0.0011560917, 0.07596165, 0.012221694, 0.049833834, 0.0063440204, 0.025399268, 0.016808987, 0.044436812, 0.030286133, 0.008228958, 0.006216228, 0.033174157, 0.014634728, 0.044325292, 0.06025392, 0.03936106, 0.013899684, 0.0050098896, 0.00034356117, 0.006582856, 0.012265146, 0.04713142, 0.0155107975, 0.07165122, 0.019334197, 0.032878637, 0.0071818233, 0.02444613, 0.008676529, 0.007476449, 0.006223023, 0.02581942, 0.029761195, 0.03654176, 0.075445294, 0.0045108795, 0.025684953, 0.061594725, 0.007631004, 0.007062018, 0.00268054, 0.0118941665, 0.044142544]
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: 2026-02-10T04:27:37.171
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=4 n=4 2026-02-10T04:27:37.591
[ Info: neardup> range: 17:32, current elements: 4, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:38.866
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=4 ep=6 n=6 2026-02-10T04:27:38.866
[ Info: neardup> range: 33:48, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:38.872
[ Info: neardup> range: 49:64, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:38.872
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:38.872
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:38.872
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:40.136
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-10T04:27:40.137
D.map = UInt32[0x00000001, 0x00000003, 0x00000006, 0x0000000d, 0x0000001a, 0x0000001d, 0x00000021, 0x00000026, 0x0000003f, 0x00000041, 0x00000051]
D.nn = Int32[1, 1, 3, 1, 3, 6, 3, 1, 3, 6, 1, 3, 13, 6, 13, 6, 1, 13, 13, 6, 3, 13, 3, 6, 13, 26, 6, 3, 29, 3, 6, 13, 33, 26, 1, 26, 13, 38, 1, 1, 3, 1, 29, 33, 13, 1, 1, 29, 3, 1, 29, 1, 3, 3, 13, 3, 1, 1, 29, 26, 29, 6, 63, 3, 65, 26, 6, 6, 13, 63, 29, 1, 26, 3, 13, 1, 38, 13, 1, 6, 81, 29, 33, 6, 29, 6, 13, 3, 1, 29, 63, 13, 3, 26, 63, 13, 13, 3, 1, 29]
D.dist = Float32[0.0, 0.08760345, 0.0, 0.08413553, 0.06768513, 0.0, 0.04992515, 0.010093391, 0.022837639, 0.04922837, 0.038600743, 0.033040643, 0.0, 0.02257669, 0.09799492, 0.081245065, 0.025685012, 0.03528911, 0.028491557, 0.029711008, 0.022977412, 0.0068930387, 0.025635958, 0.06626886, 0.041803002, 0.0, 0.09530264, 0.05997938, 0.0, 0.03374642, 0.05414605, 0.0043727756, 0.0, 0.055583477, 0.018042445, 0.08811861, 0.07158053, 0.0, 0.019595563, 0.02816999, 0.005896449, 0.06658864, 0.026641488, 0.01799643, 0.037272036, 0.0427441, 0.05345863, 0.028960168, 0.018541157, 0.05710572, 0.03330809, 0.045390606, 0.09219867, 0.020471573, 0.037344873, 0.016843915, 0.013934195, 0.04100591, 0.0052962303, 0.012221694, 0.04409361, 0.060159206, 0.0, 0.025313854, 0.0, 0.030286133, 0.030404866, 0.061503053, 0.033174157, 0.09190261, 0.037376225, 0.06237656, 0.07736951, 0.042601228, 0.0050098896, 0.009212971, 0.006582856, 0.06139052, 0.057813644, 0.020214975, 0.0, 0.018310249, 0.032878637, 0.02904439, 0.08179039, 0.008676529, 0.007476449, 0.006223023, 0.02581942, 0.06506908, 0.07537991, 0.09161174, 0.046954572, 0.025684953, 0.03836894, 0.007631004, 0.05922109, 0.00268054, 0.042244554, 0.07021892]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  6.3s
computing farthest point 1, dmax: Inf, imax: 16, n: 30
computing farthest point 2, dmax: 1.4579216, imax: 15, n: 30
computing farthest point 3, dmax: 1.0819818, imax: 7, n: 30
computing farthest point 4, dmax: 0.9643022, imax: 27, n: 30
computing farthest point 5, dmax: 0.88460594, imax: 11, n: 30
computing farthest point 6, dmax: 0.7887171, imax: 26, n: 30
computing farthest point 7, dmax: 0.7303171, imax: 29, n: 30
computing farthest point 8, dmax: 0.6518796, imax: 28, n: 30
computing farthest point 9, dmax: 0.6046554, imax: 22, n: 30
computing farthest point 10, dmax: 0.60362595, imax: 23, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  2.1s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.7s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-10T04:27:49.961
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) 2026-02-10T04:27:51.634
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=0.975, maxvisits=104) 2026-02-10T04:28:06.286
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 5.0]
(i, j, d) = (12, 788, -1.1920929f-7)
(i, j, d, :parallel) = (12, 788, -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 => 24.613164313, :exact => 1.026079019)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  26.1s
  7.177805 seconds (196.06 k allocations: 12.281 MiB, 24.18% compilation time)
SEARCH Exhaustive 1: 0.004338 seconds
SEARCH Exhaustive 2: 0.004497 seconds
SEARCH Exhaustive 3: 0.005151 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) 2026-02-10T04:28:34.919
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) 2026-02-10T04:28:36.789
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=6, Δ=1.1, maxvisits=200) 2026-02-10T04:28:47.941
LOG n.size quantiles:[2.0, 4.0, 4.0, 5.0, 6.0]
LOG add_vertex! sp=17260 ep=17264 n=17259 BeamSearch(bsize=6, Δ=1.05, maxvisits=360) 2026-02-10T04:28:48.941
LOG n.size quantiles:[5.0, 7.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=30095 ep=30099 n=30094 BeamSearch(bsize=10, Δ=1.155, maxvisits=444) 2026-02-10T04:28:49.941
LOG n.size quantiles:[4.0, 5.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=41080 ep=41084 n=41079 BeamSearch(bsize=8, Δ=1.07625, maxvisits=484) 2026-02-10T04:28:50.941
LOG n.size quantiles:[6.0, 8.0, 8.0, 9.0, 9.0]
LOG add_vertex! sp=52410 ep=52414 n=52409 BeamSearch(bsize=8, Δ=1.07625, maxvisits=484) 2026-02-10T04:28:51.942
LOG n.size quantiles:[3.0, 5.0, 6.0, 8.0, 8.0]
LOG add_vertex! sp=61105 ep=61109 n=61104 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:28:52.942
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=70625 ep=70629 n=70624 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:28:53.942
LOG n.size quantiles:[7.0, 8.0, 8.0, 8.0, 10.0]
LOG add_vertex! sp=79915 ep=79919 n=79914 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:28:54.943
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=87065 ep=87069 n=87064 BeamSearch(bsize=10, Δ=1.0, maxvisits=468) 2026-02-10T04:28:55.943
LOG n.size quantiles:[5.0, 7.0, 8.0, 8.0, 10.0]
LOG add_vertex! sp=96130 ep=96134 n=96129 BeamSearch(bsize=10, Δ=1.0, maxvisits=468) 2026-02-10T04:28:56.943
LOG n.size quantiles:[4.0, 4.0, 5.0, 6.0, 7.0]
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, 17.0, 23.0, 88.0]
[ Info: minrecall: queries per second: 3394.659578581257, recall: 0.901625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.155, maxvisits=734))
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, 17.0, 23.0, 88.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=600)), 1000, 8)
[ Info: rebuild: queries per second: 14953.842125051026, recall: 0.90325
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=600))
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=8, Δ=1.14, maxvisits=746)), 1000, 8)
  0.655470 seconds (91.86 k allocations: 5.374 MiB, 88.61% compilation time)
[ Info: matrixhints: queries per second: 13564.846007052609, recall: 0.899625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.14, maxvisits=746))
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, 17.0, 23.0, 88.0]
  3.058088 seconds (158.07 k allocations: 10.347 MiB, 56.69% compilation time)
SEARCH Exhaustive 1: 0.001367 seconds
SEARCH Exhaustive 2: 0.001452 seconds
SEARCH Exhaustive 3: 0.001699 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) 2026-02-10T04:30:12.831
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) 2026-02-10T04:30:14.624
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=6, Δ=1.1, maxvisits=200) 2026-02-10T04:30:25.131
LOG n.size quantiles:[2.0, 4.0, 4.0, 5.0, 6.0]
LOG add_vertex! sp=20765 ep=20769 n=20764 BeamSearch(bsize=6, Δ=1.05, maxvisits=360) 2026-02-10T04:30:26.131
LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=34745 ep=34749 n=34744 BeamSearch(bsize=10, Δ=1.155, maxvisits=444) 2026-02-10T04:30:27.131
LOG n.size quantiles:[4.0, 5.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=47140 ep=47144 n=47139 BeamSearch(bsize=8, Δ=1.07625, maxvisits=484) 2026-02-10T04:30:28.197
LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=58360 ep=58364 n=58359 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:30:29.197
LOG n.size quantiles:[3.0, 4.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=68730 ep=68734 n=68729 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:30:30.197
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=78860 ep=78864 n=78859 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:30:31.197
LOG n.size quantiles:[7.0, 7.0, 9.0, 9.0, 10.0]
LOG add_vertex! sp=85040 ep=85044 n=85039 BeamSearch(bsize=4, Δ=1.157625, maxvisits=410) 2026-02-10T04:30:32.197
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=94770 ep=94774 n=94769 BeamSearch(bsize=10, Δ=1.0, maxvisits=468) 2026-02-10T04:30:33.198
LOG n.size quantiles:[4.0, 6.0, 7.0, 8.0, 8.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 17.0, 23.0, 88.0]
[ Info: minrecall: queries per second: 3008.8302397669117, recall: 0.901625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.155, maxvisits=734))
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, 17.0, 23.0, 88.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=600)), 1000, 8)
[ Info: rebuild: queries per second: 17653.299576458507, recall: 0.90325
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=600))
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=8, Δ=1.14, maxvisits=746)), 1000, 8)
  0.679113 seconds (92.94 k allocations: 5.528 MiB, 88.96% compilation time)
[ Info: matrixhints: queries per second: 14621.430261874788, recall: 0.899625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.14, maxvisits=746))
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, 17.0, 23.0, 88.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  3m04.1s
     Testing SimilaritySearch tests passed 

Testing completed after 702.64s

PkgEval succeeded after 761.66s