Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1621 (4d04bb6b3b*) started at 2026-01-28T00:56:56.374


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

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

Set-up completed after 10.31s


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

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [053f045d] + SimilaritySearch v0.13.7
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [7d9f7c33] + Accessors v0.1.43
  [79e6a3ab] + Adapt v4.4.0
  [4fba245c] + ArrayInterface v7.22.0
  [62783981] + BitTwiddlingConvenienceFunctions v0.1.6
  [2a0fbf3d] + CPUSummary v0.2.7
  [fb6a15b2] + CloseOpenIntervals v0.1.13
  [f70d9fcc] + CommonWorldInvalidations v1.0.0
  [34da2185] + Compat v4.18.1
  [a33af91c] + CompositionsBase v0.1.2
  [187b0558] + ConstructionBase v1.6.0
  [adafc99b] + CpuId v0.3.1
  [9a962f9c] + DataAPI v1.16.0
⌅ [864edb3b] + DataStructures v0.18.22
  [b4f34e82] + Distances v0.10.12
  [ffbed154] + DocStringExtensions v0.9.5
  [615f187c] + IfElse v0.1.1
  [3587e190] + InverseFunctions v0.1.17
  [92d709cd] + IrrationalConstants v0.2.6
  [10f19ff3] + LayoutPointers v0.1.17
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [1914dd2f] + MacroTools v0.5.16
  [d125e4d3] + ManualMemory v0.1.8
  [e1d29d7a] + Missings v1.2.0
  [bac558e1] + OrderedCollections v1.8.1
  [d96e819e] + Parameters v0.12.3
  [f517fe37] + Polyester v0.7.18
  [1d0040c9] + PolyesterWeave v0.2.2
  [aea7be01] + PrecompileTools v1.3.3
  [21216c6a] + Preferences v1.5.1
  [92933f4c] + ProgressMeter v1.11.0
  [ae029012] + Requires v1.3.1
  [94e857df] + SIMDTypes v0.1.0
  [431bcebd] + SciMLPublic v1.0.1
⌅ [0e966ebe] + SearchModels v0.4.1
  [053f045d] + SimilaritySearch v0.13.7
  [a2af1166] + SortingAlgorithms v1.2.2
  [aedffcd0] + Static v1.3.1
  [0d7ed370] + StaticArrayInterface v1.8.0
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
⌅ [2913bbd2] + StatsBase v0.33.21
  [7792a7ef] + StrideArraysCore v0.5.8
  [8290d209] + ThreadingUtilities v0.5.5
  [3a884ed6] + UnPack v1.0.2
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8ba89e20] + Distributed v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.13.0
  [d6f4376e] + Markdown v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v1.0.0
  [9e88b42a] + Serialization v1.11.0
  [6462fe0b] + Sockets v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [f489334b] + StyledStrings v1.13.0
  [fa267f1f] + TOML v1.0.3
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1
  [4536629a] + OpenBLAS_jll v0.3.30+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [8e850b90] + libblastrampoline_jll v5.15.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 4.16s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   5210.1 ms  ✓ StatsBase
   5265.1 ms  ✓ SearchModels
   9804.8 ms  ✓ SimilaritySearch
  3 dependencies successfully precompiled in 21 seconds. 87 already precompiled.

Precompilation completed after 37.7s


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

     Testing SimilaritySearch
      Status `/tmp/jl_0tBRg8/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_0tBRg8/Manifest.toml`
  [7d9f7c33] Accessors v0.1.43
  [79e6a3ab] Adapt v4.4.0
  [4c88cf16] Aqua v0.8.14
  [4fba245c] ArrayInterface v7.22.0
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [2a0fbf3d] CPUSummary v0.2.7
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.18.1
  [a33af91c] CompositionsBase v0.1.2
  [187b0558] ConstructionBase v1.6.0
  [adafc99b] CpuId v0.3.1
  [9a962f9c] DataAPI v1.16.0
⌅ [864edb3b] DataStructures v0.18.22
  [b4f34e82] Distances v0.10.12
  [ffbed154] DocStringExtensions v0.9.5
  [615f187c] IfElse v0.1.1
  [3587e190] InverseFunctions v0.1.17
  [92d709cd] IrrationalConstants v0.2.6
  [10f19ff3] LayoutPointers v0.1.17
  [2ab3a3ac] LogExpFunctions v0.3.29
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [e1d29d7a] Missings v1.2.0
  [bac558e1] OrderedCollections v1.8.1
  [d96e819e] Parameters v0.12.3
  [f517fe37] Polyester v0.7.18
  [1d0040c9] PolyesterWeave v0.2.2
  [aea7be01] PrecompileTools v1.3.3
  [21216c6a] Preferences v1.5.1
  [92933f4c] ProgressMeter v1.11.0
  [ae029012] Requires v1.3.1
  [94e857df] SIMDTypes v0.1.0
  [431bcebd] SciMLPublic v1.0.1
⌅ [0e966ebe] SearchModels v0.4.1
  [053f045d] SimilaritySearch v0.13.7
  [a2af1166] SortingAlgorithms v1.2.2
  [aedffcd0] Static v1.3.1
  [0d7ed370] StaticArrayInterface v1.8.0
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
⌅ [2913bbd2] StatsBase v0.33.21
  [7792a7ef] StrideArraysCore v0.5.8
  [8290d209] ThreadingUtilities v0.5.5
  [3a884ed6] UnPack v1.0.2
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0
  [b27032c2] LibCURL v1.0.0
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.14.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v1.0.0
  [9e88b42a] Serialization v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [f489334b] StyledStrings v1.13.0
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.18.0+0
  [e37daf67] LibGit2_jll v1.9.2+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.12.2
  [4536629a] OpenBLAS_jll v0.3.30+0
  [458c3c95] OpenSSL_jll v3.5.4+0
  [efcefdf7] PCRE2_jll v10.47.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [3161d3a3] Zstd_jll v1.5.7+1
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.68.0+1
  [3f19e933] p7zip_jll v17.7.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Test Summary:              | Pass  Total   Time
test database abstractions |   56     56  11.7s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  3.8s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.5s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  4.810731 seconds (1000 allocations: 78.125 KiB)
  5.848676 seconds (1000 allocations: 78.125 KiB)
  4.104595 seconds (1000 allocations: 78.125 KiB)
  4.383805 seconds (1000 allocations: 78.125 KiB)
  4.128808 seconds (1000 allocations: 78.125 KiB)
  4.041572 seconds (1000 allocations: 78.125 KiB)
  4.188686 seconds (1000 allocations: 78.125 KiB)
  4.109502 seconds (1000 allocations: 78.125 KiB)
 14.182091 seconds (1000 allocations: 78.125 KiB)
 14.241827 seconds (1000 allocations: 78.125 KiB)
 27.516700 seconds (1000 allocations: 78.125 KiB)
 27.389374 seconds (1000 allocations: 78.125 KiB)
 19.453442 seconds (6.23 k allocations: 358.094 KiB)
 19.567379 seconds (1000 allocations: 78.125 KiB)
 16.813883 seconds (1.00 k allocations: 78.141 KiB)
 16.680245 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m21.5s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.190092 seconds (1000 allocations: 78.125 KiB)
  3.294536 seconds (1000 allocations: 78.125 KiB)
 28.106567 seconds (1000 allocations: 78.125 KiB)
 28.181463 seconds (1000 allocations: 78.125 KiB)
 28.101419 seconds (1000 allocations: 78.125 KiB)
 28.095437 seconds (1000 allocations: 78.125 KiB)
  4.243211 seconds (1000 allocations: 78.125 KiB)
  4.269703 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m11.8s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 10.328233 seconds (1000 allocations: 78.125 KiB)
 10.153988 seconds (1000 allocations: 78.125 KiB)
 10.415639 seconds (1000 allocations: 78.125 KiB)
 10.300608 seconds (1000 allocations: 78.125 KiB)
 10.463695 seconds (1000 allocations: 78.125 KiB)
 10.252205 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m04.8s
  0.044213 seconds (1.00 k allocations: 78.141 KiB)
  0.050656 seconds (1000 allocations: 78.125 KiB)
  0.042120 seconds (1000 allocations: 78.125 KiB)
  0.042951 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  2.9s
  0.052557 seconds (1000 allocations: 78.125 KiB)
  0.052481 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.4s
ExhaustiveSearch allknn: 4.288450 seconds (1.99 M allocations: 119.536 MiB, 2.33% gc time, 99.97% compilation time)
ParallelExhaustiveSearch allknn: 1.206498 seconds (527.97 k allocations: 28.785 MiB, 99.89% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  6.0s
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  3.0s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:33.477
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-28T01:05:33.724
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) 2026-01-28T01:05:35.140
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
[ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:35.527
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x0000000d, 0x00000016, 0x0000001a, 0x0000002c]
D.nn = Int32[1, 2, 3, 4, 5, 4, 1, 3, 3, 4, 4, 1, 13, 5, 1, 3, 1, 4, 5, 1, 1, 22, 2, 5, 1, 26, 1, 13, 2, 13, 4, 4, 2, 1, 4, 22, 4, 4, 4, 22, 5, 4, 1, 44, 5, 4, 4, 4, 5, 1, 3, 2, 1, 26, 26, 4, 22, 44, 26, 26, 4, 26, 4, 13, 22, 44, 1, 44, 26, 4, 4, 2, 26, 4, 4, 2, 1, 2, 1, 1, 4, 22, 1, 3, 5, 1, 4, 4, 4, 2, 13, 26, 1, 44, 1, 2, 1, 1, 1, 22]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.06429905, 0.067756414, 0.026958287, 0.08733839, 0.08474219, 0.05269581, 0.017104149, 0.0, 0.06508267, 0.00881201, 0.053682268, 0.069702625, 0.02358538, 0.048232853, 0.014216781, 0.06212282, 0.0, 0.040896595, 0.036250412, 0.0754118, 0.0, 0.07182902, 0.056686163, 0.03390205, 0.03703606, 0.030156255, 0.013335168, 0.06242585, 0.053959787, 0.00032669306, 0.07100618, 0.04260385, 0.04119873, 0.014798045, 0.07948828, 0.022850394, 0.015389144, 0.06537473, 0.0, 0.020558, 0.0147407055, 0.024584293, 0.042943895, 0.037365377, 0.010082781, 0.01734531, 0.013758004, 0.063434005, 0.015683472, 0.06713873, 0.03570056, 0.06191671, 0.036923587, 0.08552998, 0.09596342, 0.03491491, 0.014481962, 0.07607061, 0.09089303, 0.044195414, 0.019605517, 0.038737833, 0.03937453, 0.07886726, 0.017585933, 0.058259606, 0.016803026, 0.052642763, 0.033255637, 0.012968183, 0.03909421, 0.049857914, 0.03886944, 0.03360915, 0.04992181, 0.007153809, 0.06810176, 0.04492891, 0.053261876, 0.030195653, 0.02363491, 0.07370812, 0.0401541, 0.017834485, 0.027286708, 0.08320671, 0.0077682137, 0.0318982, 0.03273022, 0.046396255, 0.033866942, 0.016702652, 0.0046455264, 0.050757885, 0.027853608]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  18.8s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.720
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-28T01:05:36.720
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
[ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
[ Info: neardup> range: 97:100, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
[ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.721
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x0000000d, 0x00000016, 0x0000001a, 0x0000002c]
D.nn = Int32[1, 2, 3, 4, 5, 4, 1, 3, 3, 4, 4, 1, 13, 5, 1, 3, 1, 4, 5, 1, 1, 22, 2, 5, 1, 26, 1, 13, 2, 13, 4, 4, 2, 1, 4, 22, 4, 4, 4, 22, 5, 4, 1, 44, 5, 4, 4, 4, 5, 1, 3, 2, 1, 26, 26, 4, 22, 44, 26, 26, 4, 26, 4, 13, 22, 44, 1, 44, 26, 4, 4, 2, 26, 4, 4, 2, 1, 2, 1, 1, 4, 22, 1, 3, 5, 1, 4, 4, 4, 2, 13, 26, 1, 44, 1, 2, 1, 1, 1, 22]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.06429905, 0.067756414, 0.026958287, 0.08733839, 0.08474219, 0.05269581, 0.017104149, 0.0, 0.06508267, 0.00881201, 0.053682268, 0.069702625, 0.02358538, 0.048232853, 0.014216781, 0.06212282, 0.0, 0.040896595, 0.036250412, 0.0754118, 0.0, 0.07182902, 0.056686163, 0.03390205, 0.03703606, 0.030156255, 0.013335168, 0.06242585, 0.053959787, 0.00032669306, 0.07100618, 0.04260385, 0.04119873, 0.014798045, 0.07948828, 0.022850394, 0.015389144, 0.06537473, 0.0, 0.020558, 0.0147407055, 0.024584293, 0.042943895, 0.037365377, 0.010082781, 0.01734531, 0.013758004, 0.063434005, 0.015683472, 0.06713873, 0.03570056, 0.06191671, 0.036923587, 0.08552998, 0.09596342, 0.03491491, 0.014481962, 0.07607061, 0.09089303, 0.044195414, 0.019605517, 0.038737833, 0.03937453, 0.07886726, 0.017585933, 0.058259606, 0.016803026, 0.052642763, 0.033255637, 0.012968183, 0.03909421, 0.049857914, 0.03886944, 0.03360915, 0.04992181, 0.007153809, 0.06810176, 0.04492891, 0.053261876, 0.030195653, 0.02363491, 0.07370812, 0.0401541, 0.017834485, 0.027286708, 0.08320671, 0.0077682137, 0.0318982, 0.03273022, 0.046396255, 0.033866942, 0.016702652, 0.0046455264, 0.050757885, 0.027853608]
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: 2026-01-28T01:05:36.809
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-28T01:05:36.809
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: 2026-01-28T01:05:36.809
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.810
[ Info: neardup> range: 49:64, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.810
[ Info: neardup> range: 65:80, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.810
[ Info: neardup> range: 81:96, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.810
[ Info: neardup> range: 97:100, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.810
[ Info: neardup> finished current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:36.810
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000016]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 10, 4, 14, 1, 10, 22, 14, 5, 14, 15, 10, 9, 2, 13, 4, 4, 2, 10, 4, 22, 4, 4, 4, 10, 5, 4, 1, 10, 5, 4, 6, 10, 14, 15, 16, 2, 7, 7, 14, 10, 14, 10, 2, 14, 4, 15, 10, 7, 14, 10, 10, 10, 14, 4, 16, 2, 1, 4, 4, 2, 10, 2, 1, 15, 4, 22, 10, 16, 14, 1, 14, 10, 4, 2, 9, 7, 12, 10, 1, 2, 12, 1, 7, 22]
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, 0.022823632, 0.02358538, 0.0033606887, 0.014216781, 0.035200834, 0.0, 0.012295663, 0.036250412, 0.02597922, 0.08366501, 0.055359364, 0.009853721, 0.03390205, 0.03703606, 0.030156255, 0.013335168, 0.06242585, 0.035538554, 0.00032669306, 0.07100618, 0.04260385, 0.04119873, 0.014798045, 0.042657077, 0.022850394, 0.015389144, 0.06537473, 0.06511861, 0.020558, 0.0147407055, 0.010149598, 0.027254522, 0.021683812, 0.0020297766, 0.014545023, 0.013758004, 0.0017712116, 0.06599212, 0.0814566, 0.028093457, 0.039824307, 0.063524485, 0.09354824, 0.031747997, 0.03491491, 0.07462406, 0.06675887, 0.010746837, 0.039227664, 0.014933825, 0.027336001, 0.0128445625, 0.04142493, 0.017585933, 0.013847709, 0.016803026, 0.059237003, 0.033255637, 0.012968183, 0.03909421, 0.018854618, 0.03886944, 0.03360915, 0.04350871, 0.007153809, 0.06810176, 0.044820428, 0.020065308, 0.008825183, 0.02363491, 0.023492634, 0.02261275, 0.017834485, 0.027286708, 0.046813786, 0.06513739, 0.026037097, 0.014338195, 0.046396255, 0.033866942, 0.0014129281, 0.0046455264, 0.018507779, 0.027853608]
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: 2026-01-28T01:05:44.174
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=6 n=6 2026-01-28T01:05:44.174
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.179
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.179
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.179
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.179
[ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.180
[ Info: neardup> range: 97:100, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.180
[ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-28T01:05:44.180
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x0000000d, 0x00000016, 0x0000001a, 0x0000002c]
D.nn = Int32[1, 2, 3, 4, 5, 4, 1, 3, 3, 4, 4, 1, 13, 5, 1, 3, 1, 4, 5, 1, 1, 22, 2, 5, 1, 26, 1, 13, 2, 13, 4, 4, 2, 1, 4, 22, 4, 4, 4, 22, 5, 4, 1, 44, 5, 4, 4, 4, 5, 1, 3, 2, 1, 26, 26, 4, 22, 44, 26, 26, 4, 26, 4, 13, 22, 44, 1, 44, 26, 4, 4, 2, 26, 4, 4, 2, 1, 2, 1, 1, 4, 22, 1, 3, 5, 1, 4, 4, 4, 2, 13, 26, 1, 44, 1, 2, 1, 1, 1, 22]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.06429905, 0.067756414, 0.026958287, 0.08733839, 0.08474219, 0.05269581, 0.017104149, 0.0, 0.06508267, 0.00881201, 0.053682268, 0.069702625, 0.02358538, 0.048232853, 0.014216781, 0.06212282, 0.0, 0.040896595, 0.036250412, 0.0754118, 0.0, 0.07182902, 0.056686163, 0.03390205, 0.03703606, 0.030156255, 0.013335168, 0.06242585, 0.053959787, 0.00032669306, 0.07100618, 0.04260385, 0.04119873, 0.014798045, 0.07948828, 0.022850394, 0.015389144, 0.06537473, 0.0, 0.020558, 0.0147407055, 0.024584293, 0.042943895, 0.037365377, 0.010082781, 0.01734531, 0.013758004, 0.063434005, 0.015683472, 0.06713873, 0.03570056, 0.06191671, 0.036923587, 0.08552998, 0.09596342, 0.03491491, 0.014481962, 0.07607061, 0.09089303, 0.044195414, 0.019605517, 0.038737833, 0.03937453, 0.07886726, 0.017585933, 0.058259606, 0.016803026, 0.052642763, 0.033255637, 0.012968183, 0.03909421, 0.049857914, 0.03886944, 0.03360915, 0.04992181, 0.007153809, 0.06810176, 0.04492891, 0.053261876, 0.030195653, 0.02363491, 0.07370812, 0.0401541, 0.017834485, 0.027286708, 0.08320671, 0.0077682137, 0.0318982, 0.03273022, 0.046396255, 0.033866942, 0.016702652, 0.0046455264, 0.050757885, 0.027853608]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  7.4s
computing farthest point 1, dmax: Inf, imax: 18, n: 30
computing farthest point 2, dmax: 0.9745338, imax: 26, n: 30
computing farthest point 3, dmax: 0.87579584, imax: 21, n: 30
computing farthest point 4, dmax: 0.7843218, imax: 14, n: 30
computing farthest point 5, dmax: 0.7348733, imax: 13, n: 30
computing farthest point 6, dmax: 0.7026771, imax: 22, n: 30
computing farthest point 7, dmax: 0.5798117, imax: 2, n: 30
computing farthest point 8, dmax: 0.53452104, imax: 4, n: 30
computing farthest point 9, dmax: 0.53444904, imax: 3, n: 30
computing farthest point 10, dmax: 0.52515674, imax: 15, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.5s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.6s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-28T01:05:52.467
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=0.95, maxvisits=108) 2026-01-28T01:06:04.429
LOG n.size quantiles:[4.0, 4.0, 4.0, 4.0, 5.0]
(i, j, d) = (9, 283, -1.1920929f-7)
(i, j, d, :parallel) = (9, 917, -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 => 19.588416426000002, :exact => 0.938148638)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  21.1s
  5.944812 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.005177 seconds
SEARCH Exhaustive 2: 0.004913 seconds
SEARCH Exhaustive 3: 0.006016 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) 2026-01-28T01:06:33.175
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=16, Δ=1.155, maxvisits=194) 2026-01-28T01:06:38.669
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 5.0]
LOG add_vertex! sp=18285 ep=18289 n=18284 BeamSearch
BeamSearch(bsize=10, Δ=1.1, maxvisits=372) 2026-01-28T01:06:39.669
LOG n.size quantiles:[3.0, 5.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=31235 ep=31239 n=31234 BeamSearch
BeamSearch(bsize=12, Δ=1.21275, maxvisits=476) 2026-01-28T01:06:40.669
LOG n.size quantiles:[4.0, 5.0, 5.0, 7.0, 9.0]
LOG add_vertex! sp=42020 ep=42024 n=42019 BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=414) 2026-01-28T01:06:41.669
LOG n.size quantiles:[5.0, 7.0, 8.0, 9.0, 10.0]
LOG add_vertex! sp=53200 ep=53204 n=53199 BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=414) 2026-01-28T01:06:42.669
LOG n.size quantiles:[4.0, 4.0, 5.0, 7.0, 8.0]
LOG add_vertex! sp=62145 ep=62149 n=62144 BeamSearch
BeamSearch(bsize=6, Δ=1.025, maxvisits=518) 2026-01-28T01:06:43.669
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=72990 ep=72994 n=72989 BeamSearch
BeamSearch(bsize=6, Δ=1.025, maxvisits=518) 2026-01-28T01:06:44.670
LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=83105 ep=83109 n=83104 BeamSearch
BeamSearch(bsize=6, Δ=1.025, maxvisits=518) 2026-01-28T01:06:45.670
LOG n.size quantiles:[4.0, 5.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=90470 ep=90474 n=90469 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=612) 2026-01-28T01:06:46.670
LOG n.size quantiles:[5.0, 5.0, 6.0, 9.0, 9.0]
LOG add_vertex! sp=99585 ep=99589 n=99584 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=612) 2026-01-28T01:06:47.670
LOG n.size quantiles:[4.0, 6.0, 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, 91.0]
[ Info: minrecall: queries per second: 13535.185906861247, recall: 0.901375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=5, Δ=1.18, maxvisits=838))
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, 91.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=626)), 1000, 8)
[ Info: rebuild: queries per second: 15956.110484257582, recall: 0.90525
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=626))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=852)), 1000, 8)
  1.624301 seconds (496.34 k allocations: 28.653 MiB, 96.08% compilation time)
[ Info: matrixhints: queries per second: 14348.783337963207, recall: 0.90175
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=852))
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, 91.0]
  2.261948 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.002052 seconds
SEARCH Exhaustive 2: 0.002071 seconds
SEARCH Exhaustive 3: 0.002336 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) 2026-01-28T01:07:57.163
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=16, Δ=1.155, maxvisits=194) 2026-01-28T01:08:02.389
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 5.0]
LOG add_vertex! sp=22300 ep=22304 n=22299 BeamSearch
BeamSearch(bsize=10, Δ=1.1, maxvisits=372) 2026-01-28T01:08:03.390
LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=37490 ep=37494 n=37489 BeamSearch
BeamSearch(bsize=12, Δ=1.21275, maxvisits=476) 2026-01-28T01:08:04.390
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=50325 ep=50329 n=50324 BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=414) 2026-01-28T01:08:05.390
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=62375 ep=62379 n=62374 BeamSearch
BeamSearch(bsize=6, Δ=1.025, maxvisits=518) 2026-01-28T01:08:06.390
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=74300 ep=74304 n=74299 BeamSearch
BeamSearch(bsize=6, Δ=1.025, maxvisits=518) 2026-01-28T01:08:07.390
LOG n.size quantiles:[5.0, 5.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=612) 2026-01-28T01:08:08.430
LOG n.size quantiles:[7.0, 8.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=95625 ep=95629 n=95624 BeamSearch
BeamSearch(bsize=12, Δ=1.1851876, maxvisits=612) 2026-01-28T01:08:09.430
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 91.0]
[ Info: minrecall: queries per second: 15444.760847531252, recall: 0.901375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=5, Δ=1.18, maxvisits=838))
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, 91.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=626)), 1000, 8)
[ Info: rebuild: queries per second: 15102.532147929543, recall: 0.90525
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=626))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=852)), 1000, 8)
  1.478939 seconds (459.92 k allocations: 26.627 MiB, 95.24% compilation time)
[ Info: matrixhints: queries per second: 14486.231459905312, recall: 0.90175
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.1851876, maxvisits=852))
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, 91.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  2m40.2s
     Testing SimilaritySearch tests passed 

Testing completed after 655.73s

PkgEval succeeded after 719.77s