Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.50 (b60d1db399*) started at 2025-11-09T17:48:00.374 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.91s ################################################################################ # Installation # Installing SimilaritySearch... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [053f045d] + SimilaritySearch v0.13.5 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 v0.13.5 [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 4.45s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... ┌ Error: Failed to use TestEnv.jl; test dependencies will not be precompiled │ exception = │ UndefVarError: `project_rel_path` not defined in `TestEnv` │ Suggestion: this global was defined as `Pkg.Operations.project_rel_path` but not assigned a value. │ Stacktrace: │ [1] get_test_dir(ctx::Pkg.Types.Context, pkgspec::PackageSpec) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:75 │ [2] test_dir_has_project_file │ @ ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:52 [inlined] │ [3] maybe_gen_project_override! │ @ ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:83 [inlined] │ [4] activate(pkg::String; allow_reresolve::Bool) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:12 │ [5] activate(pkg::String) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/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... 5590.0 ms ✓ SearchModels 14319.9 ms ✓ SimilaritySearch 2 dependencies successfully precompiled in 21 seconds. 66 already precompiled. Precompilation completed after 33.82s ################################################################################ # Testing # Testing SimilaritySearch Status `/tmp/jl_Tje3Vb/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 v0.13.5 [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_Tje3Vb/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 v0.13.5 [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 17.1s Test Summary: | Pass Total Time heap | 16 16 0.1s Test Summary: | Pass Total Time KnnHeap | 30005 30005 3.5s Test Summary: | Pass Total Time XKnn | 25005 25005 2.3s Test Summary: | Pass Total Time XKnn pop ops | 9603 9603 1.1s [ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}}) 9.244831 seconds (1000 allocations: 78.125 KiB) 11.152335 seconds (1000 allocations: 78.125 KiB) 3.779335 seconds (1000 allocations: 78.125 KiB) 4.102893 seconds (1000 allocations: 78.125 KiB) 3.781791 seconds (1000 allocations: 78.125 KiB) 4.006838 seconds (1000 allocations: 78.125 KiB) 3.660948 seconds (1000 allocations: 78.125 KiB) 3.794676 seconds (1000 allocations: 78.125 KiB) 15.615855 seconds (1000 allocations: 78.125 KiB) 15.929995 seconds (1000 allocations: 78.125 KiB) 28.445072 seconds (1000 allocations: 78.125 KiB) 28.277251 seconds (1000 allocations: 78.125 KiB) 20.894065 seconds (6.23 k allocations: 358.125 KiB) 20.758075 seconds (1000 allocations: 78.125 KiB) 18.326375 seconds (1.00 k allocations: 78.141 KiB) 18.236989 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing vectors with ExhaustiveSearch | 8000 8000 3m41.4s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 3.143829 seconds (1000 allocations: 78.125 KiB) 3.222784 seconds (1000 allocations: 78.125 KiB) 30.382236 seconds (1000 allocations: 78.125 KiB) 29.311526 seconds (1000 allocations: 78.125 KiB) 30.370827 seconds (1000 allocations: 78.125 KiB) 28.327361 seconds (1000 allocations: 78.125 KiB) 4.151809 seconds (1000 allocations: 78.125 KiB) 4.276535 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing sequences with ExhaustiveSearch | 4000 4000 2m17.2s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 10.854938 seconds (1000 allocations: 78.125 KiB) 10.947512 seconds (1000 allocations: 78.125 KiB) 10.907037 seconds (1000 allocations: 78.125 KiB) 10.437142 seconds (1000 allocations: 78.125 KiB) 10.348443 seconds (1000 allocations: 78.125 KiB) 10.536903 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing sets with ExhaustiveSearch | 3000 3000 1m06.8s 0.042748 seconds (1.00 k allocations: 78.141 KiB) 0.030267 seconds (1000 allocations: 78.125 KiB) 0.037323 seconds (1000 allocations: 78.125 KiB) 0.040530 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time Normalized Cosine and Normalized Angle distances | 2000 2000 3.1s 0.069778 seconds (1000 allocations: 78.125 KiB) 0.068999 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time Binary hamming distance | 1000 1000 1.4s ExhaustiveSearch allknn: 4.316316 seconds (2.44 M allocations: 129.786 MiB, 1.62% gc time, 99.96% compilation time) ParallelExhaustiveSearch allknn: 1.139392 seconds (615.38 k allocations: 30.730 MiB, 99.85% compilation time) Test Summary: | Pass Total Time allknn | 3 3 6.0s quantile(length.(hsp_knns), 0:0.1:1) = [3.0, 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 2.2s [ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:06.979 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-09T17:57:07.220 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) 2025-11-09T17:57:08.551 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] [ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:08.924 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x00000008, 0x0000000c, 0x0000000e, 0x00000016, 0x0000001d, 0x0000003b] D.nn = Int32[1, 2, 3, 3, 3, 6, 6, 8, 8, 3, 6, 12, 8, 14, 8, 8, 14, 3, 3, 12, 3, 22, 6, 3, 3, 14, 1, 12, 29, 3, 22, 3, 29, 3, 1, 1, 3, 8, 6, 14, 6, 3, 1, 3, 3, 29, 14, 12, 8, 3, 22, 14, 29, 29, 3, 3, 14, 12, 59, 12, 8, 6, 29, 3, 22, 3, 8, 3, 22, 6, 29, 12, 8, 29, 1, 3, 1, 29, 29, 8, 3, 6, 59, 1, 59, 3, 3, 22, 29, 3, 14, 29, 3, 14, 29, 14, 8, 29, 12, 29] D.dist = Float32[0.0, 0.0, 0.0, 0.029690742, 0.058615386, 0.0, 0.029901385, 0.0, 0.0989874, 0.049825132, 0.009470701, 0.0, 0.04120207, 0.0, 0.020734668, 0.019451618, 0.044811785, 0.07858914, 0.035544634, 0.078534365, 0.042988896, 0.0, 0.046349585, 0.014690399, 0.04522401, 0.063800275, 0.038868964, 0.045104265, 0.0, 0.03096652, 0.082498014, 0.017888188, 0.07319516, 0.07476711, 0.029707313, 0.057034373, 0.0024007559, 0.008815825, 0.07931262, 0.0069351792, 0.07243532, 0.078431845, 0.040957153, 0.032140076, 0.07464379, 0.049602985, 0.010763109, 0.038285494, 0.04043573, 0.071278155, 0.0097280145, 0.018502772, 0.0270499, 0.040305793, 0.061677635, 0.07742113, 0.022600234, 0.05387658, 0.0, 0.004602313, 0.023153365, 0.094928324, 0.04138112, 0.025809646, 0.027472198, 0.08591962, 0.024147093, 0.025019825, 0.014990032, 0.04646635, 0.010080576, 0.030706286, 0.056620717, 0.04038477, 0.046925664, 0.058138132, 0.06404263, 0.026765287, 0.021766126, 0.0491938, 0.06422913, 0.048943996, 0.034326315, 0.08892554, 0.07082319, 0.041176498, 0.05123186, 0.057402015, 0.07826728, 0.013310075, 0.028859198, 0.035780728, 0.07329464, 0.085797906, 0.002578199, 0.0018680096, 0.028506398, 0.01878202, 0.013206065, 0.03136581] Test Summary: | Pass Total Time neardup single block | 3 3 17.1s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-09T17:57:10.036 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] [ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 [ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 [ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 [ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 [ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 [ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 [ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.036 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x00000008, 0x0000000c, 0x0000000e, 0x00000016, 0x0000001d, 0x0000003b] D.nn = Int32[1, 2, 3, 3, 3, 6, 6, 8, 8, 3, 6, 12, 8, 14, 8, 8, 14, 3, 3, 12, 3, 22, 6, 3, 3, 14, 1, 12, 29, 3, 12, 3, 29, 3, 1, 1, 3, 8, 6, 14, 6, 3, 1, 3, 3, 29, 14, 12, 8, 3, 22, 14, 29, 29, 3, 3, 14, 12, 59, 12, 8, 6, 29, 3, 22, 3, 8, 3, 22, 6, 29, 12, 8, 29, 1, 3, 1, 29, 29, 8, 3, 6, 59, 1, 59, 3, 3, 22, 29, 3, 14, 29, 3, 14, 29, 14, 8, 29, 12, 29] D.dist = Float32[0.0, 0.0, 0.0, 0.029690742, 0.058615386, 0.0, 0.029901385, 0.0, 0.0989874, 0.049825132, 0.009470701, 0.0, 0.04120207, 0.0, 0.020734668, 0.019451618, 0.044811785, 0.07858914, 0.035544634, 0.078534365, 0.042988896, 0.0, 0.046349585, 0.014690399, 0.04522401, 0.063800275, 0.038868964, 0.045104265, 0.0, 0.03096652, 0.088338315, 0.017888188, 0.07319516, 0.07476711, 0.029707313, 0.057034373, 0.0024007559, 0.008815825, 0.07931262, 0.0069351792, 0.07243532, 0.078431845, 0.040957153, 0.032140076, 0.07464379, 0.049602985, 0.010763109, 0.038285494, 0.04043573, 0.071278155, 0.0097280145, 0.018502772, 0.0270499, 0.040305793, 0.061677635, 0.07742113, 0.022600234, 0.05387658, 0.0, 0.004602313, 0.023153365, 0.094928324, 0.04138112, 0.025809646, 0.027472198, 0.08591962, 0.024147093, 0.025019825, 0.014990032, 0.04646635, 0.010080576, 0.030706286, 0.056620717, 0.04038477, 0.046925664, 0.058138132, 0.06404263, 0.026765287, 0.021766126, 0.0491938, 0.06422913, 0.048943996, 0.034326315, 0.08892554, 0.07082319, 0.041176498, 0.05123186, 0.057402015, 0.07826728, 0.013310075, 0.028859198, 0.035780728, 0.07329464, 0.085797906, 0.002578199, 0.0018680096, 0.028506398, 0.01878202, 0.013206065, 0.03136581] 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: 2025-11-09T17:57:10.121 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-11-09T17:57:10.121 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: 2025-11-09T17:57:10.122 [ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.122 [ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.122 [ Info: neardup> range: 65:80, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.122 [ Info: neardup> range: 81:96, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.122 [ Info: neardup> range: 97:100, current elements: 19, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.122 [ Info: neardup> finished current elements: 19, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:10.122 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000003b, 0x00000045, 0x00000059] D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 9, 7, 4, 10, 10, 13, 7, 3, 10, 7, 1, 12, 5, 5, 12, 4, 5, 3, 1, 1, 3, 8, 11, 14, 6, 3, 1, 3, 5, 15, 14, 12, 10, 3, 13, 14, 5, 10, 7, 4, 14, 12, 59, 12, 8, 9, 12, 10, 14, 9, 16, 10, 69, 7, 15, 12, 15, 10, 9, 10, 9, 10, 15, 10, 7, 11, 59, 5, 59, 3, 10, 69, 89, 3, 9, 10, 10, 7, 5, 14, 16, 4, 12, 8] 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, 0.004817128, 0.049208343, 0.0050190687, 0.041413546, 0.0085706115, 0.08888918, 0.012288153, 0.014690399, 0.013277769, 0.057567775, 0.038868964, 0.045104265, 0.07455391, 0.018599391, 0.088338315, 0.012907922, 0.037928462, 0.07476711, 0.029707313, 0.057034373, 0.0024007559, 0.008815825, 0.07414621, 0.0069351792, 0.07243532, 0.078431845, 0.040957153, 0.032140076, 0.0060409904, 0.026372135, 0.010763109, 0.038285494, 0.035752952, 0.071278155, 0.06006497, 0.018502772, 0.029214203, 0.02463466, 0.037521124, 0.07671732, 0.022600234, 0.05387658, 0.0, 0.004602313, 0.023153365, 0.05006069, 0.048860013, 0.01232481, 0.08792877, 0.027947247, 0.022124529, 0.010507286, 0.0, 0.014261603, 0.047635138, 0.030706286, 0.016644359, 0.06271052, 0.026654541, 0.009345353, 0.012995839, 0.041817248, 0.041127503, 0.005506575, 0.03665501, 0.032634974, 0.034326315, 0.051564515, 0.07082319, 0.041176498, 0.030612528, 0.021632075, 0.0, 0.013310075, 0.0006542206, 0.014250636, 0.027480483, 0.02967, 0.06685346, 0.0018680096, 0.0102241635, 0.023052514, 0.013206065, 0.061145186] 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: 2025-11-09T17:57:17.225 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=7 n=7 2025-11-09T17:57:17.225 [ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 [ Info: neardup> range: 33:48, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 [ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 [ Info: neardup> range: 65:80, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 [ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 [ Info: neardup> range: 97:100, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 [ Info: neardup> finished current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-11-09T17:57:17.231 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000006, 0x00000008, 0x0000000c, 0x0000000e, 0x00000016, 0x0000001d, 0x0000003b] D.nn = Int32[1, 2, 3, 3, 3, 6, 6, 8, 8, 3, 6, 12, 8, 14, 8, 8, 14, 3, 3, 12, 3, 22, 6, 3, 3, 14, 1, 12, 29, 3, 12, 3, 29, 3, 1, 1, 3, 8, 6, 14, 6, 3, 1, 3, 3, 29, 14, 12, 8, 3, 22, 14, 29, 29, 3, 3, 14, 12, 59, 12, 8, 6, 29, 3, 22, 3, 8, 3, 22, 6, 29, 12, 8, 29, 1, 3, 1, 29, 29, 8, 3, 6, 59, 1, 59, 3, 3, 22, 29, 3, 14, 29, 3, 14, 29, 14, 8, 29, 12, 29] D.dist = Float32[0.0, 0.0, 0.0, 0.029690742, 0.058615386, 0.0, 0.029901385, 0.0, 0.0989874, 0.049825132, 0.009470701, 0.0, 0.04120207, 0.0, 0.020734668, 0.019451618, 0.044811785, 0.07858914, 0.035544634, 0.078534365, 0.042988896, 0.0, 0.046349585, 0.014690399, 0.04522401, 0.063800275, 0.038868964, 0.045104265, 0.0, 0.03096652, 0.088338315, 0.017888188, 0.07319516, 0.07476711, 0.029707313, 0.057034373, 0.0024007559, 0.008815825, 0.07931262, 0.0069351792, 0.07243532, 0.078431845, 0.040957153, 0.032140076, 0.07464379, 0.049602985, 0.010763109, 0.038285494, 0.04043573, 0.071278155, 0.0097280145, 0.018502772, 0.0270499, 0.040305793, 0.061677635, 0.07742113, 0.022600234, 0.05387658, 0.0, 0.004602313, 0.023153365, 0.094928324, 0.04138112, 0.025809646, 0.027472198, 0.08591962, 0.024147093, 0.025019825, 0.014990032, 0.04646635, 0.010080576, 0.030706286, 0.056620717, 0.04038477, 0.046925664, 0.058138132, 0.06404263, 0.026765287, 0.021766126, 0.0491938, 0.06422913, 0.048943996, 0.034326315, 0.08892554, 0.07082319, 0.041176498, 0.05123186, 0.057402015, 0.07826728, 0.013310075, 0.028859198, 0.035780728, 0.07329464, 0.085797906, 0.002578199, 0.0018680096, 0.028506398, 0.01878202, 0.013206065, 0.03136581] Test Summary: | Pass Total Time neardup small block with filterblocks=false | 3 3 7.1s computing farthest point 1, dmax: Inf, imax: 8, n: 30 computing farthest point 2, dmax: 1.2125285, imax: 18, n: 30 computing farthest point 3, dmax: 1.0047879, imax: 2, n: 30 computing farthest point 4, dmax: 0.84006584, imax: 25, n: 30 computing farthest point 5, dmax: 0.8396863, imax: 11, n: 30 computing farthest point 6, dmax: 0.76331484, imax: 28, n: 30 computing farthest point 7, dmax: 0.6771996, imax: 1, n: 30 computing farthest point 8, dmax: 0.6739176, imax: 24, n: 30 computing farthest point 9, dmax: 0.651792, imax: 4, n: 30 computing farthest point 10, dmax: 0.6252529, imax: 22, n: 30 Test Summary: | Pass Total Time farthest first traversal | 3 3 1.4s 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) 2025-11-09T17:57:25.549 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=0.90702945, maxvisits=104) 2025-11-09T17:57:37.146 LOG n.size quantiles:[4.0, 4.0, 4.0, 4.0, 5.0] (i, j, d) = (14, 464, -1.1920929f-7) (i, j, d, :parallel) = (14, 464, -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 => 19.164726010000003, :exact => 0.823855537) Test Summary: | Pass Total Time closestpair | 4 4 20.5s 5.890787 seconds (1.00 k allocations: 140.742 KiB) SEARCH Exhaustive 1: 0.002922 seconds SEARCH Exhaustive 2: 0.002919 seconds SEARCH Exhaustive 3: 0.003502 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) 2025-11-09T17:58:03.916 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=9, Δ=1.474105, maxvisits=268) 2025-11-09T17:58:09.281 LOG n.size quantiles:[2.0, 5.0, 5.0, 5.0, 6.0] LOG add_vertex! sp=19015 ep=19019 n=19014 BeamSearch(bsize=16, Δ=1.1, maxvisits=372) 2025-11-09T17:58:10.281 LOG n.size quantiles:[4.0, 6.0, 7.0, 8.0, 9.0] LOG add_vertex! sp=32470 ep=32474 n=32469 BeamSearch(bsize=8, Δ=1.1, maxvisits=500) 2025-11-09T17:58:11.281 LOG n.size quantiles:[4.0, 5.0, 5.0, 6.0, 8.0] LOG add_vertex! sp=44000 ep=44004 n=43999 BeamSearch(bsize=12, Δ=1.05, maxvisits=498) 2025-11-09T17:58:12.282 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0] LOG add_vertex! sp=53725 ep=53729 n=53724 BeamSearch(bsize=12, Δ=1.05, maxvisits=498) 2025-11-09T17:58:13.282 LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=62795 ep=62799 n=62794 BeamSearch(bsize=12, Δ=1.025, maxvisits=500) 2025-11-09T17:58:14.282 LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 10.0] LOG add_vertex! sp=73510 ep=73514 n=73509 BeamSearch(bsize=12, Δ=1.025, maxvisits=500) 2025-11-09T17:58:15.282 LOG n.size quantiles:[3.0, 7.0, 8.0, 8.0, 8.0] LOG add_vertex! sp=83930 ep=83934 n=83929 BeamSearch(bsize=12, Δ=1.025, maxvisits=500) 2025-11-09T17:58:16.283 LOG n.size quantiles:[5.0, 5.0, 7.0, 8.0, 11.0] LOG add_vertex! sp=92105 ep=92109 n=92104 BeamSearch(bsize=9, Δ=1.155, maxvisits=540) 2025-11-09T17:58:17.283 LOG n.size quantiles:[7.0, 7.0, 7.0, 8.0, 10.0] 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: 11983.957746865904, recall: 0.900375 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=9, Δ=1.14, maxvisits=714)) 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=1.157625, maxvisits=564)), 1000, 8) [ Info: rebuild: queries per second: 15837.85232133976, recall: 0.901625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.157625, maxvisits=564)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 32.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.155, maxvisits=756)), 1000, 8) 1.721858 seconds (611.69 k allocations: 31.313 MiB, 95.50% compilation time) [ Info: matrixhints: queries per second: 13180.269805658634, recall: 0.903 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.155, maxvisits=756)) 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] 2.164776 seconds (1.00 k allocations: 140.711 KiB) SEARCH Exhaustive 1: 0.001906 seconds SEARCH Exhaustive 2: 0.001890 seconds SEARCH Exhaustive 3: 0.001968 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) 2025-11-09T17:59:28.471 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=9, Δ=1.474105, maxvisits=268) 2025-11-09T17:59:34.248 LOG n.size quantiles:[2.0, 5.0, 5.0, 5.0, 6.0] LOG add_vertex! sp=22350 ep=22354 n=22349 BeamSearch(bsize=16, Δ=1.1, maxvisits=372) 2025-11-09T17:59:35.248 LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 10.0] LOG add_vertex! sp=37800 ep=37804 n=37799 BeamSearch(bsize=8, Δ=1.1, maxvisits=500) 2025-11-09T17:59:36.248 LOG n.size quantiles:[4.0, 4.0, 4.0, 6.0, 7.0] LOG add_vertex! sp=51080 ep=51084 n=51079 BeamSearch(bsize=12, Δ=1.05, maxvisits=498) 2025-11-09T17:59:37.248 LOG n.size quantiles:[5.0, 6.0, 7.0, 10.0, 10.0] LOG add_vertex! sp=67100 ep=67104 n=67099 BeamSearch(bsize=12, Δ=1.025, maxvisits=500) 2025-11-09T17:59:38.248 LOG n.size quantiles:[3.0, 4.0, 6.0, 6.0, 6.0] LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch(bsize=9, Δ=1.155, maxvisits=540) 2025-11-09T17:59:39.289 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 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: 22718.742355853155, recall: 0.900375 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=9, Δ=1.14, maxvisits=714)) 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=1.157625, maxvisits=564)), 1000, 8) [ Info: rebuild: queries per second: 31878.89691620766, recall: 0.901625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.157625, maxvisits=564)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [3.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 32.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.155, maxvisits=756)), 1000, 8) 1.572553 seconds (567.40 k allocations: 29.096 MiB, 4.58% gc time, 97.03% compilation time) [ Info: matrixhints: queries per second: 23347.96674932003, recall: 0.903 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=12, Δ=1.155, maxvisits=756)) 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 2m28.1s Testing SimilaritySearch tests passed Testing completed after 676.4s PkgEval succeeded after 740.46s