Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1555 (0c48c4942b*) started at 2026-01-13T23:36:57.705


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

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

Set-up completed after 9.62s


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

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

Installation completed after 4.5s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   5560.8 ms  ✓ SearchModels
   9685.4 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 17 seconds. 88 already precompiled.

Precompilation completed after 33.67s


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

     Testing SimilaritySearch
      Status `/tmp/jl_7mSW0L/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_7mSW0L/Manifest.toml`
  [7d9f7c33] Accessors v0.1.43
  [79e6a3ab] Adapt v4.4.0
  [4c88cf16] Aqua v0.8.14
  [4fba245c] ArrayInterface v7.22.0
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [2a0fbf3d] CPUSummary v0.2.7
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.18.1
  [a33af91c] CompositionsBase v0.1.2
  [187b0558] ConstructionBase v1.6.0
  [adafc99b] CpuId v0.3.1
  [9a962f9c] DataAPI v1.16.0
⌅ [864edb3b] DataStructures v0.18.22
  [b4f34e82] Distances v0.10.12
  [ffbed154] DocStringExtensions v0.9.5
  [615f187c] IfElse v0.1.1
  [3587e190] InverseFunctions v0.1.17
  [92d709cd] IrrationalConstants v0.2.6
  [10f19ff3] LayoutPointers v0.1.17
  [2ab3a3ac] LogExpFunctions v0.3.29
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [e1d29d7a] Missings v1.2.0
  [bac558e1] OrderedCollections v1.8.1
  [d96e819e] Parameters v0.12.3
  [f517fe37] Polyester v0.7.18
  [1d0040c9] PolyesterWeave v0.2.2
  [aea7be01] PrecompileTools v1.3.3
  [21216c6a] Preferences v1.5.1
  [92933f4c] ProgressMeter v1.11.0
  [ae029012] Requires v1.3.1
  [94e857df] SIMDTypes v0.1.0
  [431bcebd] SciMLPublic v1.0.1
⌅ [0e966ebe] SearchModels v0.4.1
  [053f045d] SimilaritySearch v0.13.7
  [a2af1166] SortingAlgorithms v1.2.2
  [aedffcd0] Static v1.3.1
  [0d7ed370] StaticArrayInterface v1.8.0
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
⌅ [2913bbd2] StatsBase v0.33.21
  [7792a7ef] StrideArraysCore v0.5.8
  [8290d209] ThreadingUtilities v0.5.5
  [3a884ed6] UnPack v1.0.2
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0
  [b27032c2] LibCURL v1.0.0
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.14.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v1.0.0
  [9e88b42a] Serialization v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [f489334b] StyledStrings v1.13.0
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.18.0+0
  [e37daf67] LibGit2_jll v1.9.2+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.12.2
  [4536629a] OpenBLAS_jll v0.3.29+0
  [458c3c95] OpenSSL_jll v3.5.4+0
  [efcefdf7] PCRE2_jll v10.47.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [3161d3a3] Zstd_jll v1.5.7+1
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.68.0+1
  [3f19e933] p7zip_jll v17.7.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Test Summary:              | Pass  Total  Time
test database abstractions |   56     56  9.0s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  2.4s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  1.8s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  0.8s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  5.545409 seconds (1000 allocations: 78.125 KiB)
  5.168216 seconds (1000 allocations: 78.125 KiB)
  1.957179 seconds (1000 allocations: 78.125 KiB)
  2.006829 seconds (1000 allocations: 78.125 KiB)
  1.912809 seconds (1000 allocations: 78.125 KiB)
  1.906945 seconds (1000 allocations: 78.125 KiB)
  2.113739 seconds (1000 allocations: 78.125 KiB)
  1.905642 seconds (1000 allocations: 78.125 KiB)
 10.849588 seconds (1000 allocations: 78.125 KiB)
 10.742435 seconds (1000 allocations: 78.125 KiB)
 22.893309 seconds (1000 allocations: 78.125 KiB)
 22.928387 seconds (1000 allocations: 78.125 KiB)
 15.194630 seconds (6.23 k allocations: 358.125 KiB)
 14.612152 seconds (1000 allocations: 78.125 KiB)
 11.587233 seconds (1.00 k allocations: 78.141 KiB)
 11.940485 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  2m31.7s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  2.339783 seconds (1000 allocations: 78.125 KiB)
  2.342162 seconds (1000 allocations: 78.125 KiB)
 16.104990 seconds (1000 allocations: 78.125 KiB)
 16.164128 seconds (1000 allocations: 78.125 KiB)
 16.015272 seconds (1000 allocations: 78.125 KiB)
 15.935742 seconds (1000 allocations: 78.125 KiB)
  2.600810 seconds (1000 allocations: 78.125 KiB)
  2.573447 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  1m16.8s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  8.669791 seconds (1000 allocations: 78.125 KiB)
  8.616701 seconds (1000 allocations: 78.125 KiB)
  8.619344 seconds (1000 allocations: 78.125 KiB)
  8.568359 seconds (1000 allocations: 78.125 KiB)
  8.536101 seconds (1000 allocations: 78.125 KiB)
  8.618758 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total   Time
indexing sets with ExhaustiveSearch | 3000   3000  54.4s
  0.041698 seconds (1.00 k allocations: 78.141 KiB)
  0.042058 seconds (1000 allocations: 78.125 KiB)
  0.019017 seconds (1000 allocations: 78.125 KiB)
  0.019139 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  2.0s
  0.022120 seconds (1000 allocations: 78.125 KiB)
  0.022003 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  0.9s
ExhaustiveSearch allknn: 3.569330 seconds (1.99 M allocations: 119.967 MiB, 1.29% gc time, 99.97% compilation time)
ParallelExhaustiveSearch allknn: 0.956954 seconds (527.93 k allocations: 28.782 MiB, 99.87% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  5.0s
quantile(length.(hsp_knns), 0:0.1:1) = [2.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 5.0, 5.0, 6.0]
Test Summary: | Total  Time
HSP           |     0  2.2s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:41.134
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-13T23:43:41.376
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) 2026-01-13T23:43:42.914
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: 2026-01-13T23:43:43.215
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000005, 0x00000006, 0x00000008, 0x00000010, 0x0000001b, 0x0000001f, 0x00000034, 0x00000045]
D.nn = Int32[1, 2, 2, 4, 5, 6, 4, 8, 2, 1, 2, 1, 5, 1, 5, 16, 5, 5, 5, 5, 8, 8, 2, 5, 5, 16, 27, 6, 5, 6, 31, 5, 8, 5, 1, 1, 31, 31, 2, 2, 1, 16, 2, 16, 16, 27, 8, 2, 2, 6, 6, 52, 6, 2, 2, 8, 5, 5, 6, 5, 31, 8, 5, 5, 6, 5, 8, 5, 69, 31, 16, 5, 8, 8, 5, 1, 31, 5, 1, 6, 4, 1, 31, 69, 6, 5, 2, 2, 5, 52, 16, 5, 2, 8, 2, 69, 6, 6, 31, 69]
D.dist = Float32[0.0, 0.0, 0.050947726, 0.0, 0.0, 0.0, 0.0043767095, 0.0, 0.02181673, 0.024885416, 0.024941027, 0.04164505, 0.0258767, 0.0023363829, 0.060239017, 0.0, 0.012741029, 0.017519355, 0.0044630766, 0.027545393, 0.009991765, 0.059532702, 0.036773503, 0.058048964, 0.03477627, 0.097821295, 0.0, 0.042369187, 0.04229629, 0.026313305, 0.0, 0.053219676, 0.01877153, 0.060661614, 0.039514244, 0.030047238, 0.056149483, 0.029477239, 0.025764465, 0.0782966, 0.03530073, 0.032752156, 0.062471986, 0.022053361, 0.091206014, 0.040149093, 0.042733133, 0.08063084, 0.037446916, 0.0152234435, 0.02974248, 0.0, 0.00983417, 0.05455768, 0.07259405, 0.03754753, 0.028217793, 0.016475499, 0.020447016, 0.05816251, 0.0068175793, 0.08570349, 0.04561019, 0.04371828, 0.032452285, 0.09560001, 0.0432117, 0.037543178, 0.0, 0.032962203, 0.011254907, 0.006579578, 0.057574987, 0.079272985, 0.038486302, 0.021151781, 0.0155285, 0.038734853, 0.034365237, 0.019698799, 0.042434692, 0.0019392967, 0.047139943, 0.04901707, 0.026217401, 0.02533096, 0.059050977, 0.016624272, 0.015347779, 0.06557143, 0.016860068, 0.010094702, 0.03004688, 0.036822855, 0.059731483, 0.035277545, 0.020911932, 0.005034983, 0.008402765, 0.020487666]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  13.8s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.204
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-13T23:43:44.204
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.205
[ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.205
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.205
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.206
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.206
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.206
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.206
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000005, 0x00000006, 0x00000008, 0x00000010, 0x0000001b, 0x0000001f, 0x00000034, 0x00000045]
D.nn = Int32[1, 2, 2, 4, 5, 6, 4, 8, 2, 1, 2, 1, 5, 1, 5, 16, 5, 5, 5, 5, 8, 8, 2, 5, 5, 16, 27, 6, 5, 6, 31, 5, 8, 5, 1, 1, 31, 31, 2, 2, 1, 16, 2, 16, 16, 27, 8, 2, 2, 6, 6, 52, 6, 2, 2, 8, 5, 5, 6, 5, 31, 8, 5, 5, 6, 5, 8, 5, 69, 31, 16, 5, 8, 8, 5, 1, 31, 5, 1, 6, 4, 1, 31, 69, 6, 5, 2, 2, 5, 52, 16, 5, 2, 8, 2, 69, 6, 6, 31, 69]
D.dist = Float32[0.0, 0.0, 0.050947726, 0.0, 0.0, 0.0, 0.0043767095, 0.0, 0.02181673, 0.024885416, 0.024941027, 0.04164505, 0.0258767, 0.0023363829, 0.060239017, 0.0, 0.012741029, 0.017519355, 0.0044630766, 0.027545393, 0.009991765, 0.059532702, 0.036773503, 0.058048964, 0.03477627, 0.097821295, 0.0, 0.042369187, 0.04229629, 0.026313305, 0.0, 0.053219676, 0.01877153, 0.060661614, 0.039514244, 0.030047238, 0.056149483, 0.029477239, 0.025764465, 0.0782966, 0.03530073, 0.032752156, 0.062471986, 0.022053361, 0.091206014, 0.040149093, 0.042733133, 0.08063084, 0.037446916, 0.0152234435, 0.02974248, 0.0, 0.00983417, 0.05455768, 0.07259405, 0.03754753, 0.028217793, 0.016475499, 0.020447016, 0.05816251, 0.0068175793, 0.08570349, 0.04561019, 0.04371828, 0.032452285, 0.09560001, 0.0432117, 0.037543178, 0.0, 0.032962203, 0.011254907, 0.006579578, 0.057574987, 0.079272985, 0.038486302, 0.021151781, 0.0155285, 0.038734853, 0.034365237, 0.019698799, 0.042434692, 0.0019392967, 0.047139943, 0.04901707, 0.026217401, 0.02533096, 0.059050977, 0.016624272, 0.015347779, 0.06557143, 0.016860068, 0.010094702, 0.03004688, 0.036822855, 0.059731483, 0.035277545, 0.020911932, 0.005034983, 0.008402765, 0.020487666]
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: 2026-01-13T23:43:44.281
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-13T23:43:44.281
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: 2026-01-13T23:43:44.282
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.282
[ Info: neardup> range: 49:64, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.282
[ Info: neardup> range: 65:80, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.282
[ Info: neardup> range: 81:96, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.282
[ Info: neardup> range: 97:100, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.282
[ Info: neardup> finished current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:44.282
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000001b, 0x00000034]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 5, 13, 5, 13, 8, 8, 9, 5, 5, 16, 27, 6, 15, 6, 3, 5, 8, 5, 14, 12, 3, 8, 11, 11, 10, 16, 2, 16, 12, 27, 8, 2, 11, 6, 13, 52, 6, 2, 9, 3, 13, 5, 6, 5, 3, 8, 15, 11, 6, 11, 8, 5, 11, 8, 16, 5, 8, 8, 13, 1, 3, 5, 12, 6, 7, 14, 3, 1, 9, 5, 11, 9, 5, 52, 16, 5, 9, 8, 9, 11, 6, 6, 3, 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, 0.012741029, 0.012912214, 0.0044630766, 0.023736417, 0.009991765, 0.059532702, 0.012228608, 0.058048964, 0.03477627, 0.097821295, 0.0, 0.042369187, 0.027194202, 0.026313305, 0.017520547, 0.053219676, 0.01877153, 0.060661614, 0.030195296, 0.0043771863, 0.0784502, 0.040100217, 0.018838525, 0.02287525, 0.003652811, 0.032752156, 0.062471986, 0.022053361, 0.06656754, 0.040149093, 0.042733133, 0.08063084, 0.007757187, 0.0152234435, 0.005957842, 0.0, 0.00983417, 0.05455768, 0.05340904, 0.027481377, 0.023223042, 0.016475499, 0.020447016, 0.05816251, 0.005277157, 0.08570349, 0.043078065, 0.019095004, 0.032452285, 0.08597571, 0.0432117, 0.037543178, 0.098890185, 0.04334843, 0.011254907, 0.006579578, 0.057574987, 0.079272985, 0.0031550527, 0.021151781, 0.027703285, 0.038734853, 0.019060135, 0.019698799, 0.030362546, 0.0011105537, 0.0669409, 0.09867883, 0.008352995, 0.02533096, 0.02694267, 0.0113841295, 0.015347779, 0.06557143, 0.016860068, 0.010094702, 0.019189775, 0.036822855, 0.02565968, 0.07933134, 0.020911932, 0.005034983, 0.03770423, 0.09911561]
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: 2026-01-13T23:43:50.011
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=7 n=7 2026-01-13T23:43:50.012
[ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.017
[ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.017
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.017
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.017
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.017
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.018
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-01-13T23:43:50.018
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000005, 0x00000006, 0x00000008, 0x00000010, 0x0000001b, 0x0000001f, 0x00000034, 0x00000045]
D.nn = Int32[1, 2, 2, 4, 5, 6, 4, 8, 2, 1, 2, 1, 5, 1, 5, 16, 5, 5, 5, 5, 8, 8, 2, 5, 5, 16, 27, 6, 5, 6, 31, 5, 8, 5, 1, 1, 31, 31, 2, 2, 1, 16, 2, 16, 16, 27, 8, 2, 2, 6, 6, 52, 6, 2, 2, 8, 5, 5, 6, 5, 31, 8, 5, 5, 6, 5, 8, 5, 69, 31, 16, 5, 8, 8, 5, 1, 31, 5, 1, 6, 4, 1, 31, 69, 6, 5, 2, 2, 5, 52, 16, 5, 2, 8, 2, 69, 6, 6, 31, 69]
D.dist = Float32[0.0, 0.0, 0.050947726, 0.0, 0.0, 0.0, 0.0043767095, 0.0, 0.02181673, 0.024885416, 0.024941027, 0.04164505, 0.0258767, 0.0023363829, 0.060239017, 0.0, 0.012741029, 0.017519355, 0.0044630766, 0.027545393, 0.009991765, 0.059532702, 0.036773503, 0.058048964, 0.03477627, 0.097821295, 0.0, 0.042369187, 0.04229629, 0.026313305, 0.0, 0.053219676, 0.01877153, 0.060661614, 0.039514244, 0.030047238, 0.056149483, 0.029477239, 0.025764465, 0.0782966, 0.03530073, 0.032752156, 0.062471986, 0.022053361, 0.091206014, 0.040149093, 0.042733133, 0.08063084, 0.037446916, 0.0152234435, 0.02974248, 0.0, 0.00983417, 0.05455768, 0.07259405, 0.03754753, 0.028217793, 0.016475499, 0.020447016, 0.05816251, 0.0068175793, 0.08570349, 0.04561019, 0.04371828, 0.032452285, 0.09560001, 0.0432117, 0.037543178, 0.0, 0.032962203, 0.011254907, 0.006579578, 0.057574987, 0.079272985, 0.038486302, 0.021151781, 0.0155285, 0.038734853, 0.034365237, 0.019698799, 0.042434692, 0.0019392967, 0.047139943, 0.04901707, 0.026217401, 0.02533096, 0.059050977, 0.016624272, 0.015347779, 0.06557143, 0.016860068, 0.010094702, 0.03004688, 0.036822855, 0.059731483, 0.035277545, 0.020911932, 0.005034983, 0.008402765, 0.020487666]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  5.7s
computing farthest point 1, dmax: Inf, imax: 10, n: 30
computing farthest point 2, dmax: 1.3429077, imax: 27, n: 30
computing farthest point 3, dmax: 0.9737635, imax: 22, n: 30
computing farthest point 4, dmax: 0.8940783, imax: 6, n: 30
computing farthest point 5, dmax: 0.80701435, imax: 11, n: 30
computing farthest point 6, dmax: 0.79146826, imax: 16, n: 30
computing farthest point 7, dmax: 0.6820661, imax: 18, n: 30
computing farthest point 8, dmax: 0.5979905, imax: 26, n: 30
computing farthest point 9, dmax: 0.55834323, imax: 24, n: 30
computing farthest point 10, dmax: 0.55212915, imax: 5, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.1s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.2s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-01-13T23:43:55.384
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=0.9047619, maxvisits=112) 2026-01-13T23:44:04.444
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 6.0]
(i, j, d) = (54, 314, -1.1920929f-7)
(i, j, d, :parallel) = (54, 314, -1.1920929f-7, :parallel)
[ Info: NOTE: the exact method will be faster on small datasets due to the preprocessing step of the approximation method
[ Info: ("closestpair computation time", :approx => 13.831811373, :exact => 0.803122465)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  15.1s
  1.884445 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001627 seconds
SEARCH Exhaustive 2: 0.001670 seconds
SEARCH Exhaustive 3: 0.001555 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) 2026-01-13T23:44:19.302
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=8, Δ=1.2733874, maxvisits=210) 2026-01-13T23:44:23.336
LOG n.size quantiles:[3.0, 4.0, 4.0, 5.0, 5.0]
LOG add_vertex! sp=31140 ep=31144 n=31139 BeamSearch
BeamSearch(bsize=8, Δ=1.05, maxvisits=428) 2026-01-13T23:44:24.336
LOG n.size quantiles:[4.0, 5.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=51435 ep=51439 n=51434 BeamSearch
BeamSearch(bsize=16, Δ=1.05, maxvisits=422) 2026-01-13T23:44:25.336
LOG n.size quantiles:[4.0, 5.0, 5.0, 6.0, 8.0]
LOG add_vertex! sp=69105 ep=69109 n=69104 BeamSearch
BeamSearch(bsize=16, Δ=1.025, maxvisits=556) 2026-01-13T23:44:26.336
LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=85145 ep=85149 n=85144 BeamSearch
BeamSearch(bsize=16, Δ=1.025, maxvisits=556) 2026-01-13T23:44:27.336
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 7.0]
LOG add_vertex! sp=98475 ep=98479 n=98474 BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=498) 2026-01-13T23:44:28.336
LOG n.size quantiles:[6.0, 6.0, 6.0, 7.0, 11.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 86.0]
[ Info: minrecall: queries per second: 19313.220339663923, recall: 0.900875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.2, maxvisits=758))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 86.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=15, Δ=1.1851876, maxvisits=610)), 1000, 8)
[ Info: rebuild: queries per second: 20327.59587617315, recall: 0.9045
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=15, Δ=1.1851876, maxvisits=610))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.2155062, maxvisits=794)), 1000, 8)
  1.171246 seconds (496.50 k allocations: 28.658 MiB, 94.63% compilation time)
[ Info: matrixhints: queries per second: 19028.03358326148, recall: 0.903
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.2155062, maxvisits=794))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 86.0]
  1.819539 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001534 seconds
SEARCH Exhaustive 2: 0.001535 seconds
SEARCH Exhaustive 3: 0.001576 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) 2026-01-13T23:45:13.091
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=8, Δ=1.2733874, maxvisits=210) 2026-01-13T23:45:16.854
LOG n.size quantiles:[3.0, 4.0, 4.0, 5.0, 5.0]
LOG add_vertex! sp=29120 ep=29124 n=29119 BeamSearch
BeamSearch(bsize=8, Δ=1.05, maxvisits=428) 2026-01-13T23:45:17.854
LOG n.size quantiles:[6.0, 6.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=49425 ep=49429 n=49424 BeamSearch
BeamSearch(bsize=16, Δ=1.05, maxvisits=422) 2026-01-13T23:45:18.854
LOG n.size quantiles:[4.0, 5.0, 5.0, 6.0, 7.0]
LOG add_vertex! sp=65930 ep=65934 n=65929 BeamSearch
BeamSearch(bsize=16, Δ=1.025, maxvisits=556) 2026-01-13T23:45:19.855
LOG n.size quantiles:[4.0, 4.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=82390 ep=82394 n=82389 BeamSearch
BeamSearch(bsize=16, Δ=1.025, maxvisits=556) 2026-01-13T23:45:20.855
LOG n.size quantiles:[5.0, 7.0, 9.0, 9.0, 11.0]
LOG add_vertex! sp=93805 ep=93809 n=93804 BeamSearch
BeamSearch(bsize=10, Δ=1.1025, maxvisits=498) 2026-01-13T23:45:21.855
LOG n.size quantiles:[6.0, 6.0, 6.0, 6.0, 6.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 86.0]
[ Info: minrecall: queries per second: 21695.532319302954, recall: 0.900875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=10, Δ=1.2, maxvisits=758))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 86.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=15, Δ=1.1851876, maxvisits=610)), 1000, 8)
[ Info: rebuild: queries per second: 21662.221073450568, recall: 0.9045
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=15, Δ=1.1851876, maxvisits=610))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.2155062, maxvisits=794)), 1000, 8)
  1.084264 seconds (460.09 k allocations: 26.637 MiB, 3.34% gc time, 95.57% compilation time)
[ Info: matrixhints: queries per second: 20933.288477482783, recall: 0.903
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=18, Δ=1.2155062, maxvisits=794))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 86.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  1m44.4s
     Testing SimilaritySearch tests passed 

Testing completed after 480.01s

PkgEval succeeded after 545.4s