Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1711 (41ad7d9eeb*) started at 2026-02-12T16:52:16.144 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 12.58s ################################################################################ # Installation # Installing SimilaritySearch... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [053f045d] + SimilaritySearch v0.13.8 Updating `~/.julia/environments/v1.14/Manifest.toml` [7d9f7c33] + Accessors v0.1.43 [79e6a3ab] + Adapt v4.4.0 [4fba245c] + ArrayInterface v7.22.0 [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 [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 [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 v1.0.1 [0e966ebe] + SearchModels v0.5.0 [053f045d] + SimilaritySearch v0.13.8 [a2af1166] + SortingAlgorithms v1.2.2 [aedffcd0] + Static v1.3.1 [0d7ed370] + StaticArrayInterface v1.9.0 [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 [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 v0.3.30+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 4.76s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 3145.2 ms ✓ SearchModels 7110.9 ms ✓ SimilaritySearch 2 dependencies successfully precompiled in 11 seconds. 81 already precompiled. Precompilation completed after 32.01s ################################################################################ # Testing # Testing SimilaritySearch Status `/tmp/jl_bdo7Fz/Project.toml` [7d9f7c33] Accessors v0.1.43 [4c88cf16] Aqua v0.8.14 [b4f34e82] Distances v0.10.12 [92933f4c] ProgressMeter v1.11.0 [0e966ebe] SearchModels v0.5.0 [053f045d] SimilaritySearch v0.13.8 [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_bdo7Fz/Manifest.toml` [7d9f7c33] Accessors v0.1.43 [79e6a3ab] Adapt v4.4.0 [4c88cf16] Aqua v0.8.14 [4fba245c] ArrayInterface v7.22.0 [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 [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 [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 v1.0.1 [0e966ebe] SearchModels v0.5.0 [053f045d] SimilaritySearch v0.13.8 [a2af1166] SortingAlgorithms v1.2.2 [aedffcd0] Static v1.3.1 [0d7ed370] StaticArrayInterface v1.9.0 [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 [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 v8.18.0+0 [e37daf67] LibGit2_jll v1.9.2+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.12.2 [4536629a] OpenBLAS_jll v0.3.30+0 [458c3c95] OpenSSL_jll v3.5.5+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 | 57 57 16.3s Test Summary: | Pass Total Time heap | 16 16 0.1s Test Summary: | Pass Total Time KnnHeap | 30005 30005 3.8s Test Summary: | Pass Total Time XKnn | 25005 25005 2.9s Test Summary: | Pass Total Time XKnn pop ops | 9603 9603 1.2s [ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}}) 5.431620 seconds (400.95 k allocations: 24.701 MiB, 33.23% compilation time) 3.620528 seconds (7 allocations: 512 bytes) 5.429382 seconds (255.86 k allocations: 16.082 MiB, 32.64% compilation time) 3.649386 seconds (7 allocations: 512 bytes) 5.256726 seconds (239.62 k allocations: 15.180 MiB, 0.55% gc time, 34.70% compilation time) 3.477166 seconds (7 allocations: 512 bytes) 5.193438 seconds (235.05 k allocations: 14.918 MiB, 33.44% compilation time) 3.377171 seconds (7 allocations: 512 bytes) 15.912621 seconds (247.53 k allocations: 15.587 MiB, 9.73% compilation time) 14.271176 seconds (7 allocations: 512 bytes) 27.313916 seconds (7 allocations: 512 bytes) 27.248571 seconds (7 allocations: 512 bytes) 20.349535 seconds (511.57 k allocations: 31.515 MiB, 0.37% gc time, 8.51% compilation time) 18.516748 seconds (7 allocations: 512 bytes) 17.363375 seconds (406.76 k allocations: 25.465 MiB, 6.42% compilation time) 16.591848 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time indexing vectors with ExhaustiveSearch | 8000 8000 3m18.2s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 3.806734 seconds (169.00 k allocations: 11.272 MiB, 1.71% gc time, 35.04% compilation time) 3.444230 seconds (7 allocations: 512 bytes) 32.059130 seconds (210.23 k allocations: 13.612 MiB, 5.60% compilation time) 28.558667 seconds (7 allocations: 528 bytes) 28.701703 seconds (7 allocations: 528 bytes) 28.274505 seconds (7 allocations: 528 bytes) 6.731860 seconds (152.91 k allocations: 9.927 MiB, 33.96% compilation time) 4.417984 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time indexing sequences with ExhaustiveSearch | 4000 4000 2m18.0s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 12.180348 seconds (165.75 k allocations: 10.782 MiB, 11.90% compilation time) 9.570605 seconds (7 allocations: 512 bytes) 11.366490 seconds (154.64 k allocations: 10.077 MiB, 13.07% compilation time) 10.081727 seconds (7 allocations: 512 bytes) 11.302273 seconds (154.55 k allocations: 10.074 MiB, 12.83% compilation time) 9.902856 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time indexing sets with ExhaustiveSearch | 3000 3000 1m06.4s 1.095253 seconds (227.56 k allocations: 14.251 MiB, 96.35% compilation time) 0.040044 seconds (7 allocations: 512 bytes) 1.751820 seconds (235.77 k allocations: 15.066 MiB, 97.96% compilation time) 0.035597 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time Normalized Cosine and Normalized Angle distances | 2000 2000 4.8s 1.908776 seconds (289.55 k allocations: 17.773 MiB, 1.13% gc time, 97.03% compilation time) 0.057081 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time Binary hamming distance | 1000 1000 2.6s allknn 2%|▉ | ETA: 0:03:24 allknn 100%|█████████████████████████████████████████████| Time: 0:00:04 ExhaustiveSearch allknn: 4.829789 seconds (1.81 M allocations: 110.528 MiB, 0.59% gc time, 99.95% compilation time) Test Summary: | Pass Total Time allknn | 1 1 5.0s 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 4.8s [ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:01.492 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-12T17:01:02.225 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) 2026-02-12T17:01:05.043 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=5 ep=9 n=4 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-12T17:01:06.900 LOG n.size quantiles:[1.0, 2.0, 2.0, 2.0, 2.0] [ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:07.357 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000008, 0x0000000a, 0x0000000e, 0x00000010, 0x00000037, 0x0000003f] D.nn = Int32[1, 2, 3, 1, 3, 2, 3, 8, 2, 10, 2, 3, 10, 14, 2, 16, 14, 2, 1, 2, 2, 1, 14, 14, 8, 10, 2, 14, 3, 2, 10, 3, 3, 14, 2, 10, 3, 14, 8, 2, 2, 14, 8, 2, 2, 16, 2, 14, 14, 8, 3, 2, 3, 14, 55, 2, 1, 2, 10, 2, 10, 3, 63, 8, 1, 2, 14, 2, 1, 63, 1, 2, 3, 2, 1, 1, 2, 8, 55, 2, 14, 3, 16, 2, 16, 63, 14, 63, 2, 8, 3, 63, 55, 14, 1, 2, 14, 3, 16, 14] D.dist = Float32[0.0, 0.0, 0.0, 0.035430133, 0.009367585, 0.05020374, 0.09309298, 0.0, 0.054491997, 0.0, 0.009374738, 0.04105842, 0.055550873, 0.0, 0.094688416, 0.0, 0.059374332, 0.057535708, 0.07830244, 0.035372853, 0.058646798, 0.009233236, 0.09888375, 0.01845771, 0.025791168, 0.021374345, 0.09746832, 0.040920556, 0.053159952, 0.024046004, 0.06479353, 0.026231766, 0.08174026, 0.051939905, 0.02375555, 0.05783999, 0.036218166, 0.047661364, 0.0863775, 0.01912427, 0.08355081, 0.024793148, 0.050420344, 0.091380596, 0.03046918, 0.08336407, 0.030133307, 0.063284874, 0.06656021, 0.05832833, 0.081043124, 0.04554254, 0.020933032, 0.012559056, 0.0, 0.011356473, 0.041040897, 0.08022821, 0.0068361163, 0.082142234, 0.07740247, 0.02376163, 0.0, 0.08334774, 0.03772384, 0.0039978623, 0.02588737, 0.08198583, 0.051673055, 0.012817442, 0.029093444, 0.041237295, 0.058794916, 0.035449147, 0.029011428, 0.043243945, 0.025578916, 0.0023108125, 0.03837681, 0.046172082, 0.08027285, 0.037958503, 0.054466546, 0.028429866, 0.054998517, 0.002558589, 0.035541415, 0.0610165, 0.010754824, 0.07019806, 0.04470092, 0.09878421, 0.052048862, 0.06899208, 0.04728633, 0.06243384, 0.07198024, 0.059770644, 0.044636488, 0.06401104] Test Summary: | Pass Total Time neardup single block | 3 3 21.1s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:08.472 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-12T17:01:08.473 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: 2026-02-12T17:01:11.468 [ Info: neardup> range: 33:48, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.469 [ Info: neardup> range: 49:64, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.469 LOG add_vertex! sp=8 ep=9 n=7 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-12T17:01:11.469 LOG n.size quantiles:[2.0, 2.25, 2.5, 2.75, 3.0] [ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.469 [ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.469 [ Info: neardup> range: 97:100, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.742 [ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.742 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000008, 0x0000000a, 0x0000000e, 0x00000010, 0x00000037, 0x0000003f] D.nn = Int32[1, 2, 3, 1, 3, 2, 3, 8, 2, 10, 2, 3, 10, 14, 2, 16, 14, 2, 1, 2, 2, 1, 14, 14, 8, 10, 2, 14, 3, 2, 10, 3, 3, 14, 2, 10, 3, 14, 8, 2, 2, 14, 8, 2, 2, 16, 2, 14, 14, 8, 3, 2, 3, 14, 55, 2, 1, 2, 10, 2, 10, 3, 63, 8, 1, 2, 14, 2, 1, 63, 1, 2, 3, 2, 1, 1, 2, 8, 55, 2, 14, 3, 16, 2, 16, 63, 14, 63, 2, 8, 3, 63, 55, 14, 1, 2, 14, 3, 16, 14] D.dist = Float32[0.0, 0.0, 0.0, 0.035430133, 0.009367585, 0.05020374, 0.09309298, 0.0, 0.054491997, 0.0, 0.009374738, 0.04105842, 0.055550873, 0.0, 0.094688416, 0.0, 0.059374332, 0.057535708, 0.07830244, 0.035372853, 0.058646798, 0.009233236, 0.09888375, 0.01845771, 0.025791168, 0.021374345, 0.09746832, 0.040920556, 0.053159952, 0.024046004, 0.06479353, 0.026231766, 0.08174026, 0.051939905, 0.02375555, 0.05783999, 0.036218166, 0.047661364, 0.0863775, 0.01912427, 0.08355081, 0.024793148, 0.050420344, 0.091380596, 0.03046918, 0.08336407, 0.030133307, 0.063284874, 0.06656021, 0.05832833, 0.081043124, 0.04554254, 0.020933032, 0.012559056, 0.0, 0.011356473, 0.041040897, 0.08022821, 0.0068361163, 0.082142234, 0.07740247, 0.02376163, 0.0, 0.08334774, 0.03772384, 0.0039978623, 0.02588737, 0.08198583, 0.051673055, 0.012817442, 0.029093444, 0.041237295, 0.058794916, 0.035449147, 0.029011428, 0.043243945, 0.025578916, 0.0023108125, 0.03837681, 0.046172082, 0.08027285, 0.037958503, 0.054466546, 0.028429866, 0.054998517, 0.002558589, 0.035541415, 0.0610165, 0.010754824, 0.07019806, 0.04470092, 0.09878421, 0.052048862, 0.06899208, 0.04728633, 0.06243384, 0.07198024, 0.059770644, 0.044636488, 0.06401104] Test Summary: | Pass Total Time neardup small block | 3 3 3.3s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.826 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-12T17:01:11.827 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: 2026-02-12T17:01:11.827 [ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.827 [ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.827 [ Info: neardup> range: 65:80, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.828 [ Info: neardup> range: 81:96, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.828 [ Info: neardup> range: 97:100, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.828 [ Info: neardup> finished current elements: 17, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:11.828 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000037] D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 14, 2, 4, 6, 11, 1, 14, 14, 8, 13, 6, 14, 7, 11, 10, 5, 12, 14, 2, 10, 3, 14, 11, 11, 7, 14, 8, 2, 2, 12, 11, 12, 14, 8, 12, 7, 3, 14, 55, 11, 4, 12, 10, 15, 13, 5, 15, 8, 4, 2, 14, 12, 1, 15, 1, 2, 12, 2, 1, 1, 2, 8, 55, 2, 12, 5, 16, 2, 16, 15, 14, 11, 2, 12, 12, 11, 55, 12, 4, 2, 12, 12, 16, 12] 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, 0.059374332, 0.057535708, 0.036470413, 0.0027365088, 0.0540334, 0.009233236, 0.09888375, 0.01845771, 0.025791168, 0.019067168, 0.011787653, 0.040920556, 0.02875626, 0.013433814, 0.06479353, 0.011146665, 0.008790195, 0.051939905, 0.02375555, 0.05783999, 0.036218166, 0.047661364, 0.07360542, 0.011813402, 0.022237003, 0.024793148, 0.050420344, 0.091380596, 0.03046918, 0.011381149, 0.0075507164, 0.03259009, 0.06656021, 0.05832833, 0.018855393, 0.02343756, 0.020933032, 0.012559056, 0.0, 0.0028666258, 0.012414455, 0.034107983, 0.0068361163, 0.029435873, 0.0036397576, 0.010575712, 0.011541069, 0.08334774, 0.023702562, 0.0039978623, 0.02588737, 0.07251322, 0.051673055, 0.0070199966, 0.029093444, 0.041237295, 0.0026445389, 0.035449147, 0.029011428, 0.043243945, 0.025578916, 0.0023108125, 0.03837681, 0.046172082, 0.031812668, 0.01061368, 0.054466546, 0.028429866, 0.054998517, 0.008638322, 0.035541415, 0.038992286, 0.010754824, 0.06749648, 0.01182878, 0.06566006, 0.052048862, 0.03274554, 0.034151852, 0.06243384, 0.04684913, 0.006227076, 0.044636488, 0.042102396] 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: 2026-02-12T17:01:16.687 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=7 n=7 2026-02-12T17:01:17.050 [ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:18.291 [ Info: neardup> range: 33:48, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:18.291 [ Info: neardup> range: 49:64, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:18.292 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=7 ep=9 n=9 2026-02-12T17:01:18.292 [ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:18.297 [ Info: neardup> range: 81:96, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:18.297 [ Info: neardup> range: 97:100, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:19.398 [ Info: neardup> finished current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-12T17:01:19.398 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000008, 0x0000000a, 0x0000000e, 0x00000010, 0x00000037, 0x0000003f] D.nn = Int32[1, 2, 3, 1, 3, 2, 3, 8, 2, 10, 2, 3, 10, 14, 2, 16, 14, 2, 1, 2, 2, 1, 14, 14, 8, 10, 2, 14, 3, 2, 10, 3, 3, 14, 2, 10, 3, 14, 8, 2, 2, 14, 8, 2, 2, 16, 2, 14, 14, 8, 3, 2, 3, 14, 55, 2, 1, 2, 10, 2, 10, 3, 63, 8, 1, 2, 14, 2, 1, 63, 1, 2, 3, 2, 1, 1, 2, 8, 55, 2, 14, 3, 16, 2, 16, 63, 14, 63, 2, 8, 3, 63, 55, 14, 1, 2, 14, 3, 16, 14] D.dist = Float32[0.0, 0.0, 0.0, 0.035430133, 0.009367585, 0.05020374, 0.09309298, 0.0, 0.054491997, 0.0, 0.009374738, 0.04105842, 0.055550873, 0.0, 0.094688416, 0.0, 0.059374332, 0.057535708, 0.07830244, 0.035372853, 0.058646798, 0.009233236, 0.09888375, 0.01845771, 0.025791168, 0.021374345, 0.09746832, 0.040920556, 0.053159952, 0.024046004, 0.06479353, 0.026231766, 0.08174026, 0.051939905, 0.02375555, 0.05783999, 0.036218166, 0.047661364, 0.0863775, 0.01912427, 0.08355081, 0.024793148, 0.050420344, 0.091380596, 0.03046918, 0.08336407, 0.030133307, 0.063284874, 0.06656021, 0.05832833, 0.081043124, 0.04554254, 0.020933032, 0.012559056, 0.0, 0.011356473, 0.041040897, 0.08022821, 0.0068361163, 0.082142234, 0.07740247, 0.02376163, 0.0, 0.08334774, 0.03772384, 0.0039978623, 0.02588737, 0.08198583, 0.051673055, 0.012817442, 0.029093444, 0.041237295, 0.058794916, 0.035449147, 0.029011428, 0.043243945, 0.025578916, 0.0023108125, 0.03837681, 0.046172082, 0.08027285, 0.037958503, 0.054466546, 0.028429866, 0.054998517, 0.002558589, 0.035541415, 0.0610165, 0.010754824, 0.07019806, 0.04470092, 0.09878421, 0.052048862, 0.06899208, 0.04728633, 0.06243384, 0.07198024, 0.059770644, 0.044636488, 0.06401104] Test Summary: | Pass Total Time neardup small block with filterblocks=false | 3 3 7.6s computing farthest point 1, dmax: Inf, imax: 26, n: 30 computing farthest point 2, dmax: 1.2092185, imax: 3, n: 30 computing farthest point 3, dmax: 0.9853719, imax: 19, n: 30 computing farthest point 4, dmax: 0.97299904, imax: 30, n: 30 computing farthest point 5, dmax: 0.7097594, imax: 24, n: 30 computing farthest point 6, dmax: 0.70229405, imax: 16, n: 30 computing farthest point 7, dmax: 0.70147365, imax: 8, n: 30 computing farthest point 8, dmax: 0.59628123, imax: 7, n: 30 computing farthest point 9, dmax: 0.5697338, imax: 28, n: 30 computing farthest point 10, dmax: 0.5461721, imax: 11, n: 30 Test Summary: | Pass Total Time farthest first traversal | 3 3 1.9s 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) 2026-02-12T17:01:28.274 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) 2026-02-12T17:01:29.817 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=2, Δ=0.861678, maxvisits=106) 2026-02-12T17:01:43.166 LOG n.size quantiles:[3.0, 3.0, 3.0, 5.0, 5.0] (i, j, d) = (95, 621, -1.1920929f-7) (i, j, d, :parallel) = (95, 621, -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 => 22.152133177, :exact => 1.023196676) Test Summary: | Pass Total Time closestpair | 4 4 23.7s 7.465920 seconds (196.76 k allocations: 12.325 MiB, 4.01% gc time, 27.33% compilation time) SEARCH Exhaustive 1: 0.004230 seconds SEARCH Exhaustive 2: 0.004005 seconds SEARCH Exhaustive 3: 0.005012 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) 2026-02-12T17:02:10.536 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) 2026-02-12T17:02:12.240 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=14, Δ=1.155, maxvisits=200) 2026-02-12T17:02:22.325 LOG n.size quantiles:[2.0, 3.0, 4.0, 4.0, 7.0] LOG add_vertex! sp=15900 ep=15904 n=15899 BeamSearch(bsize=12, Δ=1.155, maxvisits=362) 2026-02-12T17:02:23.325 LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 8.0] LOG add_vertex! sp=28970 ep=28974 n=28969 BeamSearch(bsize=8, Δ=1.025, maxvisits=386) 2026-02-12T17:02:24.325 LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 8.0] LOG add_vertex! sp=40475 ep=40479 n=40474 BeamSearch(bsize=10, Δ=1.075, maxvisits=462) 2026-02-12T17:02:25.325 LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 8.0] LOG add_vertex! sp=51830 ep=51834 n=51829 BeamSearch(bsize=10, Δ=1.075, maxvisits=462) 2026-02-12T17:02:26.325 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0] LOG add_vertex! sp=60555 ep=60559 n=60554 BeamSearch(bsize=16, Δ=1.05, maxvisits=476) 2026-02-12T17:02:27.326 LOG n.size quantiles:[3.0, 8.0, 8.0, 9.0, 9.0] LOG add_vertex! sp=71270 ep=71274 n=71269 BeamSearch(bsize=16, Δ=1.05, maxvisits=476) 2026-02-12T17:02:28.326 LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 8.0] LOG add_vertex! sp=80925 ep=80929 n=80924 BeamSearch(bsize=16, Δ=1.05, maxvisits=476) 2026-02-12T17:02:29.326 LOG n.size quantiles:[5.0, 6.0, 6.0, 8.0, 9.0] LOG add_vertex! sp=88090 ep=88094 n=88089 BeamSearch(bsize=16, Δ=1.1851876, maxvisits=516) 2026-02-12T17:02:30.326 LOG n.size quantiles:[4.0, 5.0, 5.0, 7.0, 7.0] LOG add_vertex! sp=96490 ep=96494 n=96489 BeamSearch(bsize=16, Δ=1.1851876, maxvisits=516) 2026-02-12T17:02:31.327 LOG n.size quantiles:[6.0, 7.0, 8.0, 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, 12.0, 14.0, 17.0, 23.0, 87.0] [ Info: minrecall: queries per second: 3148.9003207195915, recall: 0.902125 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.1025, maxvisits=796)) 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, 87.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598)), 1000, 8) [ Info: rebuild: queries per second: 15775.306379718471, recall: 0.90075 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 31.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.09, maxvisits=796)), 1000, 8) 0.602866 seconds (92.96 k allocations: 5.461 MiB, 87.67% compilation time) [ Info: matrixhints: queries per second: 13419.960610536813, recall: 0.898625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.09, maxvisits=796)) 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, 87.0] 2.925532 seconds (158.41 k allocations: 10.370 MiB, 52.95% compilation time) SEARCH Exhaustive 1: 0.001400 seconds SEARCH Exhaustive 2: 0.001206 seconds SEARCH Exhaustive 3: 0.001454 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) 2026-02-12T17:03:42.565 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) 2026-02-12T17:03:44.301 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=14, Δ=1.155, maxvisits=200) 2026-02-12T17:03:54.092 LOG n.size quantiles:[2.0, 3.0, 4.0, 4.0, 7.0] LOG add_vertex! sp=18980 ep=18984 n=18979 BeamSearch(bsize=12, Δ=1.155, maxvisits=362) 2026-02-12T17:03:55.092 LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 8.0] LOG add_vertex! sp=32945 ep=32949 n=32944 BeamSearch(bsize=8, Δ=1.025, maxvisits=386) 2026-02-12T17:03:56.092 LOG n.size quantiles:[3.0, 4.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=45580 ep=45584 n=45579 BeamSearch(bsize=10, Δ=1.075, maxvisits=462) 2026-02-12T17:03:57.092 LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 7.0] LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch(bsize=16, Δ=1.05, maxvisits=476) 2026-02-12T17:03:58.134 LOG n.size quantiles:[4.0, 5.0, 6.0, 8.0, 9.0] LOG add_vertex! sp=67885 ep=67889 n=67884 BeamSearch(bsize=16, Δ=1.05, maxvisits=476) 2026-02-12T17:03:59.134 LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 10.0] LOG add_vertex! sp=77540 ep=77544 n=77539 BeamSearch(bsize=16, Δ=1.05, maxvisits=476) 2026-02-12T17:04:00.135 LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 9.0] LOG add_vertex! sp=86805 ep=86809 n=86804 BeamSearch(bsize=16, Δ=1.1851876, maxvisits=516) 2026-02-12T17:04:01.135 LOG n.size quantiles:[2.0, 6.0, 7.0, 8.0, 12.0] LOG add_vertex! sp=95765 ep=95769 n=95764 BeamSearch(bsize=16, Δ=1.1851876, maxvisits=516) 2026-02-12T17:04:02.136 LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 11.0] 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, 87.0] [ Info: minrecall: queries per second: 3135.2024484401145, recall: 0.902125 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=10, Δ=1.1025, maxvisits=796)) 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, 87.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598)), 1000, 8) [ Info: rebuild: queries per second: 15813.29608184633, recall: 0.90075 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 31.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.09, maxvisits=796)), 1000, 8) 0.637563 seconds (94.05 k allocations: 5.616 MiB, 89.17% compilation time) [ Info: matrixhints: queries per second: 14385.054595741558, recall: 0.898625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.09, maxvisits=796)) 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, 87.0] Test Summary: | Pass Total Time vector indexing with SearchGraph | 18 18 2m53.8s Testing SimilaritySearch tests passed Testing completed after 691.46s PkgEval succeeded after 752.74s