Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1420 (3d611fddcf*) started at 2025-12-28T16:34:44.981 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 9.56s ################################################################################ # Installation # Installing SimilaritySearch... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [053f045d] + SimilaritySearch v0.13.7 Updating `~/.julia/environments/v1.14/Manifest.toml` [7d9f7c33] + Accessors v0.1.43 [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 v1.5.1 [92933f4c] + ProgressMeter v1.11.0 [ae029012] + Requires v1.3.1 [94e857df] + SIMDTypes v0.1.0 [431bcebd] + SciMLPublic v1.0.0 ⌅ [0e966ebe] + SearchModels v0.4.1 [053f045d] + SimilaritySearch v0.13.7 [a2af1166] + SortingAlgorithms v1.2.2 [aedffcd0] + Static v1.3.1 [0d7ed370] + StaticArrayInterface v1.8.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 ⌅ [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 v1.13.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [d6f4376e] + Markdown v1.11.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [fa267f1f] + TOML v1.0.3 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [4536629a] + OpenBLAS_jll v0.3.29+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [8e850b90] + libblastrampoline_jll v5.15.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 3.54s ################################################################################ # Precompilation # ERROR: LoadError: MethodError: no method matching setindex!(::Base.ScopedValues.ScopedValue{IO}, ::Nothing) The function `setindex!` exists, but no method is defined for this combination of argument types. Stacktrace: [1] top-level scope @ /PkgEval.jl/scripts/precompile.jl:10 [2] include(mod::Module, _path::String) @ Base ./Base.jl:309 [3] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [4] _start() @ Base ./client.jl:585 in expression starting at /PkgEval.jl/scripts/precompile.jl:6 caused by: MethodError: no method matching setindex!(::Base.ScopedValues.ScopedValue{IO}, ::Base.DevNull) The function `setindex!` exists, but no method is defined for this combination of argument types. Stacktrace: [1] top-level scope @ /PkgEval.jl/scripts/precompile.jl:7 [2] include(mod::Module, _path::String) @ Base ./Base.jl:309 [3] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [4] _start() @ Base ./client.jl:585 Precompilation failed after 12.78s ################################################################################ # Testing # Testing SimilaritySearch Status `/tmp/jl_5BocQy/Project.toml` [7d9f7c33] Accessors v0.1.43 [4c88cf16] Aqua v0.8.14 [b4f34e82] Distances v0.10.12 [f517fe37] Polyester v0.7.18 [92933f4c] ProgressMeter v1.11.0 ⌅ [0e966ebe] SearchModels v0.4.1 [053f045d] SimilaritySearch v0.13.7 [10745b16] Statistics v1.11.1 ⌅ [2913bbd2] StatsBase v0.33.21 [7792a7ef] StrideArraysCore v0.5.8 [ade2ca70] Dates v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_5BocQy/Manifest.toml` [7d9f7c33] Accessors v0.1.43 [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 v1.5.1 [92933f4c] ProgressMeter v1.11.0 [ae029012] Requires v1.3.1 [94e857df] SIMDTypes v0.1.0 [431bcebd] SciMLPublic v1.0.0 ⌅ [0e966ebe] SearchModels v0.4.1 [053f045d] SimilaritySearch v0.13.7 [a2af1166] SortingAlgorithms v1.2.2 [aedffcd0] Static v1.3.1 [0d7ed370] StaticArrayInterface v1.8.0 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.8.0 ⌅ [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 v1.13.0 [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 v1.14.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.0.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.17.0+0 [e37daf67] LibGit2_jll v1.9.2+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.12.2 [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 8.7s Test Summary: | Pass Total Time heap | 16 16 0.1s Test Summary: | Pass Total Time KnnHeap | 30005 30005 2.4s Test Summary: | Pass Total Time XKnn | 25005 25005 1.6s Test Summary: | Pass Total Time XKnn pop ops | 9603 9603 0.7s [ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}}) 5.166964 seconds (1000 allocations: 78.125 KiB) 5.266365 seconds (1000 allocations: 78.125 KiB) 2.246632 seconds (1000 allocations: 78.125 KiB) 1.989567 seconds (1000 allocations: 78.125 KiB) 1.951000 seconds (1000 allocations: 78.125 KiB) 1.928454 seconds (1000 allocations: 78.125 KiB) 2.027467 seconds (1000 allocations: 78.125 KiB) 1.953601 seconds (1000 allocations: 78.125 KiB) 10.614072 seconds (1000 allocations: 78.125 KiB) 10.688505 seconds (1000 allocations: 78.125 KiB) 22.425243 seconds (1000 allocations: 78.125 KiB) 22.207120 seconds (1000 allocations: 78.125 KiB) 13.882688 seconds (6.23 k allocations: 358.094 KiB) 14.111917 seconds (1000 allocations: 78.125 KiB) 11.376412 seconds (1.00 k allocations: 78.141 KiB) 11.468590 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing vectors with ExhaustiveSearch | 8000 8000 2m27.4s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 2.035895 seconds (1000 allocations: 78.125 KiB) 2.037103 seconds (1000 allocations: 78.125 KiB) 15.971291 seconds (1000 allocations: 78.125 KiB) 11.532082 seconds (1000 allocations: 78.125 KiB) 13.981903 seconds (1000 allocations: 78.125 KiB) 14.984332 seconds (1000 allocations: 78.125 KiB) 2.295696 seconds (1000 allocations: 78.125 KiB) 2.471635 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing sequences with ExhaustiveSearch | 4000 4000 1m08.0s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 8.352966 seconds (1000 allocations: 78.125 KiB) 9.012061 seconds (1000 allocations: 78.125 KiB) 8.546330 seconds (1000 allocations: 78.125 KiB) 8.452282 seconds (1000 allocations: 78.125 KiB) 8.457079 seconds (1000 allocations: 78.125 KiB) 8.535245 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time indexing sets with ExhaustiveSearch | 3000 3000 53.6s 0.041286 seconds (1.00 k allocations: 78.141 KiB) 0.041203 seconds (1000 allocations: 78.125 KiB) 0.019990 seconds (1000 allocations: 78.125 KiB) 0.020438 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time Normalized Cosine and Normalized Angle distances | 2000 2000 1.9s 0.023996 seconds (1000 allocations: 78.125 KiB) 0.023632 seconds (1000 allocations: 78.125 KiB) Test Summary: | Pass Total Time Binary hamming distance | 1000 1000 0.9s ExhaustiveSearch allknn: 3.358801 seconds (2.38 M allocations: 127.801 MiB, 1.85% gc time, 99.97% compilation time) ParallelExhaustiveSearch allknn: 0.893489 seconds (609.40 k allocations: 30.532 MiB, 99.85% compilation time) Test Summary: | Pass Total Time allknn | 3 3 4.7s 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 2.1s [ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:47.081 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:40:47.306 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=2 ep=2 n=2 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:40:48.503 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] [ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:48.783 D.map = UInt32[0x00000001, 0x00000005, 0x00000007, 0x0000000b, 0x0000000c, 0x0000000d, 0x00000015, 0x00000018, 0x00000021, 0x00000029, 0x00000033, 0x00000043] D.nn = Int32[1, 1, 1, 1, 5, 1, 7, 7, 7, 1, 11, 12, 13, 1, 11, 13, 7, 1, 7, 11, 21, 1, 11, 24, 11, 7, 12, 13, 21, 21, 7, 21, 33, 5, 5, 21, 12, 21, 11, 11, 41, 5, 21, 24, 24, 33, 13, 11, 11, 7, 51, 33, 11, 51, 12, 1, 11, 11, 1, 24, 1, 33, 13, 11, 13, 1, 67, 24, 1, 21, 13, 11, 7, 7, 13, 41, 11, 7, 11, 1, 33, 51, 13, 1, 51, 1, 1, 24, 1, 7, 21, 21, 1, 67, 24, 13, 67, 1, 11, 1] D.dist = Float32[0.0, 0.085706234, 0.059221625, 0.036439896, 0.0, 0.014109194, 0.0, 0.05539882, 0.025692701, 0.014708817, 0.0, 0.0, 0.0, 0.035495996, 0.028712094, 0.020143926, 0.03123808, 0.06734544, 0.03968042, 0.061490476, 0.0, 0.01945573, 0.074998915, 0.0, 0.025159538, 0.02759087, 0.0459674, 0.02620244, 0.032770038, 0.03986609, 0.023091137, 0.06723368, 0.0, 0.03422171, 0.029244661, 0.08901143, 0.02084124, 0.021871388, 0.053679645, 0.05361265, 0.0, 0.038149238, 0.054988742, 0.060106218, 0.06368995, 0.061551213, 0.059065342, 0.041660488, 0.030847311, 0.012398362, 0.0, 0.029811502, 0.041899085, 0.043124616, 0.054561973, 0.056025445, 0.069212735, 0.01998967, 0.005096793, 0.052749693, 0.048384964, 0.037359357, 0.017877638, 0.057530046, 0.041569293, 0.03332591, 0.0, 0.080673695, 0.06300467, 0.006118655, 0.017383516, 0.032931447, 0.026547074, 0.06945014, 0.025395513, 0.024776876, 0.011321425, 0.033140898, 0.06054461, 0.04975629, 0.072187126, 0.04487115, 0.009249091, 0.060322523, 0.0397076, 0.009336591, 0.056622565, 0.014606178, 0.026078403, 0.037875712, 0.07417065, 0.01376456, 0.008430779, 0.01734829, 0.015417337, 0.03133762, 0.030164182, 0.02238977, 0.07194471, 0.017032802] Test Summary: | Pass Total Time neardup single block | 3 3 13.2s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.823 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:40:49.823 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: 2025-12-28T16:40:49.823 [ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.823 [ Info: neardup> range: 49:64, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.823 [ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.823 [ Info: neardup> range: 81:96, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.823 [ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.823 [ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.824 D.map = UInt32[0x00000001, 0x00000005, 0x00000007, 0x0000000b, 0x0000000c, 0x0000000d, 0x00000015, 0x00000018, 0x00000021, 0x00000029, 0x00000033, 0x00000043] D.nn = Int32[1, 1, 1, 1, 5, 1, 7, 7, 7, 1, 11, 12, 13, 1, 11, 13, 7, 1, 7, 11, 21, 1, 11, 24, 11, 7, 12, 13, 11, 21, 7, 1, 33, 5, 5, 21, 12, 21, 11, 11, 41, 5, 21, 24, 24, 33, 13, 11, 11, 7, 51, 33, 11, 11, 12, 1, 11, 11, 1, 24, 1, 33, 13, 11, 13, 1, 67, 24, 1, 21, 13, 11, 7, 7, 13, 41, 11, 7, 11, 1, 33, 51, 13, 1, 51, 1, 1, 24, 1, 7, 21, 21, 1, 67, 24, 13, 67, 1, 11, 1] D.dist = Float32[0.0, 0.085706234, 0.059221625, 0.036439896, 0.0, 0.014109194, 0.0, 0.05539882, 0.025692701, 0.014708817, 0.0, 0.0, 0.0, 0.035495996, 0.028712094, 0.020143926, 0.03123808, 0.06734544, 0.03968042, 0.061490476, 0.0, 0.01945573, 0.074998915, 0.0, 0.025159538, 0.02759087, 0.0459674, 0.02620244, 0.08577061, 0.03986609, 0.023091137, 0.083795846, 0.0, 0.03422171, 0.029244661, 0.08901143, 0.02084124, 0.021871388, 0.053679645, 0.05361265, 0.0, 0.038149238, 0.054988742, 0.060106218, 0.06368995, 0.061551213, 0.059065342, 0.041660488, 0.030847311, 0.012398362, 0.0, 0.029811502, 0.041899085, 0.05834925, 0.054561973, 0.056025445, 0.069212735, 0.01998967, 0.005096793, 0.052749693, 0.048384964, 0.037359357, 0.017877638, 0.057530046, 0.041569293, 0.03332591, 0.0, 0.080673695, 0.06300467, 0.006118655, 0.017383516, 0.032931447, 0.026547074, 0.06945014, 0.025395513, 0.024776876, 0.011321425, 0.033140898, 0.06054461, 0.04975629, 0.072187126, 0.04487115, 0.009249091, 0.060322523, 0.0397076, 0.009336591, 0.056622565, 0.014606178, 0.026078403, 0.037875712, 0.07417065, 0.01376456, 0.008430779, 0.01734829, 0.015417337, 0.03133762, 0.030164182, 0.02238977, 0.07194471, 0.017032802] 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: 2025-12-28T16:40:49.895 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:40:49.895 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: 2025-12-28T16:40:49.896 [ Info: neardup> range: 33:48, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.896 [ Info: neardup> range: 49:64, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.896 [ Info: neardup> range: 65:80, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.896 [ Info: neardup> range: 81:96, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.896 [ Info: neardup> range: 97:100, current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.896 [ Info: neardup> finished current elements: 21, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:49.896 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000018, 0x0000001e, 0x00000021, 0x0000002e, 0x00000033] D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 9, 14, 9, 11, 15, 10, 15, 24, 2, 7, 9, 13, 15, 30, 8, 14, 33, 5, 5, 15, 12, 15, 11, 15, 6, 5, 14, 24, 24, 46, 8, 15, 15, 7, 51, 33, 2, 11, 12, 8, 8, 11, 1, 24, 3, 33, 16, 2, 4, 6, 30, 24, 9, 30, 16, 15, 8, 8, 16, 1, 11, 7, 11, 3, 46, 51, 13, 3, 51, 1, 46, 24, 4, 2, 14, 14, 1, 30, 24, 16, 30, 1, 11, 3] 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, 0.017764688, 0.012063861, 0.0036605597, 0.061490476, 0.09311992, 0.005123377, 0.026021957, 0.0, 0.013448, 0.02759087, 0.023219287, 0.02620244, 0.082336485, 0.0, 0.0137425065, 0.011798918, 0.0, 0.03422171, 0.029244661, 0.037532747, 0.02084124, 0.046168625, 0.053679645, 0.019375563, 0.08558166, 0.038149238, 0.012391806, 0.060106218, 0.06368995, 0.0, 0.032370687, 0.0379377, 0.0046365857, 0.012398362, 0.0, 0.029811502, 0.003919482, 0.05834925, 0.054561973, 0.022479594, 0.024842918, 0.01998967, 0.005096793, 0.052749693, 0.0055428147, 0.037359357, 0.008709729, 0.048594475, 0.024682462, 0.009345055, 0.097384214, 0.080673695, 0.024706244, 0.027177393, 0.0017645359, 0.01520884, 0.009794295, 0.004127443, 0.017069161, 0.0413661, 0.011321425, 0.033140898, 0.06054461, 0.0016623139, 0.044735134, 0.04487115, 0.009249091, 0.004070103, 0.0397076, 0.009336591, 0.016767383, 0.014606178, 0.015199661, 0.026461482, 0.023545265, 0.049595535, 0.008430779, 0.04509902, 0.015417337, 0.014225543, 0.07051903, 0.02238977, 0.07194471, 0.014630318] 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: 2025-12-28T16:40:55.988 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=6 n=6 2025-12-28T16:40:55.988 [ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.993 [ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.993 [ Info: neardup> range: 49:64, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.993 [ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.993 [ Info: neardup> range: 81:96, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.994 [ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.994 [ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-12-28T16:40:55.994 D.map = UInt32[0x00000001, 0x00000005, 0x00000007, 0x0000000b, 0x0000000c, 0x0000000d, 0x00000015, 0x00000018, 0x00000021, 0x00000029, 0x00000033, 0x00000043] D.nn = Int32[1, 1, 1, 1, 5, 1, 7, 7, 7, 1, 11, 12, 13, 1, 11, 13, 7, 1, 7, 11, 21, 1, 11, 24, 11, 7, 12, 13, 11, 21, 7, 1, 33, 5, 5, 21, 12, 21, 11, 11, 41, 5, 21, 24, 24, 33, 13, 11, 11, 7, 51, 33, 11, 11, 12, 1, 11, 11, 1, 24, 1, 33, 13, 11, 13, 1, 67, 24, 1, 21, 13, 11, 7, 7, 13, 41, 11, 7, 11, 1, 33, 51, 13, 1, 51, 1, 1, 24, 1, 7, 21, 21, 1, 67, 24, 13, 67, 1, 11, 1] D.dist = Float32[0.0, 0.085706234, 0.059221625, 0.036439896, 0.0, 0.014109194, 0.0, 0.05539882, 0.025692701, 0.014708817, 0.0, 0.0, 0.0, 0.035495996, 0.028712094, 0.020143926, 0.03123808, 0.06734544, 0.03968042, 0.061490476, 0.0, 0.01945573, 0.074998915, 0.0, 0.025159538, 0.02759087, 0.0459674, 0.02620244, 0.08577061, 0.03986609, 0.023091137, 0.083795846, 0.0, 0.03422171, 0.029244661, 0.08901143, 0.02084124, 0.021871388, 0.053679645, 0.05361265, 0.0, 0.038149238, 0.054988742, 0.060106218, 0.06368995, 0.061551213, 0.059065342, 0.041660488, 0.030847311, 0.012398362, 0.0, 0.029811502, 0.041899085, 0.05834925, 0.054561973, 0.056025445, 0.069212735, 0.01998967, 0.005096793, 0.052749693, 0.048384964, 0.037359357, 0.017877638, 0.057530046, 0.041569293, 0.03332591, 0.0, 0.080673695, 0.06300467, 0.006118655, 0.017383516, 0.032931447, 0.026547074, 0.06945014, 0.025395513, 0.024776876, 0.011321425, 0.033140898, 0.06054461, 0.04975629, 0.072187126, 0.04487115, 0.009249091, 0.060322523, 0.0397076, 0.009336591, 0.056622565, 0.014606178, 0.026078403, 0.037875712, 0.07417065, 0.01376456, 0.008430779, 0.01734829, 0.015417337, 0.03133762, 0.030164182, 0.02238977, 0.07194471, 0.017032802] Test Summary: | Pass Total Time neardup small block with filterblocks=false | 3 3 6.1s computing farthest point 1, dmax: Inf, imax: 30, n: 30 computing farthest point 2, dmax: 1.4068344, imax: 2, n: 30 computing farthest point 3, dmax: 0.97586757, imax: 21, n: 30 computing farthest point 4, dmax: 0.8959266, imax: 16, n: 30 computing farthest point 5, dmax: 0.71544874, imax: 7, n: 30 computing farthest point 6, dmax: 0.66216624, imax: 12, n: 30 computing farthest point 7, dmax: 0.64439, imax: 22, n: 30 computing farthest point 8, dmax: 0.64299995, imax: 24, n: 30 computing farthest point 9, dmax: 0.63543314, imax: 23, n: 30 computing farthest point 10, dmax: 0.5682349, imax: 29, n: 30 Test Summary: | Pass Total Time farthest first traversal | 3 3 1.1s Test Summary: | Pass Total Time AdjacencyList | 15 15 1.1s LOG add_vertex! sp=1 ep=1 n=1 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:41:01.341 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch BeamSearch(bsize=2, Δ=0.8344671, maxvisits=120) 2025-12-28T16:41:09.857 LOG n.size quantiles:[4.0, 4.0, 4.0, 4.0, 6.0] (i, j, d) = (14, 775, -1.1920929f-7) (i, j, d, :parallel) = (14, 775, -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 => 13.351122797, :exact => 0.782034009) Test Summary: | Pass Total Time closestpair | 4 4 14.6s 1.900912 seconds (1.00 k allocations: 140.711 KiB) SEARCH Exhaustive 1: 0.001851 seconds SEARCH Exhaustive 2: 0.001827 seconds SEARCH Exhaustive 3: 0.001783 seconds typeof(seq) = ExhaustiveSearch{SqL2Distance, MatrixDatabase{Matrix{Float32}}} typeof(ectx) = GenericContext{KnnSorted} typeof(q) = SubArray{Float32, 1, Matrix{Float32}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true} typeof(res) = KnnSorted{Vector{IdWeight}} [ Info: ===================== minrecall ============================== LOG add_vertex! sp=1 ep=1 n=1 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:41:24.684 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch BeamSearch(bsize=7, Δ=1.5478102, maxvisits=276) 2025-12-28T16:41:28.272 LOG n.size quantiles:[3.0, 4.0, 5.0, 6.0, 7.0] LOG add_vertex! sp=19450 ep=19454 n=19449 BeamSearch BeamSearch(bsize=11, Δ=1.3370568, maxvisits=562) 2025-12-28T16:41:29.272 LOG n.size quantiles:[5.0, 5.0, 6.0, 7.0, 9.0] LOG add_vertex! sp=40015 ep=40019 n=40014 BeamSearch BeamSearch(bsize=12, Δ=1.1, maxvisits=422) 2025-12-28T16:41:30.272 LOG n.size quantiles:[5.0, 5.0, 8.0, 8.0, 9.0] LOG add_vertex! sp=57920 ep=57924 n=57919 BeamSearch BeamSearch(bsize=4, Δ=1.3370568, maxvisits=520) 2025-12-28T16:41:31.273 LOG n.size quantiles:[4.0, 4.0, 5.0, 7.0, 8.0] LOG add_vertex! sp=71835 ep=71839 n=71834 BeamSearch BeamSearch(bsize=4, Δ=1.3370568, maxvisits=520) 2025-12-28T16:41:32.273 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 9.0] LOG add_vertex! sp=84475 ep=84479 n=84474 BeamSearch BeamSearch(bsize=4, Δ=1.3370568, maxvisits=520) 2025-12-28T16:41:33.273 LOG n.size quantiles:[6.0, 7.0, 7.0, 10.0, 10.0] LOG add_vertex! sp=98825 ep=98829 n=98824 BeamSearch BeamSearch(bsize=8, Δ=1.025, maxvisits=538) 2025-12-28T16:41:34.273 LOG n.size quantiles:[5.0, 7.0, 8.0, 8.0, 9.0] quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 84.0] [ Info: minrecall: queries per second: 20475.877409775298, recall: 0.90325 graph.algo = Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=10, Δ=1.1287501, maxvisits=734)) 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, 84.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=17, Δ=1.155, maxvisits=648)), 1000, 8) [ Info: rebuild: queries per second: 26802.195721640543, recall: 0.90175 graph.algo = Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=17, Δ=1.155, maxvisits=648)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 14.0, 14.0, 15.0, 16.0, 18.0, 19.0, 33.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=6, Δ=1.1287501, maxvisits=734)), 1000, 8) 1.109735 seconds (606.43 k allocations: 31.118 MiB, 95.60% compilation time) [ Info: matrixhints: queries per second: 21788.18036534595, recall: 0.90325 graph.algo = Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=6, Δ=1.1287501, maxvisits=734)) 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, 84.0] 1.776256 seconds (1.00 k allocations: 140.711 KiB) SEARCH Exhaustive 1: 0.001889 seconds SEARCH Exhaustive 2: 0.001952 seconds SEARCH Exhaustive 3: 0.002005 seconds typeof(seq) = ExhaustiveSearch{SqL2Distance, StrideMatrixDatabase{StrideArraysCore.StrideArray{Float32, 2, (1, 2), Tuple{Int64, Int64}, Tuple{Nothing, Nothing}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}, Matrix{Float32}}}} typeof(ectx) = GenericContext{KnnSorted} typeof(q) = StrideArraysCore.StrideArray{Float32, 1, (1,), Tuple{Int64}, Tuple{Nothing}, Tuple{Static.StaticInt{1}}, Matrix{Float32}} typeof(res) = KnnSorted{Vector{IdWeight}} [ Info: ===================== minrecall ============================== LOG add_vertex! sp=1 ep=1 n=1 BeamSearch BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-12-28T16:42:15.692 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch BeamSearch(bsize=7, Δ=1.5478102, maxvisits=276) 2025-12-28T16:42:19.721 LOG n.size quantiles:[3.0, 4.0, 5.0, 6.0, 7.0] LOG add_vertex! sp=25525 ep=25529 n=25524 BeamSearch BeamSearch(bsize=16, Δ=1.1, maxvisits=438) 2025-12-28T16:42:20.722 LOG n.size quantiles:[3.0, 5.0, 7.0, 7.0, 9.0] LOG add_vertex! sp=45340 ep=45344 n=45339 BeamSearch BeamSearch(bsize=12, Δ=1.1, maxvisits=422) 2025-12-28T16:42:21.722 LOG n.size quantiles:[4.0, 7.0, 7.0, 9.0, 9.0] LOG add_vertex! sp=60655 ep=60659 n=60654 BeamSearch BeamSearch(bsize=4, Δ=1.3370568, maxvisits=520) 2025-12-28T16:42:22.722 LOG n.size quantiles:[3.0, 4.0, 6.0, 8.0, 8.0] LOG add_vertex! sp=73890 ep=73894 n=73889 BeamSearch BeamSearch(bsize=4, Δ=1.3370568, maxvisits=520) 2025-12-28T16:42:23.722 LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 9.0] LOG add_vertex! sp=85225 ep=85229 n=85224 BeamSearch BeamSearch(bsize=8, Δ=1.025, maxvisits=538) 2025-12-28T16:42:24.757 LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 8.0] LOG add_vertex! sp=98715 ep=98719 n=98714 BeamSearch BeamSearch(bsize=8, Δ=1.025, maxvisits=538) 2025-12-28T16:42:25.757 LOG n.size quantiles:[6.0, 7.0, 9.0, 9.0, 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, 13.0, 15.0, 18.0, 23.0, 84.0] [ Info: minrecall: queries per second: 19319.68921497862, recall: 0.90325 graph.algo = Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=10, Δ=1.1287501, maxvisits=734)) 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, 84.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=17, Δ=1.155, maxvisits=648)), 1000, 8) [ Info: rebuild: queries per second: 23880.048415365356, recall: 0.90175 graph.algo = Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=17, Δ=1.155, maxvisits=648)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 14.0, 14.0, 15.0, 16.0, 18.0, 19.0, 33.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=6, Δ=1.1287501, maxvisits=734)), 1000, 8) 1.197239 seconds (562.61 k allocations: 28.928 MiB, 3.14% gc time, 95.90% compilation time) [ Info: matrixhints: queries per second: 20132.943057574357, recall: 0.90325 graph.algo = Base.RefValue{BeamSearch}(BeamSearch BeamSearch(bsize=6, Δ=1.1287501, maxvisits=734)) 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, 84.0] Test Summary: | Pass Total Time vector indexing with SearchGraph | 18 18 1m41.7s Testing SimilaritySearch tests passed Testing completed after 457.65s PkgEval succeeded after 497.26s