Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.87 (8bcaa34afa*) started at 2025-11-15T10:55:24.237


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.29s


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

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [053f045d] + SimilaritySearch v0.13.6
    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 v0.13.6
  [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 v1.11.0
  [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 4.48s


################################################################################
# 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...
   8990.9 ms  ✓ StatsBase
   5633.9 ms  ✓ SearchModels
  14261.6 ms  ✓ SimilaritySearch
  3 dependencies successfully precompiled in 29 seconds. 65 already precompiled.

Precompilation completed after 42.52s


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

     Testing SimilaritySearch
      Status `/tmp/jl_3Yu4dL/Project.toml`
  [7d9f7c33] Accessors v0.1.42
  [4c88cf16] Aqua v0.8.14
  [b4f34e82] Distances v0.10.12
  [d96e819e] Parameters v0.12.3
  [f517fe37] Polyester v0.7.18
  [92933f4c] ProgressMeter v1.11.0
  [0e966ebe] SearchModels v0.4.1
  [053f045d] SimilaritySearch v0.13.6
  [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_3Yu4dL/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 v0.13.6
  [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 v1.11.0
  [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 v8.16.0+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  17.0s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.1s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  3.9s
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}})
 10.442033 seconds (1000 allocations: 78.125 KiB)
 10.440106 seconds (1000 allocations: 78.125 KiB)
  3.917753 seconds (1000 allocations: 78.125 KiB)
  3.959292 seconds (1000 allocations: 78.125 KiB)
  3.955436 seconds (1000 allocations: 78.125 KiB)
  3.965807 seconds (1000 allocations: 78.125 KiB)
  3.910437 seconds (1000 allocations: 78.125 KiB)
  3.852150 seconds (1000 allocations: 78.125 KiB)
 15.397966 seconds (1000 allocations: 78.125 KiB)
 15.212711 seconds (1000 allocations: 78.125 KiB)
 27.913356 seconds (1000 allocations: 78.125 KiB)
 28.025252 seconds (1000 allocations: 78.125 KiB)
 20.499094 seconds (6.23 k allocations: 358.125 KiB)
 20.565674 seconds (1000 allocations: 78.125 KiB)
 17.462221 seconds (1.00 k allocations: 78.141 KiB)
 17.635064 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m39.0s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.144132 seconds (1000 allocations: 78.125 KiB)
  3.134089 seconds (1000 allocations: 78.125 KiB)
 28.902813 seconds (1000 allocations: 78.125 KiB)
 28.615784 seconds (1000 allocations: 78.125 KiB)
 27.042169 seconds (1000 allocations: 78.125 KiB)
 28.473944 seconds (1000 allocations: 78.125 KiB)
  4.178344 seconds (1000 allocations: 78.125 KiB)
  4.180156 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m11.6s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 10.442260 seconds (1000 allocations: 78.125 KiB)
 10.315003 seconds (1000 allocations: 78.125 KiB)
 10.446264 seconds (1000 allocations: 78.125 KiB)
 10.418463 seconds (1000 allocations: 78.125 KiB)
 10.688320 seconds (1000 allocations: 78.125 KiB)
 10.642381 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m06.0s
  0.043609 seconds (1.00 k allocations: 78.141 KiB)
  0.043587 seconds (1000 allocations: 78.125 KiB)
  0.041594 seconds (1000 allocations: 78.125 KiB)
  0.040370 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  3.0s
  0.053847 seconds (1000 allocations: 78.125 KiB)
  0.055343 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.4s
ExhaustiveSearch allknn: 4.593376 seconds (2.39 M allocations: 127.055 MiB, 7.11% gc time, 99.96% compilation time)
ParallelExhaustiveSearch allknn: 1.179736 seconds (613.31 k allocations: 30.466 MiB, 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, 5.0]
Test Summary: | Total  Time
HSP           |     0  3.0s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:34.319
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:04:34.568
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:04:36.022
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: 2025-11-15T11:04:36.421
D.map = UInt32[0x00000001, 0x00000002, 0x00000007, 0x0000000a, 0x0000000c, 0x00000012, 0x00000021, 0x00000029, 0x0000002f, 0x00000031, 0x00000063]
D.nn = Int32[1, 2, 1, 1, 2, 1, 7, 1, 1, 10, 7, 12, 7, 7, 12, 1, 12, 18, 18, 7, 7, 1, 7, 12, 1, 7, 7, 1, 10, 18, 12, 2, 33, 2, 7, 18, 7, 7, 2, 12, 41, 18, 12, 2, 7, 1, 47, 18, 49, 1, 12, 49, 7, 1, 12, 18, 7, 41, 12, 12, 49, 18, 1, 12, 7, 7, 47, 49, 12, 47, 7, 7, 7, 49, 2, 18, 10, 41, 47, 7, 12, 1, 12, 2, 49, 49, 49, 1, 47, 7, 18, 2, 7, 12, 12, 1, 2, 7, 99, 33]
D.dist = Float32[0.0, 0.0, 0.06526488, 0.070464075, 0.04884368, 0.072149396, 0.0, 0.056932986, 0.08540487, 0.0, 0.04829538, 0.0, 0.042152464, 0.030816376, 0.055877566, 0.06317264, 0.055544257, 0.0, 0.07181078, 0.0765084, 0.06597048, 0.02561438, 0.021138966, 0.0287956, 0.071392715, 0.038879514, 0.04704559, 0.05107075, 0.056190312, 0.054702044, 0.033718944, 0.011977434, 0.0, 0.027049065, 0.045380056, 0.0073883533, 0.03517425, 0.06852329, 0.030208051, 0.058095932, 0.0, 0.02124989, 0.057594478, 0.021417618, 0.083120525, 0.051045954, 0.0, 0.09725523, 0.0, 0.03738928, 0.04717529, 0.027172983, 0.0032580495, 0.02802515, 0.03509587, 0.004929304, 0.004421711, 0.011513412, 0.06430513, 0.06658983, 0.01444, 0.026837587, 0.023746192, 0.02489829, 0.016504705, 0.018018425, 0.03440416, 0.05698353, 0.024368405, 0.036423564, 0.03606522, 0.015606403, 0.020361662, 0.0077924132, 0.011960506, 0.08466494, 0.029393673, 0.09837204, 0.046794415, 0.028968334, 0.037526906, 0.06507212, 0.018662572, 0.004229009, 0.06039244, 0.02576983, 0.029672801, 0.095044374, 0.08044112, 0.014451563, 0.04869765, 0.039979756, 0.043385804, 0.01368922, 0.056218743, 0.015610516, 0.09385413, 0.0133859515, 0.0, 0.07690114]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  18.6s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.597
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:04:37.597
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: 2025-11-15T11:04:37.598
[ Info: neardup> range: 33:48, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.598
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.598
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.599
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.599
[ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.599
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.599
D.map = UInt32[0x00000001, 0x00000002, 0x00000007, 0x0000000a, 0x0000000c, 0x00000012, 0x00000021, 0x00000029, 0x0000002f, 0x00000031, 0x00000063]
D.nn = Int32[1, 2, 1, 1, 2, 1, 7, 1, 1, 10, 7, 12, 7, 7, 12, 1, 12, 18, 7, 7, 7, 1, 7, 12, 1, 7, 7, 1, 10, 12, 12, 2, 33, 2, 7, 18, 7, 7, 2, 12, 41, 18, 12, 2, 7, 1, 47, 18, 49, 1, 12, 2, 7, 1, 12, 18, 7, 41, 12, 12, 2, 18, 1, 12, 7, 7, 47, 49, 12, 47, 7, 7, 7, 49, 2, 18, 10, 41, 47, 7, 12, 1, 12, 2, 49, 49, 49, 1, 47, 7, 18, 2, 7, 12, 12, 1, 2, 7, 99, 33]
D.dist = Float32[0.0, 0.0, 0.06526488, 0.070464075, 0.04884368, 0.072149396, 0.0, 0.056932986, 0.08540487, 0.0, 0.04829538, 0.0, 0.042152464, 0.030816376, 0.055877566, 0.06317264, 0.055544257, 0.0, 0.07532573, 0.0765084, 0.06597048, 0.02561438, 0.021138966, 0.0287956, 0.071392715, 0.038879514, 0.04704559, 0.05107075, 0.056190312, 0.07607794, 0.033718944, 0.011977434, 0.0, 0.027049065, 0.045380056, 0.0073883533, 0.03517425, 0.06852329, 0.030208051, 0.058095932, 0.0, 0.02124989, 0.057594478, 0.021417618, 0.083120525, 0.051045954, 0.0, 0.09725523, 0.0, 0.03738928, 0.04717529, 0.056597292, 0.0032580495, 0.02802515, 0.03509587, 0.004929304, 0.004421711, 0.011513412, 0.06430513, 0.06658983, 0.053925753, 0.026837587, 0.023746192, 0.02489829, 0.016504705, 0.018018425, 0.03440416, 0.05698353, 0.024368405, 0.036423564, 0.03606522, 0.015606403, 0.020361662, 0.0077924132, 0.011960506, 0.08466494, 0.029393673, 0.09837204, 0.046794415, 0.028968334, 0.037526906, 0.06507212, 0.018662572, 0.004229009, 0.06039244, 0.02576983, 0.029672801, 0.095044374, 0.08044112, 0.014451563, 0.04869765, 0.039979756, 0.043385804, 0.01368922, 0.056218743, 0.015610516, 0.09385413, 0.0133859515, 0.0, 0.07690114]
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: 2025-11-15T11:04:37.689
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:04:37.689
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: 2025-11-15T11:04:37.690
[ Info: neardup> range: 33:48, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.691
[ Info: neardup> range: 49:64, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.691
[ Info: neardup> range: 65:80, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.691
[ Info: neardup> range: 81:96, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.691
[ Info: neardup> range: 97:100, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.691
[ Info: neardup> finished current elements: 22, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:37.691
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000012, 0x00000021, 0x00000029, 0x00000031, 0x00000046, 0x00000063]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 15, 18, 13, 13, 13, 3, 7, 12, 1, 7, 14, 6, 9, 12, 12, 2, 33, 2, 7, 18, 11, 11, 2, 15, 41, 18, 14, 2, 13, 3, 8, 18, 49, 1, 12, 2, 7, 1, 12, 18, 7, 41, 14, 12, 2, 18, 1, 12, 7, 7, 8, 3, 12, 70, 14, 7, 7, 49, 2, 13, 10, 41, 9, 7, 11, 3, 12, 2, 3, 49, 49, 6, 16, 7, 18, 2, 14, 12, 12, 1, 9, 7, 99, 13]
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, 0.02179104, 0.0, 0.05686313, 0.036904454, 0.027247787, 0.013189256, 0.021138966, 0.0287956, 0.071392715, 0.038879514, 0.010841668, 0.024718583, 0.0329957, 0.07607794, 0.033718944, 0.011977434, 0.0, 0.027049065, 0.045380056, 0.0073883533, 0.008428037, 0.04677254, 0.030208051, 0.044528484, 0.0, 0.02124989, 0.006329119, 0.021417618, 0.07435942, 0.02306819, 0.06248188, 0.09725523, 0.0, 0.03738928, 0.04717529, 0.056597292, 0.0032580495, 0.02802515, 0.03509587, 0.004929304, 0.004421711, 0.011513412, 0.05991167, 0.06658983, 0.053925753, 0.026837587, 0.023746192, 0.02489829, 0.016504705, 0.018018425, 0.09287876, 0.032464564, 0.024368405, 0.0, 0.0030121207, 0.015606403, 0.020361662, 0.0077924132, 0.011960506, 0.0741145, 0.029393673, 0.09837204, 0.009799242, 0.028968334, 0.013042033, 0.003290832, 0.018662572, 0.004229009, 0.027381003, 0.02576983, 0.029672801, 0.081354916, 0.0118403435, 0.014451563, 0.04869765, 0.039979756, 0.0017570853, 0.01368922, 0.056218743, 0.015610516, 0.025205493, 0.0133859515, 0.0, 0.025388598]
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: 2025-11-15T11:04:44.953
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=5 n=5 2025-11-15T11:04:44.954
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.959
[ Info: neardup> range: 33:48, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.959
[ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.959
[ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.959
[ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.960
[ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.960
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-15T11:04:44.960
D.map = UInt32[0x00000001, 0x00000002, 0x00000007, 0x0000000a, 0x0000000c, 0x00000012, 0x00000021, 0x00000029, 0x0000002f, 0x00000031, 0x00000063]
D.nn = Int32[1, 2, 1, 1, 2, 1, 7, 1, 1, 10, 7, 12, 7, 7, 12, 1, 12, 18, 7, 7, 7, 1, 7, 12, 1, 7, 7, 1, 10, 12, 12, 2, 33, 2, 7, 18, 7, 7, 2, 12, 41, 18, 12, 2, 7, 1, 47, 18, 49, 1, 12, 2, 7, 1, 12, 18, 7, 41, 12, 12, 2, 18, 1, 12, 7, 7, 47, 49, 12, 47, 7, 7, 7, 49, 2, 18, 10, 41, 47, 7, 12, 1, 12, 2, 49, 49, 49, 1, 47, 7, 18, 2, 7, 12, 12, 1, 2, 7, 99, 33]
D.dist = Float32[0.0, 0.0, 0.06526488, 0.070464075, 0.04884368, 0.072149396, 0.0, 0.056932986, 0.08540487, 0.0, 0.04829538, 0.0, 0.042152464, 0.030816376, 0.055877566, 0.06317264, 0.055544257, 0.0, 0.07532573, 0.0765084, 0.06597048, 0.02561438, 0.021138966, 0.0287956, 0.071392715, 0.038879514, 0.04704559, 0.05107075, 0.056190312, 0.07607794, 0.033718944, 0.011977434, 0.0, 0.027049065, 0.045380056, 0.0073883533, 0.03517425, 0.06852329, 0.030208051, 0.058095932, 0.0, 0.02124989, 0.057594478, 0.021417618, 0.083120525, 0.051045954, 0.0, 0.09725523, 0.0, 0.03738928, 0.04717529, 0.056597292, 0.0032580495, 0.02802515, 0.03509587, 0.004929304, 0.004421711, 0.011513412, 0.06430513, 0.06658983, 0.053925753, 0.026837587, 0.023746192, 0.02489829, 0.016504705, 0.018018425, 0.03440416, 0.05698353, 0.024368405, 0.036423564, 0.03606522, 0.015606403, 0.020361662, 0.0077924132, 0.011960506, 0.08466494, 0.029393673, 0.09837204, 0.046794415, 0.028968334, 0.037526906, 0.06507212, 0.018662572, 0.004229009, 0.06039244, 0.02576983, 0.029672801, 0.095044374, 0.08044112, 0.014451563, 0.04869765, 0.039979756, 0.043385804, 0.01368922, 0.056218743, 0.015610516, 0.09385413, 0.0133859515, 0.0, 0.07690114]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  7.3s
computing farthest point 1, dmax: Inf, imax: 23, n: 30
computing farthest point 2, dmax: 1.1572797, imax: 8, n: 30
computing farthest point 3, dmax: 0.9310733, imax: 5, n: 30
computing farthest point 4, dmax: 0.81926346, imax: 4, n: 30
computing farthest point 5, dmax: 0.7767937, imax: 26, n: 30
computing farthest point 6, dmax: 0.7677553, imax: 27, n: 30
computing farthest point 7, dmax: 0.6818455, imax: 10, n: 30
computing farthest point 8, dmax: 0.65844494, imax: 18, n: 30
computing farthest point 9, dmax: 0.64163935, imax: 20, n: 30
computing farthest point 10, dmax: 0.53171057, imax: 17, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.9s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.7s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:04:53.813
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=7, Δ=0.8809524, maxvisits=116) 2025-11-15T11:05:05.131
LOG n.size quantiles:[3.0, 3.0, 3.0, 4.0, 5.0]
(i, j, d) = (7, 273, -1.1920929f-7)
(i, j, d, :parallel) = (7, 273, -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 => 19.007690461000003, :exact => 0.970173595)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  20.5s
  5.931307 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.004533 seconds
SEARCH Exhaustive 2: 0.004557 seconds
SEARCH Exhaustive 3: 0.005393 seconds
typeof(seq) = ExhaustiveSearch{SqL2Distance, MatrixDatabase{Matrix{Float32}}}
typeof(ectx) = GenericContext{KnnSorted}
typeof(q) = SubArray{Float32, 1, Matrix{Float32}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}
typeof(res) = KnnSorted{Vector{IdWeight}}
[ Info: ===================== minrecall ==============================
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:05:33.632
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=10, Δ=1.3720028, maxvisits=246) 2025-11-15T11:05:39.386
LOG n.size quantiles:[3.0, 4.0, 5.0, 6.0, 6.0]
LOG add_vertex! sp=18070 ep=18074 n=18069 BeamSearch(bsize=4, Δ=1.1, maxvisits=356) 2025-11-15T11:05:40.386
LOG n.size quantiles:[5.0, 5.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=32090 ep=32094 n=32089 BeamSearch(bsize=10, Δ=1.025, maxvisits=414) 2025-11-15T11:05:41.386
LOG n.size quantiles:[5.0, 7.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=43355 ep=43359 n=43354 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=400) 2025-11-15T11:05:42.386
LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=54660 ep=54664 n=54659 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=400) 2025-11-15T11:05:43.386
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=64005 ep=64009 n=64004 BeamSearch(bsize=10, Δ=1.0, maxvisits=418) 2025-11-15T11:05:44.386
LOG n.size quantiles:[5.0, 5.0, 5.0, 8.0, 9.0]
LOG add_vertex! sp=75345 ep=75349 n=75344 BeamSearch(bsize=10, Δ=1.0, maxvisits=418) 2025-11-15T11:05:45.387
LOG n.size quantiles:[7.0, 8.0, 9.0, 9.0, 10.0]
LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch(bsize=12, Δ=1.155, maxvisits=488) 2025-11-15T11:05:46.495
LOG n.size quantiles:[5.0, 5.0, 7.0, 7.0, 11.0]
LOG add_vertex! sp=94710 ep=94714 n=94709 BeamSearch(bsize=12, Δ=1.155, maxvisits=488) 2025-11-15T11:05:47.496
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, 8.0, 9.0, 10.0, 11.0, 12.0, 14.0, 17.0, 23.0, 84.0]
[ Info: minrecall: queries per second: 12897.122056222219, recall: 0.90175
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=5, Δ=1.1287501, maxvisits=762))
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, 12.0, 14.0, 17.0, 23.0, 84.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.14, maxvisits=562)), 1000, 8)
[ Info: rebuild: queries per second: 15570.128676992932, recall: 0.902
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.14, maxvisits=562))
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, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.14, maxvisits=762)), 1000, 8)
  1.797192 seconds (610.34 k allocations: 31.097 MiB, 1.76% gc time, 95.77% compilation time)
[ Info: matrixhints: queries per second: 13592.963096994612, recall: 0.90325
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.14, maxvisits=762))
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, 12.0, 14.0, 17.0, 23.0, 84.0]
  2.146790 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.002133 seconds
SEARCH Exhaustive 2: 0.002096 seconds
SEARCH Exhaustive 3: 0.002106 seconds
typeof(seq) = ExhaustiveSearch{SqL2Distance, StrideMatrixDatabase{StrideArraysCore.StrideArray{Float32, 2, (1, 2), Tuple{Int64, Int64}, Tuple{Nothing, Nothing}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}, Matrix{Float32}}}}
typeof(ectx) = GenericContext{KnnSorted}
typeof(q) = StrideArraysCore.StrideArray{Float32, 1, (1,), Tuple{Int64}, Tuple{Nothing}, Tuple{Static.StaticInt{1}}, Matrix{Float32}}
typeof(res) = KnnSorted{Vector{IdWeight}}
[ Info: ===================== minrecall ==============================
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-15T11:06:57.286
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=10, Δ=1.3720028, maxvisits=246) 2025-11-15T11:07:03.232
LOG n.size quantiles:[3.0, 4.0, 5.0, 6.0, 6.0]
LOG add_vertex! sp=21365 ep=21369 n=21364 BeamSearch(bsize=4, Δ=1.1, maxvisits=356) 2025-11-15T11:07:04.232
LOG n.size quantiles:[4.0, 4.0, 6.0, 8.0, 8.0]
LOG add_vertex! sp=36520 ep=36524 n=36519 BeamSearch(bsize=10, Δ=1.025, maxvisits=414) 2025-11-15T11:07:05.232
LOG n.size quantiles:[3.0, 6.0, 7.0, 7.0, 10.0]
LOG add_vertex! sp=49150 ep=49154 n=49149 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=400) 2025-11-15T11:07:06.233
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=60865 ep=60869 n=60864 BeamSearch(bsize=10, Δ=1.0, maxvisits=418) 2025-11-15T11:07:07.233
LOG n.size quantiles:[5.0, 7.0, 7.0, 7.0, 11.0]
LOG add_vertex! sp=73025 ep=73029 n=73024 BeamSearch(bsize=10, Δ=1.0, maxvisits=418) 2025-11-15T11:07:08.233
LOG n.size quantiles:[5.0, 6.0, 6.0, 8.0, 8.0]
LOG add_vertex! sp=83800 ep=83804 n=83799 BeamSearch(bsize=10, Δ=1.0, maxvisits=418) 2025-11-15T11:07:09.233
LOG n.size quantiles:[5.0, 5.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=92930 ep=92934 n=92929 BeamSearch(bsize=12, Δ=1.155, maxvisits=488) 2025-11-15T11:07:10.234
LOG n.size quantiles:[6.0, 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, 12.0, 14.0, 17.0, 23.0, 84.0]
[ Info: minrecall: queries per second: 14125.914873705491, recall: 0.90175
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=5, Δ=1.1287501, maxvisits=762))
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, 12.0, 14.0, 17.0, 23.0, 84.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.14, maxvisits=562)), 1000, 8)
[ Info: rebuild: queries per second: 17793.137130070892, recall: 0.902
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.14, maxvisits=562))
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, 31.0]
[ Info: ===================== matrixhints ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.14, maxvisits=762)), 1000, 8)
  1.560465 seconds (566.25 k allocations: 28.918 MiB, 95.58% compilation time)
[ Info: matrixhints: queries per second: 14521.948211131237, recall: 0.90325
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.14, maxvisits=762))
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, 12.0, 14.0, 17.0, 23.0, 84.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  2m39.8s
     Testing SimilaritySearch tests passed 

Testing completed after 684.56s

PkgEval succeeded after 779.14s