Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1299 (6d6224db99*) started at 2025-11-25T17:22:51.140


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.15s


################################################################################
# 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 v0.1.42
  [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 v1.5.0
  [92933f4c] + ProgressMeter v1.11.0
  [ae029012] + Requires v1.3.1
  [94e857df] + SIMDTypes v0.1.0
  [431bcebd] + SciMLPublic v1.0.0
  [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 v1.7.1
⌅ [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 v1.12.0
  [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 4.45s


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

Precompiling PkgEval dependencies...

┌ Error: Failed to use TestEnv.jl; test dependencies will not be precompiled
│   exception =
│    UndefVarError: `project_rel_path` not defined in `TestEnv`
│    Suggestion: this global was defined as `Pkg.Operations.project_rel_path` but not assigned a value.
│    Stacktrace:
│     [1] get_test_dir(ctx::Pkg.Types.Context, pkgspec::PackageSpec)
│       @ TestEnv ~/.julia/packages/TestEnv/i9lgt/src/julia-1.11/common.jl:75
│     [2] test_dir_has_project_file
│       @ ~/.julia/packages/TestEnv/i9lgt/src/julia-1.11/common.jl:52 [inlined]
│     [3] maybe_gen_project_override!
│       @ ~/.julia/packages/TestEnv/i9lgt/src/julia-1.11/common.jl:83 [inlined]
│     [4] activate(pkg::String; allow_reresolve::Bool)
│       @ TestEnv ~/.julia/packages/TestEnv/i9lgt/src/julia-1.11/activate_set.jl:12
│     [5] activate(pkg::String)
│       @ TestEnv ~/.julia/packages/TestEnv/i9lgt/src/julia-1.11/activate_set.jl:9
│     [6] top-level scope
│       @ /PkgEval.jl/scripts/precompile.jl:24
│     [7] include(mod::Module, _path::String)
│       @ Base ./Base.jl:309
│     [8] exec_options(opts::Base.JLOptions)
│       @ Base ./client.jl:344
│     [9] _start()
│       @ Base ./client.jl:577
└ @ Main /PkgEval.jl/scripts/precompile.jl:26
Precompiling package dependencies...
Precompiling packages...
   8954.7 ms  ✓ StatsBase
   5216.6 ms  ✓ SearchModels
  11171.8 ms  ✓ SimilaritySearch
  3 dependencies successfully precompiled in 26 seconds. 65 already precompiled.

Precompilation completed after 39.0s


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

     Testing SimilaritySearch
      Status `/tmp/jl_NVafZR/Project.toml`
  [7d9f7c33] Accessors v0.1.42
  [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_NVafZR/Manifest.toml`
  [7d9f7c33] Accessors v0.1.42
  [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 v1.5.0
  [92933f4c] ProgressMeter v1.11.0
  [ae029012] Requires v1.3.1
  [94e857df] SIMDTypes v0.1.0
  [431bcebd] SciMLPublic v1.0.0
  [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 v1.7.1
⌅ [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 v1.12.0
  [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 v1.13.0
  [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 v8.17.0+0
  [e37daf67] LibGit2_jll v1.9.1+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.11.4
  [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  17.4s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  4.2s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  2.6s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
 10.475098 seconds (1000 allocations: 78.125 KiB)
 10.738197 seconds (1000 allocations: 78.125 KiB)
  4.319387 seconds (1000 allocations: 78.125 KiB)
  4.346883 seconds (1000 allocations: 78.125 KiB)
  3.642165 seconds (1000 allocations: 78.125 KiB)
  3.995703 seconds (1000 allocations: 78.125 KiB)
  3.894152 seconds (1000 allocations: 78.125 KiB)
  4.027921 seconds (1000 allocations: 78.125 KiB)
 15.217734 seconds (1000 allocations: 78.125 KiB)
 15.271098 seconds (1000 allocations: 78.125 KiB)
 27.941398 seconds (1000 allocations: 78.125 KiB)
 28.273412 seconds (1000 allocations: 78.125 KiB)
 20.117626 seconds (6.23 k allocations: 358.094 KiB)
 21.277005 seconds (1000 allocations: 78.125 KiB)
 17.770176 seconds (1.00 k allocations: 78.141 KiB)
 18.203812 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m40.5s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.008507 seconds (1000 allocations: 78.125 KiB)
  3.027062 seconds (1000 allocations: 78.125 KiB)
 26.862991 seconds (1000 allocations: 78.125 KiB)
 29.161572 seconds (1000 allocations: 78.125 KiB)
 29.037042 seconds (1000 allocations: 78.125 KiB)
 27.355887 seconds (1000 allocations: 78.125 KiB)
  2.941062 seconds (1000 allocations: 78.125 KiB)
  3.021677 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m08.1s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 10.719959 seconds (1000 allocations: 78.125 KiB)
 11.624329 seconds (1000 allocations: 78.125 KiB)
 11.854812 seconds (1000 allocations: 78.125 KiB)
 11.796461 seconds (1000 allocations: 78.125 KiB)
 11.301172 seconds (1000 allocations: 78.125 KiB)
 10.547361 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m10.6s
  0.043591 seconds (1.00 k allocations: 78.141 KiB)
  0.043729 seconds (1000 allocations: 78.125 KiB)
  0.041885 seconds (1000 allocations: 78.125 KiB)
  0.041236 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  2.9s
  0.054619 seconds (1000 allocations: 78.125 KiB)
  0.053738 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.4s
ExhaustiveSearch allknn: 4.484680 seconds (2.38 M allocations: 126.985 MiB, 0.96% gc time, 99.96% compilation time)
ParallelExhaustiveSearch allknn: 1.252960 seconds (613.32 k allocations: 30.470 MiB, 2.01% gc time, 99.85% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  6.3s
quantile(length.(hsp_knns), 0:0.1:1) = [2.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 5.0, 5.0, 6.0]
Test Summary: | Total  Time
HSP           |     0  3.1s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:01.574
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-25T17:32:01.841
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) 2025-11-25T17:32:03.393
LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0]
[ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:03.801
D.map = UInt32[0x00000001, 0x00000002, 0x00000005, 0x0000000b, 0x0000000c, 0x00000015, 0x0000001f, 0x00000020, 0x00000025, 0x00000059]
D.nn = Int32[1, 2, 2, 1, 5, 1, 2, 1, 5, 5, 11, 12, 11, 12, 2, 5, 5, 1, 1, 11, 21, 2, 5, 2, 21, 5, 12, 12, 12, 1, 31, 32, 5, 21, 32, 21, 37, 32, 21, 2, 11, 37, 11, 12, 2, 2, 32, 37, 2, 11, 5, 5, 5, 1, 31, 32, 12, 5, 2, 5, 11, 5, 5, 32, 11, 11, 21, 2, 5, 12, 1, 11, 11, 2, 5, 11, 2, 32, 12, 2, 5, 12, 31, 11, 11, 32, 12, 21, 89, 32, 11, 32, 21, 1, 12, 21, 11, 11, 12, 32]
D.dist = Float32[0.0, 0.0, 0.054180324, 0.039238155, 0.0, 0.043506622, 0.03024745, 0.08652794, 0.09617013, 0.033783615, 0.0, 0.0, 0.06624615, 0.070456505, 0.06429899, 0.08213574, 0.04385686, 0.04199165, 0.0688228, 0.09910488, 0.0, 0.09724754, 0.078664064, 0.091694355, 0.039161444, 0.04460597, 0.08232671, 0.024698317, 0.011924088, 0.08311719, 0.0, 0.0, 0.031883, 0.09193659, 0.06935561, 0.010008931, 0.0, 0.036863804, 0.043553114, 0.0035276413, 0.040130556, 0.07140833, 0.04242474, 0.045985878, 0.030739367, 0.031831086, 0.03636974, 0.080002785, 0.009557068, 0.05830896, 0.059509516, 0.08982599, 0.04910499, 0.06970483, 0.055739462, 0.041865826, 0.06550634, 0.03528291, 0.08741355, 0.022803903, 0.024526954, 0.088324726, 0.026094615, 0.06610447, 0.047385275, 0.03271842, 0.04676479, 0.08501065, 0.06611049, 0.064905226, 0.010425627, 0.016257465, 0.008869052, 0.053200603, 0.058835983, 0.028912485, 0.03068167, 0.017468452, 0.058920503, 0.043149292, 0.025156438, 0.04367578, 0.014668763, 0.051799, 0.062205434, 0.058820784, 0.048520684, 0.06878936, 0.0, 0.018106401, 0.075971365, 0.0020279884, 0.049441755, 0.03743595, 0.0028480291, 0.018230617, 0.015896618, 0.033635557, 0.05568123, 0.016011775]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  19.2s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.020
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-25T17:32:05.021
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.022
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.022
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.022
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.023
[ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.023
[ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.023
[ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.023
D.map = UInt32[0x00000001, 0x00000002, 0x00000005, 0x0000000b, 0x0000000c, 0x00000015, 0x0000001f, 0x00000020, 0x00000025, 0x00000059]
D.nn = Int32[1, 2, 2, 1, 5, 1, 2, 1, 5, 5, 11, 12, 11, 12, 2, 5, 5, 1, 1, 11, 21, 2, 5, 2, 5, 5, 12, 12, 12, 1, 31, 32, 5, 21, 32, 21, 37, 32, 21, 2, 11, 21, 11, 12, 2, 2, 32, 32, 2, 11, 5, 5, 5, 1, 31, 32, 12, 5, 2, 5, 11, 5, 5, 32, 11, 11, 21, 2, 5, 12, 1, 11, 11, 2, 5, 11, 2, 32, 12, 2, 5, 12, 31, 11, 11, 32, 12, 21, 89, 32, 11, 32, 21, 1, 12, 21, 11, 11, 12, 32]
D.dist = Float32[0.0, 0.0, 0.054180324, 0.039238155, 0.0, 0.043506622, 0.03024745, 0.08652794, 0.09617013, 0.033783615, 0.0, 0.0, 0.06624615, 0.070456505, 0.06429899, 0.08213574, 0.04385686, 0.04199165, 0.0688228, 0.09910488, 0.0, 0.09724754, 0.078664064, 0.091694355, 0.059813023, 0.04460597, 0.08232671, 0.024698317, 0.011924088, 0.08311719, 0.0, 0.0, 0.031883, 0.09193659, 0.06935561, 0.010008931, 0.0, 0.036863804, 0.043553114, 0.0035276413, 0.040130556, 0.093046725, 0.04242474, 0.045985878, 0.030739367, 0.031831086, 0.03636974, 0.09412503, 0.009557068, 0.05830896, 0.059509516, 0.08982599, 0.04910499, 0.06970483, 0.055739462, 0.041865826, 0.06550634, 0.03528291, 0.08741355, 0.022803903, 0.024526954, 0.088324726, 0.026094615, 0.06610447, 0.047385275, 0.03271842, 0.04676479, 0.08501065, 0.06611049, 0.064905226, 0.010425627, 0.016257465, 0.008869052, 0.053200603, 0.058835983, 0.028912485, 0.03068167, 0.017468452, 0.058920503, 0.043149292, 0.025156438, 0.04367578, 0.014668763, 0.051799, 0.062205434, 0.058820784, 0.048520684, 0.06878936, 0.0, 0.018106401, 0.075971365, 0.0020279884, 0.049441755, 0.03743595, 0.0028480291, 0.018230617, 0.015896618, 0.033635557, 0.05568123, 0.016011775]
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: 2025-11-25T17:32:05.124
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-25T17:32:05.125
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: 2025-11-25T17:32:05.126
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.126
[ Info: neardup> range: 49:64, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.126
[ Info: neardup> range: 65:80, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.127
[ Info: neardup> range: 81:96, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.127
[ Info: neardup> range: 97:100, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.127
[ Info: neardup> finished current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:05.127
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000001f, 0x00000027]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 5, 6, 6, 14, 16, 15, 9, 2, 16, 16, 14, 14, 12, 6, 31, 14, 5, 16, 15, 16, 15, 15, 39, 2, 13, 3, 11, 14, 2, 7, 6, 15, 2, 8, 10, 9, 16, 4, 31, 16, 13, 10, 3, 5, 11, 3, 5, 14, 7, 11, 39, 3, 10, 14, 1, 11, 11, 3, 16, 11, 7, 6, 14, 7, 10, 12, 31, 7, 11, 39, 14, 16, 9, 6, 8, 14, 16, 6, 12, 16, 11, 11, 13, 16]
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, 0.04385686, 0.016780496, 0.015458465, 0.05613166, 0.04932618, 0.01902932, 0.0038573146, 0.091694355, 0.009363174, 0.006668806, 0.026487589, 0.017950296, 0.011924088, 0.008877873, 0.0, 0.03996688, 0.031883, 0.06854093, 0.060206234, 0.05697894, 0.05053121, 0.04412508, 0.0, 0.0035276413, 0.0067172647, 0.019626915, 0.04242474, 0.004023969, 0.030739367, 0.027039945, 0.04198855, 0.036765814, 0.009557068, 0.057072103, 0.011288226, 0.008571863, 0.03476703, 0.0069121122, 0.055739462, 0.016735554, 0.02428013, 0.016462088, 0.0120306015, 0.022803903, 0.024526954, 0.011773467, 0.026094615, 0.024150848, 0.03892511, 0.03271842, 0.038059354, 0.016065061, 0.006224513, 0.012851238, 0.010425627, 0.016257465, 0.008869052, 0.0050741434, 0.05016339, 0.028912485, 0.022782326, 0.0540756, 0.02140683, 0.031861544, 0.013722479, 0.04367578, 0.014668763, 0.047150075, 0.062205434, 0.025259137, 0.043797314, 0.013450861, 0.051925242, 0.013874233, 0.045887887, 0.035707176, 0.0017188787, 0.0033097863, 0.0028480291, 0.027538002, 0.015896618, 0.033635557, 0.051745534, 0.033136845]
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: 2025-11-25T17:32:12.685
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=5 n=5 2025-11-25T17:32:12.685
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.692
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.692
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.692
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.692
[ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.692
[ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.692
[ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-25T17:32:12.693
D.map = UInt32[0x00000001, 0x00000002, 0x00000005, 0x0000000b, 0x0000000c, 0x00000015, 0x0000001f, 0x00000020, 0x00000025, 0x00000059]
D.nn = Int32[1, 2, 2, 1, 5, 1, 2, 1, 5, 5, 11, 12, 11, 12, 2, 5, 5, 1, 1, 11, 21, 2, 5, 2, 5, 5, 12, 12, 12, 1, 31, 32, 5, 21, 32, 21, 37, 32, 21, 2, 11, 21, 11, 12, 2, 2, 32, 32, 2, 11, 5, 5, 5, 1, 31, 32, 12, 5, 2, 5, 11, 5, 5, 32, 11, 11, 21, 2, 5, 12, 1, 11, 11, 2, 5, 11, 2, 32, 12, 2, 5, 12, 31, 11, 11, 32, 12, 21, 89, 32, 11, 32, 21, 1, 12, 21, 11, 11, 12, 32]
D.dist = Float32[0.0, 0.0, 0.054180324, 0.039238155, 0.0, 0.043506622, 0.03024745, 0.08652794, 0.09617013, 0.033783615, 0.0, 0.0, 0.06624615, 0.070456505, 0.06429899, 0.08213574, 0.04385686, 0.04199165, 0.0688228, 0.09910488, 0.0, 0.09724754, 0.078664064, 0.091694355, 0.059813023, 0.04460597, 0.08232671, 0.024698317, 0.011924088, 0.08311719, 0.0, 0.0, 0.031883, 0.09193659, 0.06935561, 0.010008931, 0.0, 0.036863804, 0.043553114, 0.0035276413, 0.040130556, 0.093046725, 0.04242474, 0.045985878, 0.030739367, 0.031831086, 0.03636974, 0.09412503, 0.009557068, 0.05830896, 0.059509516, 0.08982599, 0.04910499, 0.06970483, 0.055739462, 0.041865826, 0.06550634, 0.03528291, 0.08741355, 0.022803903, 0.024526954, 0.088324726, 0.026094615, 0.06610447, 0.047385275, 0.03271842, 0.04676479, 0.08501065, 0.06611049, 0.064905226, 0.010425627, 0.016257465, 0.008869052, 0.053200603, 0.058835983, 0.028912485, 0.03068167, 0.017468452, 0.058920503, 0.043149292, 0.025156438, 0.04367578, 0.014668763, 0.051799, 0.062205434, 0.058820784, 0.048520684, 0.06878936, 0.0, 0.018106401, 0.075971365, 0.0020279884, 0.049441755, 0.03743595, 0.0028480291, 0.018230617, 0.015896618, 0.033635557, 0.05568123, 0.016011775]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  7.6s
computing farthest point 1, dmax: Inf, imax: 19, n: 30
computing farthest point 2, dmax: 1.1402915, imax: 20, n: 30
computing farthest point 3, dmax: 1.0140412, imax: 9, n: 30
computing farthest point 4, dmax: 1.003152, imax: 2, n: 30
computing farthest point 5, dmax: 1.000102, imax: 21, n: 30
computing farthest point 6, dmax: 0.6714077, imax: 27, n: 30
computing farthest point 7, dmax: 0.5721207, imax: 18, n: 30
computing farthest point 8, dmax: 0.55673283, imax: 12, n: 30
computing farthest point 9, dmax: 0.55270386, imax: 22, n: 30
computing farthest point 10, dmax: 0.54345506, imax: 24, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.7s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.7s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch
BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-25T17:32:21.599
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=0.975, maxvisits=114) 2025-11-25T17:32:33.189
LOG n.size quantiles:[4.0, 4.0, 4.0, 4.0, 4.0]
(i, j, d) = (23, 751, -1.1920929f-7)
(i, j, d, :parallel) = (23, 751, -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 => 19.50289257, :exact => 0.947941893)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  21.0s
  6.522435 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.004623 seconds
SEARCH Exhaustive 2: 0.004643 seconds
SEARCH Exhaustive 3: 0.005452 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) 2025-11-25T17:33:02.699
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=11, Δ=1.07625, maxvisits=218) 2025-11-25T17:33:08.221
LOG n.size quantiles:[3.0, 3.0, 4.0, 4.0, 4.0]
LOG add_vertex! sp=18405 ep=18409 n=18404 BeamSearch
BeamSearch(bsize=4, Δ=1.07625, maxvisits=372) 2025-11-25T17:33:09.221
LOG n.size quantiles:[4.0, 4.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=33895 ep=33899 n=33894 BeamSearch
BeamSearch(bsize=14, Δ=1.0, maxvisits=438) 2025-11-25T17:33:10.221
LOG n.size quantiles:[3.0, 5.0, 5.0, 7.0, 8.0]
LOG add_vertex! sp=46290 ep=46294 n=46289 BeamSearch
BeamSearch(bsize=4, Δ=0.975, maxvisits=392) 2025-11-25T17:33:11.222
LOG n.size quantiles:[5.0, 7.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=462) 2025-11-25T17:33:12.222
LOG n.size quantiles:[5.0, 5.0, 5.0, 7.0, 8.0]
LOG add_vertex! sp=67705 ep=67709 n=67704 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=462) 2025-11-25T17:33:13.222
LOG n.size quantiles:[7.0, 7.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=77530 ep=77534 n=77529 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=462) 2025-11-25T17:33:14.222
LOG n.size quantiles:[6.0, 7.0, 9.0, 10.0, 10.0]
LOG add_vertex! sp=85405 ep=85409 n=85404 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=454) 2025-11-25T17:33:15.222
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=94535 ep=94539 n=94534 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=454) 2025-11-25T17:33:16.223
LOG n.size quantiles:[5.0, 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, 7.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 87.0]
[ Info: minrecall: queries per second: 12829.44408735825, recall: 0.904625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=13, Δ=1.19, maxvisits=734))
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, 87.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=572)), 1000, 8)
[ Info: rebuild: queries per second: 14777.926919900237, recall: 0.902375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=572))
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=11, Δ=1.17, maxvisits=734)), 1000, 8)
  1.633369 seconds (610.33 k allocations: 31.100 MiB, 95.86% compilation time)
[ Info: matrixhints: queries per second: 14755.619858579485, recall: 0.900875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.17, maxvisits=734))
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, 87.0]
  2.142256 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001955 seconds
SEARCH Exhaustive 2: 0.001952 seconds
SEARCH Exhaustive 3: 0.001995 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) 2025-11-25T17:34:24.726
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=11, Δ=1.07625, maxvisits=218) 2025-11-25T17:34:29.533
LOG n.size quantiles:[3.0, 3.0, 4.0, 4.0, 4.0]
LOG add_vertex! sp=34495 ep=34499 n=34494 BeamSearch
BeamSearch(bsize=14, Δ=1.0, maxvisits=438) 2025-11-25T17:34:30.533
LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=52910 ep=52914 n=52909 BeamSearch
BeamSearch(bsize=4, Δ=0.975, maxvisits=392) 2025-11-25T17:34:31.534
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=65015 ep=65019 n=65014 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=462) 2025-11-25T17:34:32.534
LOG n.size quantiles:[4.0, 4.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=76810 ep=76814 n=76809 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=462) 2025-11-25T17:34:33.534
LOG n.size quantiles:[5.0, 7.0, 8.0, 10.0, 12.0]
LOG add_vertex! sp=86570 ep=86574 n=86569 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=454) 2025-11-25T17:34:34.534
LOG n.size quantiles:[4.0, 5.0, 5.0, 8.0, 8.0]
LOG add_vertex! sp=97125 ep=97129 n=97124 BeamSearch
BeamSearch(bsize=16, Δ=1.075, maxvisits=454) 2025-11-25T17:34:35.534
LOG n.size quantiles:[6.0, 8.0, 8.0, 8.0, 9.0]
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, 87.0]
[ Info: minrecall: queries per second: 15039.92076247826, recall: 0.904625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=13, Δ=1.19, maxvisits=734))
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, 87.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=572)), 1000, 8)
[ Info: rebuild: queries per second: 16352.436876936385, recall: 0.902375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=16, Δ=1.155, maxvisits=572))
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=11, Δ=1.17, maxvisits=734)), 1000, 8)
  1.646505 seconds (566.26 k allocations: 28.917 MiB, 7.66% gc time, 95.94% compilation time)
[ Info: matrixhints: queries per second: 15455.974429635902, recall: 0.900875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch
BeamSearch(bsize=11, Δ=1.17, maxvisits=734))
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, 87.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  2m38.7s
     Testing SimilaritySearch tests passed 

Testing completed after 688.47s

PkgEval succeeded after 752.76s