Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.71 (9f595ebbf8*) started at 2025-11-14T11:01:10.033


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.42s


################################################################################
# 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 5.01s


################################################################################
# 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...
   5838.0 ms  ✓ SearchModels
  14278.6 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 23 seconds. 66 already precompiled.

Precompilation completed after 33.37s


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

     Testing SimilaritySearch
      Status `/tmp/jl_GVGVoK/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_GVGVoK/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  17.3s
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  2.5s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.1s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
 10.112713 seconds (1000 allocations: 78.125 KiB)
 10.150871 seconds (1000 allocations: 78.125 KiB)
  3.868503 seconds (1000 allocations: 78.125 KiB)
  4.038645 seconds (1000 allocations: 78.125 KiB)
  4.232788 seconds (1000 allocations: 78.125 KiB)
  3.998712 seconds (1000 allocations: 78.125 KiB)
  4.101342 seconds (1000 allocations: 78.125 KiB)
  4.052018 seconds (1000 allocations: 78.125 KiB)
 15.571222 seconds (1000 allocations: 78.125 KiB)
 15.288094 seconds (1000 allocations: 78.125 KiB)
 27.969062 seconds (1000 allocations: 78.125 KiB)
 27.668498 seconds (1000 allocations: 78.125 KiB)
 20.961157 seconds (6.23 k allocations: 358.094 KiB)
 20.418538 seconds (1000 allocations: 78.125 KiB)
 17.186870 seconds (1.00 k allocations: 78.141 KiB)
 17.038487 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m38.7s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.340468 seconds (1000 allocations: 78.125 KiB)
  3.336868 seconds (1000 allocations: 78.125 KiB)
 28.334780 seconds (1000 allocations: 78.125 KiB)
 28.116128 seconds (1000 allocations: 78.125 KiB)
 27.132324 seconds (1000 allocations: 78.125 KiB)
 26.393702 seconds (1000 allocations: 78.125 KiB)
  3.152379 seconds (1000 allocations: 78.125 KiB)
  3.990101 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m07.3s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 11.203221 seconds (1000 allocations: 78.125 KiB)
 11.011567 seconds (1000 allocations: 78.125 KiB)
 10.936347 seconds (1000 allocations: 78.125 KiB)
 10.722911 seconds (1000 allocations: 78.125 KiB)
 10.574617 seconds (1000 allocations: 78.125 KiB)
  9.481786 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m06.7s
  0.045469 seconds (1.00 k allocations: 78.141 KiB)
  0.045308 seconds (1000 allocations: 78.125 KiB)
  0.042071 seconds (1000 allocations: 78.125 KiB)
  0.040276 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  2.8s
  0.055089 seconds (1000 allocations: 78.125 KiB)
  0.054495 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.5s
ExhaustiveSearch allknn: 4.056914 seconds (3.28 M allocations: 180.138 MiB, 0.99% gc time, 99.96% compilation time)
ParallelExhaustiveSearch allknn: 1.214421 seconds (821.76 k allocations: 43.789 MiB, 2.54% gc time, 99.85% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  5.8s
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: 2025-11-14T11:10:10.312
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-14T11:10:10.549
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) 2025-11-14T11:10:11.998
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: 2025-11-14T11:10:12.380
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x0000000d, 0x0000000f, 0x00000013, 0x00000014, 0x00000016, 0x00000018, 0x00000019]
D.nn = Int32[1, 2, 3, 4, 4, 4, 4, 1, 4, 3, 4, 3, 13, 3, 15, 4, 4, 13, 19, 20, 2, 22, 13, 24, 25, 13, 20, 20, 15, 1, 15, 15, 4, 13, 1, 15, 13, 3, 15, 13, 22, 20, 2, 13, 20, 4, 2, 3, 4, 15, 13, 4, 25, 24, 2, 1, 19, 22, 15, 3, 2, 15, 13, 2, 2, 24, 20, 1, 2, 13, 4, 13, 13, 4, 2, 15, 1, 15, 13, 22, 24, 3, 13, 22, 13, 13, 13, 4, 15, 4, 20, 13, 2, 3, 15, 15, 4, 20, 24, 13]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.04358673, 0.09421384, 0.055927813, 0.019616008, 0.07765782, 0.06462574, 0.014896691, 0.055969715, 0.0, 0.02181679, 0.0, 0.014973998, 0.03847742, 0.053075075, 0.0, 0.0, 0.030365646, 0.0, 0.027238965, 0.0, 0.0, 0.031493783, 0.041055977, 0.047375858, 0.049868405, 0.02818662, 0.044126034, 0.019966483, 0.053742707, 0.037217915, 0.03785664, 0.01204282, 0.039766133, 0.009146452, 0.055598736, 0.016111314, 0.010103703, 0.044969857, 0.023502529, 0.014345765, 0.051549673, 0.032530725, 0.07029331, 0.010123789, 0.041842878, 0.059268713, 0.03808564, 0.035757005, 0.017501354, 0.068627596, 0.024322748, 0.073728025, 0.046702325, 0.02682352, 0.03614843, 0.0770278, 0.029699802, 0.050411284, 0.04707253, 0.046815217, 0.031942606, 0.006958127, 0.05601698, 0.025277913, 0.018019319, 0.01925522, 0.040681064, 0.029003441, 0.027977288, 0.020309508, 0.013632417, 0.05408615, 0.05332917, 0.008160472, 0.031037271, 0.04054886, 0.036915004, 0.0627864, 0.02386576, 0.023839474, 0.020932078, 0.023591518, 0.078918576, 0.06297517, 0.05267787, 0.010022581, 0.09758037, 0.006947458, 0.06050551, 0.028184354, 0.04155773, 0.052965224, 0.0674957, 0.019363761, 0.033328593, 0.052013993]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  18.9s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.499
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-14T11:10:13.500
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.501
[ Info: neardup> range: 33:48, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.501
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.502
[ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.502
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.502
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.502
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.502
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x0000000d, 0x0000000f, 0x00000013, 0x00000014, 0x00000016, 0x00000018, 0x00000019]
D.nn = Int32[1, 2, 3, 4, 4, 4, 4, 1, 4, 3, 4, 3, 13, 3, 15, 4, 4, 13, 19, 20, 2, 22, 13, 24, 25, 13, 2, 20, 15, 1, 15, 15, 4, 13, 1, 15, 13, 3, 15, 13, 22, 20, 2, 13, 20, 4, 2, 3, 4, 15, 13, 4, 25, 24, 2, 1, 19, 22, 15, 3, 2, 15, 13, 2, 2, 24, 20, 1, 2, 13, 4, 13, 13, 4, 2, 15, 1, 15, 13, 22, 24, 3, 13, 22, 13, 13, 13, 4, 15, 4, 20, 13, 2, 3, 15, 15, 4, 20, 24, 13]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.04358673, 0.09421384, 0.055927813, 0.019616008, 0.07765782, 0.06462574, 0.014896691, 0.055969715, 0.0, 0.02181679, 0.0, 0.014973998, 0.03847742, 0.053075075, 0.0, 0.0, 0.030365646, 0.0, 0.027238965, 0.0, 0.0, 0.031493783, 0.069251, 0.047375858, 0.049868405, 0.02818662, 0.044126034, 0.019966483, 0.053742707, 0.037217915, 0.03785664, 0.01204282, 0.039766133, 0.009146452, 0.055598736, 0.016111314, 0.010103703, 0.044969857, 0.023502529, 0.014345765, 0.051549673, 0.032530725, 0.07029331, 0.010123789, 0.041842878, 0.059268713, 0.03808564, 0.035757005, 0.017501354, 0.068627596, 0.024322748, 0.073728025, 0.046702325, 0.02682352, 0.03614843, 0.0770278, 0.029699802, 0.050411284, 0.04707253, 0.046815217, 0.031942606, 0.006958127, 0.05601698, 0.025277913, 0.018019319, 0.01925522, 0.040681064, 0.029003441, 0.027977288, 0.020309508, 0.013632417, 0.05408615, 0.05332917, 0.008160472, 0.031037271, 0.04054886, 0.036915004, 0.0627864, 0.02386576, 0.023839474, 0.020932078, 0.023591518, 0.078918576, 0.06297517, 0.05267787, 0.010022581, 0.09758037, 0.006947458, 0.06050551, 0.028184354, 0.04155773, 0.052965224, 0.0674957, 0.019363761, 0.033328593, 0.052013993]
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: 2025-11-14T11:10:13.591
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-14T11:10:13.591
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: 2025-11-14T11:10:13.592
[ Info: neardup> range: 33:48, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.592
[ Info: neardup> range: 49:64, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.592
[ Info: neardup> range: 65:80, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.592
[ Info: neardup> range: 81:96, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.592
[ Info: neardup> range: 97:100, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.593
[ Info: neardup> finished current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:13.593
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000014, 0x00000016, 0x00000018, 0x00000019, 0x0000001c]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 11, 13, 16, 20, 2, 22, 13, 24, 25, 13, 2, 28, 9, 1, 12, 15, 10, 13, 1, 12, 13, 3, 15, 13, 22, 20, 2, 13, 7, 5, 2, 3, 4, 15, 9, 5, 25, 12, 2, 28, 7, 22, 15, 10, 9, 15, 9, 9, 7, 24, 7, 8, 2, 13, 4, 13, 13, 4, 2, 15, 1, 15, 13, 22, 24, 14, 13, 22, 13, 13, 13, 7, 15, 4, 20, 13, 2, 12, 6, 15, 4, 20, 24, 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, 0.0076159835, 0.053075075, 0.066089034, 0.0, 0.030365646, 0.0, 0.027238965, 0.0, 0.0, 0.031493783, 0.069251, 0.0, 0.0022482872, 0.02818662, 0.02144885, 0.019966483, 0.021404624, 0.037217915, 0.03785664, 0.01160717, 0.039766133, 0.009146452, 0.055598736, 0.016111314, 0.010103703, 0.044969857, 0.023502529, 0.014345765, 0.01985854, 0.019756794, 0.07029331, 0.010123789, 0.041842878, 0.059268713, 0.025024712, 0.008389115, 0.017501354, 0.06664413, 0.024322748, 0.05706477, 0.014149547, 0.02682352, 0.03614843, 0.007470846, 0.022795796, 0.050411284, 0.005430877, 0.011169493, 0.014976144, 0.006958127, 0.024322689, 0.011250615, 0.018019319, 0.01925522, 0.040681064, 0.029003441, 0.027977288, 0.020309508, 0.013632417, 0.05408615, 0.05332917, 0.008160472, 0.031037271, 0.04054886, 0.036915004, 0.019878685, 0.02386576, 0.023839474, 0.020932078, 0.023591518, 0.078918576, 0.042116404, 0.05267787, 0.010022581, 0.09758037, 0.006947458, 0.06050551, 0.010591567, 0.020694256, 0.052965224, 0.0674957, 0.019363761, 0.033328593, 0.023227751]
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: 2025-11-14T11:10:20.355
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=6 n=6 2025-11-14T11:10:20.355
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
[ Info: neardup> range: 33:48, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
[ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-11-14T11:10:20.362
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x0000000d, 0x0000000f, 0x00000013, 0x00000014, 0x00000016, 0x00000018, 0x00000019]
D.nn = Int32[1, 2, 3, 4, 4, 4, 4, 1, 4, 3, 4, 3, 13, 3, 15, 4, 4, 13, 19, 20, 2, 22, 13, 24, 25, 13, 2, 20, 15, 1, 15, 15, 4, 13, 1, 15, 13, 3, 15, 13, 22, 20, 2, 13, 20, 4, 2, 3, 4, 15, 13, 4, 25, 24, 2, 1, 19, 22, 15, 3, 2, 15, 13, 2, 2, 24, 20, 1, 2, 13, 4, 13, 13, 4, 2, 15, 1, 15, 13, 22, 24, 3, 13, 22, 13, 13, 13, 4, 15, 4, 20, 13, 2, 3, 15, 15, 4, 20, 24, 13]
D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.04358673, 0.09421384, 0.055927813, 0.019616008, 0.07765782, 0.06462574, 0.014896691, 0.055969715, 0.0, 0.02181679, 0.0, 0.014973998, 0.03847742, 0.053075075, 0.0, 0.0, 0.030365646, 0.0, 0.027238965, 0.0, 0.0, 0.031493783, 0.069251, 0.047375858, 0.049868405, 0.02818662, 0.044126034, 0.019966483, 0.053742707, 0.037217915, 0.03785664, 0.01204282, 0.039766133, 0.009146452, 0.055598736, 0.016111314, 0.010103703, 0.044969857, 0.023502529, 0.014345765, 0.051549673, 0.032530725, 0.07029331, 0.010123789, 0.041842878, 0.059268713, 0.03808564, 0.035757005, 0.017501354, 0.068627596, 0.024322748, 0.073728025, 0.046702325, 0.02682352, 0.03614843, 0.0770278, 0.029699802, 0.050411284, 0.04707253, 0.046815217, 0.031942606, 0.006958127, 0.05601698, 0.025277913, 0.018019319, 0.01925522, 0.040681064, 0.029003441, 0.027977288, 0.020309508, 0.013632417, 0.05408615, 0.05332917, 0.008160472, 0.031037271, 0.04054886, 0.036915004, 0.0627864, 0.02386576, 0.023839474, 0.020932078, 0.023591518, 0.078918576, 0.06297517, 0.05267787, 0.010022581, 0.09758037, 0.006947458, 0.06050551, 0.028184354, 0.04155773, 0.052965224, 0.0674957, 0.019363761, 0.033328593, 0.052013993]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  6.8s
computing farthest point 1, dmax: Inf, imax: 3, n: 30
computing farthest point 2, dmax: 1.3860605, imax: 8, n: 30
computing farthest point 3, dmax: 0.90425444, imax: 27, n: 30
computing farthest point 4, dmax: 0.8596227, imax: 18, n: 30
computing farthest point 5, dmax: 0.83488977, imax: 22, n: 30
computing farthest point 6, dmax: 0.74337846, imax: 26, n: 30
computing farthest point 7, dmax: 0.72689563, imax: 19, n: 30
computing farthest point 8, dmax: 0.57190925, imax: 7, n: 30
computing farthest point 9, dmax: 0.56767935, imax: 13, n: 30
computing farthest point 10, dmax: 0.54735893, imax: 15, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.6s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.6s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-14T11:10:29.028
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=2, Δ=0.861678, maxvisits=108) 2025-11-14T11:10:39.850
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 4.0]
(i, j, d) = (11, 620, -1.1920929f-7)
(i, j, d, :parallel) = (11, 620, -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 => 18.55283168, :exact => 0.963449514)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  20.0s
  6.245067 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.004869 seconds
SEARCH Exhaustive 2: 0.004848 seconds
SEARCH Exhaustive 3: 0.005485 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) 2025-11-14T11:11:08.496
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=16, Δ=0.975, maxvisits=208) 2025-11-14T11:11:13.558
LOG n.size quantiles:[3.0, 5.0, 5.0, 5.0, 6.0]
LOG add_vertex! sp=18155 ep=18159 n=18154 BeamSearch(bsize=8, Δ=1.075, maxvisits=410) 2025-11-14T11:11:14.558
LOG n.size quantiles:[5.0, 5.0, 5.0, 6.0, 7.0]
LOG add_vertex! sp=31475 ep=31479 n=31474 BeamSearch(bsize=7, Δ=1.1851876, maxvisits=414) 2025-11-14T11:11:15.559
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 7.0]
LOG add_vertex! sp=42200 ep=42204 n=42199 BeamSearch(bsize=8, Δ=1.1, maxvisits=440) 2025-11-14T11:11:16.559
LOG n.size quantiles:[5.0, 6.0, 6.0, 8.0, 8.0]
LOG add_vertex! sp=53280 ep=53284 n=53279 BeamSearch(bsize=8, Δ=1.1, maxvisits=440) 2025-11-14T11:11:17.559
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=61530 ep=61534 n=61529 BeamSearch(bsize=14, Δ=1.075, maxvisits=440) 2025-11-14T11:11:18.598
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 10.0]
LOG add_vertex! sp=71420 ep=71424 n=71419 BeamSearch(bsize=14, Δ=1.075, maxvisits=440) 2025-11-14T11:11:19.599
LOG n.size quantiles:[4.0, 7.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=80835 ep=80839 n=80834 BeamSearch(bsize=14, Δ=1.075, maxvisits=440) 2025-11-14T11:11:20.599
LOG n.size quantiles:[3.0, 4.0, 5.0, 7.0, 9.0]
LOG add_vertex! sp=88015 ep=88019 n=88014 BeamSearch(bsize=15, Δ=1.155, maxvisits=566) 2025-11-14T11:11:21.599
LOG n.size quantiles:[5.0, 5.0, 7.0, 9.0, 11.0]
LOG add_vertex! sp=96470 ep=96474 n=96469 BeamSearch(bsize=15, Δ=1.155, maxvisits=566) 2025-11-14T11:11:22.599
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, 13.0, 15.0, 18.0, 23.0, 96.0]
[ Info: minrecall: queries per second: 12956.138676807697, recall: 0.901625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=9, Δ=1.1, maxvisits=726))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 96.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.16, maxvisits=608)), 1000, 8)
[ Info: rebuild: queries per second: 14185.383097548623, recall: 0.897375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.16, maxvisits=608))
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(bsize=11, Δ=1.09, maxvisits=736)), 1000, 8)
  1.800593 seconds (873.24 k allocations: 46.425 MiB, 95.78% compilation time)
[ Info: matrixhints: queries per second: 13682.196694192464, recall: 0.898875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=11, Δ=1.09, maxvisits=736))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 96.0]
  2.203332 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.001934 seconds
SEARCH Exhaustive 2: 0.001948 seconds
SEARCH Exhaustive 3: 0.002001 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) 2025-11-14T11:12:34.727
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=16, Δ=0.975, maxvisits=208) 2025-11-14T11:12:39.287
LOG n.size quantiles:[3.0, 5.0, 5.0, 5.0, 6.0]
LOG add_vertex! sp=24935 ep=24939 n=24934 BeamSearch(bsize=8, Δ=1.075, maxvisits=410) 2025-11-14T11:12:40.288
LOG n.size quantiles:[5.0, 6.0, 6.0, 6.0, 7.0]
LOG add_vertex! sp=40590 ep=40594 n=40589 BeamSearch(bsize=8, Δ=1.1, maxvisits=440) 2025-11-14T11:12:41.288
LOG n.size quantiles:[5.0, 7.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=53705 ep=53709 n=53704 BeamSearch(bsize=8, Δ=1.1, maxvisits=440) 2025-11-14T11:12:42.288
LOG n.size quantiles:[3.0, 5.0, 7.0, 9.0, 9.0]
LOG add_vertex! sp=64660 ep=64664 n=64659 BeamSearch(bsize=14, Δ=1.075, maxvisits=440) 2025-11-14T11:12:43.288
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=76820 ep=76824 n=76819 BeamSearch(bsize=14, Δ=1.075, maxvisits=440) 2025-11-14T11:12:44.288
LOG n.size quantiles:[4.0, 5.0, 5.0, 6.0, 7.0]
LOG add_vertex! sp=86580 ep=86584 n=86579 BeamSearch(bsize=15, Δ=1.155, maxvisits=566) 2025-11-14T11:12:45.289
LOG n.size quantiles:[6.0, 8.0, 8.0, 9.0, 10.0]
LOG add_vertex! sp=96475 ep=96479 n=96474 BeamSearch(bsize=15, Δ=1.155, maxvisits=566) 2025-11-14T11:12:46.289
LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 96.0]
[ Info: minrecall: queries per second: 14044.257190178665, recall: 0.901625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=9, Δ=1.1, maxvisits=726))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 96.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.16, maxvisits=608)), 1000, 8)
[ Info: rebuild: queries per second: 16244.82774837509, recall: 0.897375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=7, Δ=1.16, maxvisits=608))
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(bsize=11, Δ=1.09, maxvisits=736)), 1000, 8)
  1.581045 seconds (812.55 k allocations: 43.147 MiB, 3.98% gc time, 96.06% compilation time)
[ Info: matrixhints: queries per second: 15949.427300724028, recall: 0.898875
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=11, Δ=1.09, maxvisits=736))
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 96.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  2m39.7s
     Testing SimilaritySearch tests passed 

Testing completed after 679.16s

PkgEval succeeded after 747.84s