Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.73 (4c8bca6988*) started at 2025-11-13T17:48:31.113 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.71s ################################################################################ # Installation # Installing SimilaritySearch... Resolving package versions... Installed SimilaritySearch ─ v0.13.6 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 5.68s ################################################################################ # 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... 5971.5 ms ✓ SearchModels 14333.4 ms ✓ SimilaritySearch 2 dependencies successfully precompiled in 21 seconds. 66 already precompiled. Precompilation completed after 34.23s ################################################################################ # Testing # Testing SimilaritySearch Status `/tmp/jl_9SXmh6/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_9SXmh6/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 17.2s Test Summary: | Pass Total Time heap | 16 16 0.1s Test Summary: | Pass Total Time KnnHeap | 30005 30005 4.0s Test Summary: | Pass Total Time XKnn | 25005 25005 2.5s Test Summary: | Pass Total Time XKnn pop ops | 9603 9603 1.2s [ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}}) 10.539547 seconds (1000 allocations: 78.125 KiB) 10.954045 seconds (1000 allocations: 78.125 KiB) 4.477597 seconds (1000 allocations: 78.125 KiB) 4.443620 seconds (1000 allocations: 78.125 KiB) 4.386051 seconds (1000 allocations: 78.125 KiB) 4.390271 seconds (1000 allocations: 78.125 KiB) 4.323695 seconds (1000 allocations: 78.125 KiB) 4.305710 seconds (1000 allocations: 78.125 KiB) 15.145438 seconds (1000 allocations: 78.125 KiB) 14.021595 seconds (1000 allocations: 78.125 KiB) 28.445555 seconds (1000 allocations: 78.125 KiB) 28.715308 seconds (1000 allocations: 78.125 KiB) 22.362527 seconds (6.23 k allocations: 358.172 KiB) 22.181987 seconds (1000 allocations: 78.125 KiB) 18.983701 seconds (1.00 k allocations: 78.141 KiB) 18.904933 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing vectors with ExhaustiveSearch | 8000 8000 3m48.7s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 2.973887 seconds (1000 allocations: 78.125 KiB) 2.945621 seconds (1000 allocations: 78.125 KiB) 29.950248 seconds (1000 allocations: 78.125 KiB) 29.183488 seconds (1000 allocations: 78.125 KiB) 29.112079 seconds (1000 allocations: 78.125 KiB) 27.165387 seconds (1000 allocations: 78.125 KiB) 4.273095 seconds (1000 allocations: 78.125 KiB) 4.278551 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing sequences with ExhaustiveSearch | 4000 4000 2m14.1s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 11.144511 seconds (1000 allocations: 78.125 KiB) 11.106277 seconds (1000 allocations: 78.125 KiB) 10.861778 seconds (1000 allocations: 78.125 KiB) 10.900800 seconds (1000 allocations: 78.125 KiB) 11.132727 seconds (1000 allocations: 78.125 KiB) 11.141636 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing sets with ExhaustiveSearch | 3000 3000 1m09.7s 0.052158 seconds (1.00 k allocations: 78.141 KiB) 0.045964 seconds (1000 allocations: 78.125 KiB) 0.040087 seconds (1000 allocations: 78.125 KiB) 0.040624 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time Normalized Cosine and Normalized Angle distances | 2000 2000 2.9s 0.053871 seconds (1000 allocations: 78.125 KiB) 0.059218 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time Binary hamming distance | 1000 1000 1.5s ExhaustiveSearch allknn: 4.188547 seconds (3.13 M allocations: 175.336 MiB, 0.91% gc time, 99.96% compilation time) ParallelExhaustiveSearch allknn: 1.167488 seconds (779.99 k allocations: 42.387 MiB, 2.43% gc time, 99.84% compilation time) Test Summary: | Pass Total Time allknn | 3 3 5.9s 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 3.2s [ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:52.277 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-13T17:57:52.533 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) 2025-11-13T17:57:54.048 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] [ Info: neardup> finished current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:54.457 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000005, 0x0000000b, 0x00000016, 0x0000001c, 0x0000001f, 0x00000023, 0x0000002f, 0x00000031, 0x00000039, 0x00000044] D.nn = Int32[1, 2, 3, 3, 5, 5, 5, 3, 2, 3, 11, 11, 11, 3, 3, 3, 5, 5, 11, 3, 5, 22, 1, 11, 3, 3, 5, 28, 3, 28, 31, 22, 11, 1, 35, 2, 1, 3, 11, 1, 5, 28, 31, 35, 28, 1, 47, 3, 49, 49, 5, 28, 35, 3, 5, 28, 57, 3, 5, 3, 3, 1, 1, 49, 3, 2, 49, 68, 28, 2, 3, 3, 5, 57, 28, 1, 3, 68, 35, 3, 31, 3, 35, 3, 3, 3, 3, 11, 1, 28, 1, 22, 22, 35, 3, 3, 35, 1, 3, 1] D.dist = Float32[0.0, 0.0, 0.0, 0.0139199495, 0.0, 0.030821025, 0.018684804, 0.037145913, 0.0037206411, 0.08094388, 0.0, 0.08617425, 0.07501304, 0.027334988, 0.04192108, 0.034742355, 0.07771599, 0.041122556, 0.013975441, 0.065865934, 0.011721671, 0.0, 0.02565658, 0.023483872, 0.0031101704, 0.02711749, 0.020672798, 0.0, 0.022908568, 0.030019045, 0.0, 0.008645773, 0.050062835, 0.04900539, 0.0, 0.017155468, 0.035856187, 0.07008034, 0.02222848, 0.07921058, 0.016208708, 0.018027782, 0.020107865, 0.08130801, 0.018440962, 0.044035792, 0.0, 0.050645113, 0.0, 0.07480115, 0.026805699, 0.01877898, 0.05457908, 0.00089621544, 0.024983168, 0.04004556, 0.0, 0.026041627, 0.044439793, 0.022093117, 0.036303878, 0.03978604, 0.008612633, 0.003234446, 0.010657012, 0.017598033, 0.015630841, 0.0, 0.052517295, 0.06198162, 0.038528204, 0.03309977, 0.08902514, 0.06765771, 0.023895383, 0.039335668, 0.025614142, 0.027179718, 0.026604474, 0.022731423, 0.035562694, 0.02118057, 0.034476995, 0.073821425, 0.030875921, 0.035594404, 0.028263986, 0.022220314, 0.03974706, 0.006153345, 0.004457772, 0.095734775, 0.07015127, 0.06986201, 0.041954756, 0.033152997, 0.052710593, 0.03374189, 0.016028881, 0.038952947] Test Summary: | Pass Total Time neardup single block | 3 3 19.3s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-13T17:57:55.402 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: 2025-11-13T17:57:55.402 [ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 [ Info: neardup> range: 49:64, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 [ Info: neardup> range: 65:80, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 [ Info: neardup> range: 81:96, current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 [ Info: neardup> range: 97:100, current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 [ Info: neardup> finished current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.402 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000005, 0x0000000b, 0x00000016, 0x0000001c, 0x0000001f, 0x00000023, 0x0000002f, 0x00000031, 0x00000039, 0x00000044] D.nn = Int32[1, 2, 3, 3, 5, 5, 5, 3, 2, 3, 11, 11, 11, 3, 3, 3, 5, 5, 11, 3, 5, 22, 1, 11, 3, 3, 5, 28, 3, 28, 31, 22, 11, 1, 35, 2, 1, 3, 11, 1, 5, 28, 31, 35, 28, 1, 47, 3, 49, 2, 5, 28, 35, 3, 5, 28, 57, 3, 5, 3, 3, 1, 1, 49, 3, 2, 49, 68, 28, 2, 3, 3, 5, 57, 28, 1, 3, 11, 35, 3, 31, 3, 35, 3, 3, 3, 3, 11, 1, 28, 1, 22, 22, 35, 3, 3, 35, 1, 3, 1] D.dist = Float32[0.0, 0.0, 0.0, 0.0139199495, 0.0, 0.030821025, 0.018684804, 0.037145913, 0.0037206411, 0.08094388, 0.0, 0.08617425, 0.07501304, 0.027334988, 0.04192108, 0.034742355, 0.07771599, 0.041122556, 0.013975441, 0.065865934, 0.011721671, 0.0, 0.02565658, 0.023483872, 0.0031101704, 0.02711749, 0.020672798, 0.0, 0.022908568, 0.030019045, 0.0, 0.008645773, 0.050062835, 0.04900539, 0.0, 0.017155468, 0.035856187, 0.07008034, 0.02222848, 0.07921058, 0.016208708, 0.018027782, 0.020107865, 0.08130801, 0.018440962, 0.044035792, 0.0, 0.050645113, 0.0, 0.08678621, 0.026805699, 0.01877898, 0.05457908, 0.00089621544, 0.024983168, 0.04004556, 0.0, 0.026041627, 0.044439793, 0.022093117, 0.036303878, 0.03978604, 0.008612633, 0.003234446, 0.010657012, 0.017598033, 0.015630841, 0.0, 0.052517295, 0.06198162, 0.038528204, 0.03309977, 0.08902514, 0.06765771, 0.023895383, 0.039335668, 0.025614142, 0.05154234, 0.026604474, 0.022731423, 0.035562694, 0.02118057, 0.034476995, 0.073821425, 0.030875921, 0.035594404, 0.028263986, 0.022220314, 0.03974706, 0.006153345, 0.004457772, 0.095734775, 0.07015127, 0.06986201, 0.041954756, 0.033152997, 0.052710593, 0.03374189, 0.016028881, 0.038952947] 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: 2025-11-13T17:57:55.473 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-13T17:57:55.473 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: 2025-11-13T17:57:55.473 [ Info: neardup> range: 33:48, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.473 [ Info: neardup> range: 49:64, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.474 [ Info: neardup> range: 65:80, current elements: 22, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.474 [ Info: neardup> range: 81:96, current elements: 23, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.474 [ Info: neardup> range: 97:100, current elements: 23, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.474 [ Info: neardup> finished current elements: 23, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:57:55.474 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000016, 0x0000001c, 0x00000020, 0x0000002f, 0x00000031, 0x00000040, 0x0000004a] D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 6, 6, 11, 10, 7, 22, 1, 11, 3, 16, 5, 28, 3, 12, 16, 32, 16, 8, 8, 9, 1, 8, 11, 1, 5, 28, 16, 13, 28, 15, 47, 15, 49, 9, 7, 28, 16, 3, 9, 15, 7, 14, 7, 4, 3, 1, 1, 64, 4, 2, 49, 12, 28, 7, 4, 10, 6, 74, 28, 6, 8, 13, 8, 8, 3, 3, 22, 10, 3, 16, 15, 11, 7, 28, 1, 22, 16, 13, 15, 8, 15, 1, 3, 1] 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, 0.052925527, 0.004311323, 0.013975441, 0.035073698, 0.005444169, 0.0, 0.02565658, 0.023483872, 0.0031101704, 0.019401431, 0.020672798, 0.0, 0.022908568, 0.05916637, 0.08661997, 0.0, 0.029820979, 0.027956545, 0.039773345, 0.014252961, 0.035856187, 0.025088191, 0.02222848, 0.07921058, 0.016208708, 0.018027782, 0.08436537, 0.08518249, 0.018440962, 0.03152752, 0.0, 0.012566149, 0.0, 0.07388878, 0.013011396, 0.01877898, 0.038020194, 0.00089621544, 0.0132731795, 0.039200544, 0.09971297, 0.013755202, 0.009082377, 0.0036337972, 0.036303878, 0.03978604, 0.008612633, 0.0, 0.0012330413, 0.017598033, 0.015630841, 0.006219864, 0.052517295, 0.04427868, 0.030442238, 0.030972958, 0.030166447, 0.0, 0.023895383, 0.025033891, 0.0065641403, 0.013752997, 0.009599328, 0.008035064, 0.051465154, 0.02118057, 0.039283037, 0.068172455, 0.030875921, 0.012685835, 0.026330054, 0.022220314, 0.012686789, 0.006153345, 0.004457772, 0.095734775, 0.069775105, 0.072880566, 0.01599431, 0.0003861785, 0.038047075, 0.03374189, 0.016028881, 0.038952947] 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: 2025-11-13T17:58:02.486 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=5 n=5 2025-11-13T17:58:02.487 [ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 [ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 [ Info: neardup> range: 49:64, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 [ Info: neardup> range: 65:80, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 [ Info: neardup> range: 81:96, current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 [ Info: neardup> range: 97:100, current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 [ Info: neardup> finished current elements: 13, n: 100, ϵ: 0.1, timestamp: 2025-11-13T17:58:02.494 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000005, 0x0000000b, 0x00000016, 0x0000001c, 0x0000001f, 0x00000023, 0x0000002f, 0x00000031, 0x00000039, 0x00000044] D.nn = Int32[1, 2, 3, 3, 5, 5, 5, 3, 2, 3, 11, 11, 11, 3, 3, 3, 5, 5, 11, 3, 5, 22, 1, 11, 3, 3, 5, 28, 3, 28, 31, 22, 11, 1, 35, 2, 1, 3, 11, 1, 5, 28, 31, 35, 28, 1, 47, 3, 49, 2, 5, 28, 35, 3, 5, 28, 57, 3, 5, 3, 3, 1, 1, 49, 3, 2, 49, 68, 28, 2, 3, 3, 5, 57, 28, 1, 3, 11, 35, 3, 31, 3, 35, 3, 3, 3, 3, 11, 1, 28, 1, 22, 22, 35, 3, 3, 35, 1, 3, 1] D.dist = Float32[0.0, 0.0, 0.0, 0.0139199495, 0.0, 0.030821025, 0.018684804, 0.037145913, 0.0037206411, 0.08094388, 0.0, 0.08617425, 0.07501304, 0.027334988, 0.04192108, 0.034742355, 0.07771599, 0.041122556, 0.013975441, 0.065865934, 0.011721671, 0.0, 0.02565658, 0.023483872, 0.0031101704, 0.02711749, 0.020672798, 0.0, 0.022908568, 0.030019045, 0.0, 0.008645773, 0.050062835, 0.04900539, 0.0, 0.017155468, 0.035856187, 0.07008034, 0.02222848, 0.07921058, 0.016208708, 0.018027782, 0.020107865, 0.08130801, 0.018440962, 0.044035792, 0.0, 0.050645113, 0.0, 0.08678621, 0.026805699, 0.01877898, 0.05457908, 0.00089621544, 0.024983168, 0.04004556, 0.0, 0.026041627, 0.044439793, 0.022093117, 0.036303878, 0.03978604, 0.008612633, 0.003234446, 0.010657012, 0.017598033, 0.015630841, 0.0, 0.052517295, 0.06198162, 0.038528204, 0.03309977, 0.08902514, 0.06765771, 0.023895383, 0.039335668, 0.025614142, 0.05154234, 0.026604474, 0.022731423, 0.035562694, 0.02118057, 0.034476995, 0.073821425, 0.030875921, 0.035594404, 0.028263986, 0.022220314, 0.03974706, 0.006153345, 0.004457772, 0.095734775, 0.07015127, 0.06986201, 0.041954756, 0.033152997, 0.052710593, 0.03374189, 0.016028881, 0.038952947] Test Summary: | Pass Total Time neardup small block with filterblocks=false | 3 3 7.0s computing farthest point 1, dmax: Inf, imax: 18, n: 30 computing farthest point 2, dmax: 0.9525957, imax: 24, n: 30 computing farthest point 3, dmax: 0.9336189, imax: 20, n: 30 computing farthest point 4, dmax: 0.7705624, imax: 28, n: 30 computing farthest point 5, dmax: 0.75929064, imax: 8, n: 30 computing farthest point 6, dmax: 0.7364376, imax: 17, n: 30 computing farthest point 7, dmax: 0.5885819, imax: 22, n: 30 computing farthest point 8, dmax: 0.55949694, imax: 21, n: 30 computing farthest point 9, dmax: 0.53341913, imax: 23, n: 30 computing farthest point 10, dmax: 0.5281991, imax: 25, n: 30 Test Summary: | Pass Total Time farthest first traversal | 3 3 1.6s 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) 2025-11-13T17:58:11.196 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=0.97619045, maxvisits=120) 2025-11-13T17:58:23.302 LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 5.0] (i, j, d) = (15, 796, -1.1920929f-7) (i, j, d, :parallel) = (15, 796, -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 => 20.048354748, :exact => 1.016475428) Test Summary: | Pass Total Time closestpair | 4 4 21.6s 5.878205 seconds (1.00 k allocations: 140.711 KiB) SEARCH Exhaustive 1: 0.004799 seconds SEARCH Exhaustive 2: 0.005026 seconds SEARCH Exhaustive 3: 0.005636 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) 2025-11-13T17:58:52.711 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=1.244447, maxvisits=246) 2025-11-13T17:58:58.663 LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=16800 ep=16804 n=16799 BeamSearch(bsize=16, Δ=1.075, maxvisits=360) 2025-11-13T17:58:59.663 LOG n.size quantiles:[4.0, 4.0, 5.0, 6.0, 8.0] LOG add_vertex! sp=30025 ep=30029 n=30024 BeamSearch(bsize=9, Δ=1.2733874, maxvisits=396) 2025-11-13T17:59:00.663 LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 9.0] LOG add_vertex! sp=40910 ep=40914 n=40909 BeamSearch(bsize=12, Δ=1.1, maxvisits=450) 2025-11-13T17:59:01.664 LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=52570 ep=52574 n=52569 BeamSearch(bsize=12, Δ=1.1, maxvisits=450) 2025-11-13T17:59:02.664 LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 8.0] LOG add_vertex! sp=60360 ep=60364 n=60359 BeamSearch(bsize=14, Δ=1.2733874, maxvisits=470) 2025-11-13T17:59:03.664 LOG n.size quantiles:[5.0, 5.0, 8.0, 9.0, 11.0] LOG add_vertex! sp=69410 ep=69414 n=69409 BeamSearch(bsize=14, Δ=1.2733874, maxvisits=470) 2025-11-13T17:59:04.665 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0] LOG add_vertex! sp=77800 ep=77804 n=77799 BeamSearch(bsize=14, Δ=1.2733874, maxvisits=470) 2025-11-13T17:59:05.665 LOG n.size quantiles:[4.0, 8.0, 8.0, 9.0, 9.0] LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch(bsize=16, Δ=1.05, maxvisits=510) 2025-11-13T17:59:06.719 LOG n.size quantiles:[5.0, 8.0, 8.0, 8.0, 9.0] LOG add_vertex! sp=95030 ep=95034 n=95029 BeamSearch(bsize=16, Δ=1.05, maxvisits=510) 2025-11-13T17:59:07.719 LOG n.size quantiles:[5.0, 7.0, 7.0, 8.0, 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, 90.0] [ Info: minrecall: queries per second: 13403.491856252804, recall: 0.904625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=16, Δ=1.1287501, maxvisits=770)) 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, 90.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=548)), 1000, 8) [ Info: rebuild: queries per second: 15267.065090246522, recall: 0.89725 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=548)) 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=10, Δ=1.1025, maxvisits=770)), 1000, 8) 2.034299 seconds (809.42 k allocations: 44.416 MiB, 95.86% compilation time) [ Info: matrixhints: queries per second: 12062.18883397631, recall: 0.898875 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.1025, maxvisits=770)) 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, 90.0] 2.207999 seconds (1.00 k allocations: 140.711 KiB) SEARCH Exhaustive 1: 0.001950 seconds SEARCH Exhaustive 2: 0.001944 seconds SEARCH Exhaustive 3: 0.002031 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) 2025-11-13T18:00:22.610 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=1.244447, maxvisits=246) 2025-11-13T18:00:28.338 LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=26850 ep=26854 n=26849 BeamSearch(bsize=9, Δ=1.2733874, maxvisits=396) 2025-11-13T18:00:29.338 LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 7.0] LOG add_vertex! sp=47640 ep=47644 n=47639 BeamSearch(bsize=12, Δ=1.1, maxvisits=450) 2025-11-13T18:00:30.338 LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 9.0] LOG add_vertex! sp=64565 ep=64569 n=64564 BeamSearch(bsize=14, Δ=1.2733874, maxvisits=470) 2025-11-13T18:00:31.338 LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 7.0] LOG add_vertex! sp=79890 ep=79894 n=79889 BeamSearch(bsize=14, Δ=1.2733874, maxvisits=470) 2025-11-13T18:00:32.338 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0] LOG add_vertex! sp=95570 ep=95574 n=95569 BeamSearch(bsize=16, Δ=1.05, maxvisits=510) 2025-11-13T18:00:33.338 LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 7.0] 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, 90.0] [ Info: minrecall: queries per second: 23126.8553808815, recall: 0.904625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=16, Δ=1.1287501, maxvisits=770)) 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, 90.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=548)), 1000, 8) [ Info: rebuild: queries per second: 16532.042388024427, recall: 0.89725 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.13, maxvisits=548)) 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=10, Δ=1.1025, maxvisits=770)), 1000, 8) 1.516411 seconds (754.89 k allocations: 41.309 MiB, 95.44% compilation time) [ Info: matrixhints: queries per second: 14645.12082349163, recall: 0.898875 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.1025, maxvisits=770)) 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, 90.0] Test Summary: | Pass Total Time vector indexing with SearchGraph | 18 18 2m41.5s Testing SimilaritySearch tests passed Testing completed after 704.09s PkgEval succeeded after 768.89s