Package evaluation to test SimilaritySearch on Julia 1.13.0-DEV.1353 (74c32ec0b5*) started at 2025-10-21T16:53:33.180


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 8.62s


################################################################################
# Installation
#

Installing SimilaritySearch...
   Resolving package versions...
    Updating `~/.julia/environments/v1.13/Project.toml`
  [053f045d] + SimilaritySearch v0.13.5
    Updating `~/.julia/environments/v1.13/Manifest.toml`
  [7d9f7c33] + Accessors v0.1.42
  [79e6a3ab] + Adapt v4.4.0
  [4fba245c] + ArrayInterface v7.21.0
  [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 v1.3.0
  [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 4.79s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 39.13s


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

     Testing SimilaritySearch
      Status `/tmp/jl_YZ78ga/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_YZ78ga/Manifest.toml`
  [7d9f7c33] Accessors v0.1.42
  [79e6a3ab] Adapt v4.4.0
  [4c88cf16] Aqua v0.8.14
  [4fba245c] ArrayInterface v7.21.0
  [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 v1.3.0
  [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 v2025.9.9
  [4536629a] OpenBLAS_jll v0.3.29+0
  [458c3c95] OpenSSL_jll v3.5.4+0
  [efcefdf7] PCRE2_jll v10.46.0+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 v1.67.1+0
  [3f19e933] p7zip_jll v17.6.0+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  16.5s
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  2.5s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
 10.424977 seconds (1000 allocations: 78.125 KiB)
 10.521629 seconds (1000 allocations: 78.125 KiB)
  3.999517 seconds (1000 allocations: 78.125 KiB)
  4.043039 seconds (1000 allocations: 78.125 KiB)
  3.965065 seconds (1000 allocations: 78.125 KiB)
  3.962753 seconds (1000 allocations: 78.125 KiB)
  3.872622 seconds (1000 allocations: 78.125 KiB)
  3.865361 seconds (1000 allocations: 78.125 KiB)
 15.300129 seconds (1000 allocations: 78.125 KiB)
 15.285978 seconds (1000 allocations: 78.125 KiB)
 28.081793 seconds (1000 allocations: 78.125 KiB)
 28.220359 seconds (1000 allocations: 78.125 KiB)
 20.830648 seconds (6.23 k allocations: 358.125 KiB)
 20.602683 seconds (1000 allocations: 78.125 KiB)
 17.747514 seconds (1.00 k allocations: 78.141 KiB)
 17.832953 seconds (1000 allocations: 78.125 KiB)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m40.1s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.291784 seconds (1000 allocations: 78.125 KiB)
  3.328423 seconds (1000 allocations: 78.125 KiB)
 30.347025 seconds (1000 allocations: 78.125 KiB)
 30.340304 seconds (1000 allocations: 78.125 KiB)
 29.987383 seconds (1000 allocations: 78.125 KiB)
 29.559777 seconds (1000 allocations: 78.125 KiB)
  4.254795 seconds (1000 allocations: 78.125 KiB)
  4.190583 seconds (1000 allocations: 78.125 KiB)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  2m19.0s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  9.788414 seconds (1000 allocations: 78.125 KiB)
  9.888615 seconds (1000 allocations: 78.125 KiB)
 10.134782 seconds (1000 allocations: 78.125 KiB)
  9.997385 seconds (1000 allocations: 78.125 KiB)
 10.087796 seconds (1000 allocations: 78.125 KiB)
 10.066744 seconds (1000 allocations: 78.125 KiB)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m02.7s
  0.047120 seconds (1.00 k allocations: 78.141 KiB)
  0.048370 seconds (1000 allocations: 78.125 KiB)
  0.043574 seconds (1000 allocations: 78.125 KiB)
  0.041758 seconds (1000 allocations: 78.125 KiB)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  3.0s
  0.053260 seconds (1000 allocations: 78.125 KiB)
  0.052132 seconds (1000 allocations: 78.125 KiB)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  1.5s
ExhaustiveSearch allknn: 4.558911 seconds (2.44 M allocations: 129.803 MiB, 6.43% gc time, 99.96% compilation time)
ParallelExhaustiveSearch allknn: 1.184225 seconds (615.38 k allocations: 30.730 MiB, 99.85% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    3      3  6.3s
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  2.9s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:42.125
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-10-21T17:02:42.356
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) 2025-10-21T17:02:43.567
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: 2025-10-21T17:02:43.941
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000007, 0x00000009, 0x0000000a, 0x00000023, 0x00000031, 0x0000003f, 0x00000041, 0x00000042, 0x0000005a]
D.nn = Int32[1, 2, 2, 4, 1, 4, 7, 4, 9, 10, 2, 7, 2, 2, 7, 4, 2, 4, 4, 2, 1, 1, 4, 1, 2, 2, 2, 4, 10, 2, 2, 4, 1, 2, 35, 10, 4, 4, 35, 10, 2, 35, 2, 4, 1, 10, 1, 2, 49, 2, 1, 49, 35, 2, 2, 10, 2, 35, 9, 1, 9, 10, 63, 2, 65, 66, 4, 66, 1, 4, 2, 66, 2, 10, 2, 10, 49, 4, 4, 1, 4, 65, 4, 35, 4, 1, 10, 7, 10, 90, 4, 2, 66, 10, 4, 1, 1, 10, 9, 4]
D.dist = Float32[0.0, 0.0, 0.019643009, 0.0, 0.04437703, 0.052265286, 0.0, 0.030541003, 0.0, 0.0, 0.09482956, 0.0428921, 0.014137149, 0.02939558, 0.07546073, 0.09674716, 0.023565233, 0.018020868, 0.021662533, 0.08967143, 0.03725016, 0.008558512, 0.049244046, 0.048446774, 0.009842098, 0.06976056, 0.07937384, 0.04992324, 0.029655516, 0.03747654, 0.0076863766, 0.019490957, 0.02177453, 0.08015436, 0.0, 0.008692563, 0.08866972, 0.04650581, 0.0066159964, 0.04738444, 0.04387802, 0.040899098, 0.05076605, 0.049355447, 0.027330637, 0.09630424, 0.0049835443, 0.029360592, 0.0, 0.09292692, 0.061741054, 0.06148225, 0.06501216, 0.026535153, 0.027074039, 0.01903665, 0.003498733, 0.059140027, 0.026993573, 0.07240844, 0.047238052, 0.06287962, 0.0, 0.02521485, 0.0, 0.0, 0.074219406, 0.011822104, 0.0516513, 0.034773707, 0.007727802, 0.010847747, 0.040582657, 0.038595617, 0.044444025, 0.034823895, 0.07704383, 0.034912825, 0.009171128, 0.02268207, 0.059152782, 0.045794904, 0.047423303, 0.042392075, 0.043292403, 0.03528577, 0.054734647, 0.023819387, 0.03712076, 0.0, 0.0046494603, 0.057346642, 0.028516114, 0.08038497, 0.044635475, 0.008715153, 0.026891947, 0.044828117, 0.029662669, 0.023314238]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  17.5s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.027
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-10-21T17:02:45.028
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: 2025-10-21T17:02:45.028
[ Info: neardup> range: 33:48, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.028
[ Info: neardup> range: 49:64, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.028
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.028
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.029
[ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.029
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.029
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000007, 0x00000009, 0x0000000a, 0x00000023, 0x00000031, 0x0000003f, 0x00000041, 0x00000042, 0x0000005a]
D.nn = Int32[1, 2, 2, 4, 1, 4, 7, 4, 9, 10, 2, 7, 2, 2, 7, 4, 2, 4, 4, 2, 1, 1, 4, 1, 2, 2, 2, 4, 10, 2, 2, 4, 1, 2, 35, 10, 4, 4, 35, 10, 2, 35, 2, 4, 1, 10, 1, 2, 49, 2, 1, 10, 35, 2, 2, 10, 2, 35, 9, 1, 9, 10, 63, 2, 65, 66, 4, 66, 1, 4, 2, 35, 2, 10, 2, 10, 49, 4, 4, 1, 4, 65, 4, 35, 4, 1, 10, 7, 10, 90, 4, 2, 66, 10, 4, 1, 1, 10, 9, 4]
D.dist = Float32[0.0, 0.0, 0.019643009, 0.0, 0.04437703, 0.052265286, 0.0, 0.030541003, 0.0, 0.0, 0.09482956, 0.0428921, 0.014137149, 0.02939558, 0.07546073, 0.09674716, 0.023565233, 0.018020868, 0.021662533, 0.08967143, 0.03725016, 0.008558512, 0.049244046, 0.048446774, 0.009842098, 0.06976056, 0.07937384, 0.04992324, 0.029655516, 0.03747654, 0.0076863766, 0.019490957, 0.02177453, 0.08015436, 0.0, 0.008692563, 0.08866972, 0.04650581, 0.0066159964, 0.04738444, 0.04387802, 0.040899098, 0.05076605, 0.049355447, 0.027330637, 0.09630424, 0.0049835443, 0.029360592, 0.0, 0.09292692, 0.061741054, 0.06972951, 0.06501216, 0.026535153, 0.027074039, 0.01903665, 0.003498733, 0.059140027, 0.026993573, 0.07240844, 0.047238052, 0.06287962, 0.0, 0.02521485, 0.0, 0.0, 0.074219406, 0.011822104, 0.0516513, 0.034773707, 0.007727802, 0.07264614, 0.040582657, 0.038595617, 0.044444025, 0.034823895, 0.07704383, 0.034912825, 0.009171128, 0.02268207, 0.059152782, 0.045794904, 0.047423303, 0.042392075, 0.043292403, 0.03528577, 0.054734647, 0.023819387, 0.03712076, 0.0, 0.0046494603, 0.057346642, 0.028516114, 0.08038497, 0.044635475, 0.008715153, 0.026891947, 0.044828117, 0.029662669, 0.023314238]
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: 2025-10-21T17:02:45.113
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-10-21T17:02:45.113
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: 2025-10-21T17:02:45.115
[ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.115
[ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.115
[ Info: neardup> range: 65:80, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.115
[ Info: neardup> range: 81:96, current elements: 17, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.115
[ Info: neardup> range: 97:100, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.116
[ Info: neardup> finished current elements: 18, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:45.116
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000003f, 0x0000005a]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 2, 4, 4, 11, 16, 1, 6, 5, 2, 13, 11, 6, 10, 13, 3, 4, 1, 6, 16, 10, 15, 4, 16, 10, 2, 5, 2, 13, 1, 10, 1, 13, 14, 2, 16, 6, 5, 14, 3, 10, 2, 5, 9, 5, 9, 10, 63, 13, 5, 11, 16, 11, 16, 8, 2, 11, 2, 10, 13, 10, 11, 4, 4, 1, 11, 5, 8, 5, 3, 5, 10, 12, 10, 90, 4, 13, 14, 10, 16, 1, 1, 10, 9, 4]
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, 0.023565233, 0.018020868, 0.021662533, 0.029581249, 0.025024414, 0.008558512, 0.017712831, 0.009640992, 0.009842098, 0.023541749, 0.014468789, 0.012298882, 0.029655516, 0.032526135, 0.004098892, 0.019490957, 0.02177453, 0.06927633, 0.03246796, 0.008692563, 0.009507656, 0.04650581, 0.015923738, 0.04738444, 0.04387802, 0.09172839, 0.05076605, 0.036663175, 0.027330637, 0.09630424, 0.0049835443, 0.020709813, 0.05732435, 0.09292692, 0.026722789, 0.06625891, 0.040396214, 0.022073686, 0.01100868, 0.01903665, 0.003498733, 0.02788496, 0.026993573, 0.04875642, 0.047238052, 0.06287962, 0.0, 0.012464523, 0.06754851, 0.044020176, 0.068404496, 0.070124984, 0.021083474, 0.0054187775, 0.007727802, 0.09452897, 0.040582657, 0.038595617, 0.009321451, 0.034823895, 0.06399059, 0.034912825, 0.009171128, 0.02268207, 0.04266852, 0.07137388, 0.0022366643, 0.041177392, 0.026315749, 0.00778234, 0.054734647, 0.0090433955, 0.03712076, 0.0, 0.0046494603, 0.028425395, 0.02233994, 0.08038497, 0.03775549, 0.008715153, 0.026891947, 0.044828117, 0.029662669, 0.023314238]
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: 2025-10-21T17:02:52.047
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=6 n=6 2025-10-21T17:02:52.047
[ Info: neardup> range: 17:32, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.052
[ Info: neardup> range: 33:48, current elements: 6, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.053
[ Info: neardup> range: 49:64, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.053
[ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.053
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.053
[ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.053
[ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2025-10-21T17:02:52.053
D.map = UInt32[0x00000001, 0x00000002, 0x00000004, 0x00000007, 0x00000009, 0x0000000a, 0x00000023, 0x00000031, 0x0000003f, 0x00000041, 0x00000042, 0x0000005a]
D.nn = Int32[1, 2, 2, 4, 1, 4, 7, 4, 9, 10, 2, 7, 2, 2, 7, 4, 2, 4, 4, 2, 1, 1, 4, 1, 2, 2, 2, 4, 10, 2, 2, 4, 1, 2, 35, 10, 4, 4, 35, 10, 2, 35, 2, 4, 1, 10, 1, 2, 49, 2, 1, 10, 35, 2, 2, 10, 2, 35, 9, 1, 9, 10, 63, 2, 65, 66, 4, 66, 1, 4, 2, 35, 2, 10, 2, 10, 49, 4, 4, 1, 4, 65, 4, 35, 4, 1, 10, 7, 10, 90, 4, 2, 66, 10, 4, 1, 1, 10, 9, 4]
D.dist = Float32[0.0, 0.0, 0.019643009, 0.0, 0.04437703, 0.052265286, 0.0, 0.030541003, 0.0, 0.0, 0.09482956, 0.0428921, 0.014137149, 0.02939558, 0.07546073, 0.09674716, 0.023565233, 0.018020868, 0.021662533, 0.08967143, 0.03725016, 0.008558512, 0.049244046, 0.048446774, 0.009842098, 0.06976056, 0.07937384, 0.04992324, 0.029655516, 0.03747654, 0.0076863766, 0.019490957, 0.02177453, 0.08015436, 0.0, 0.008692563, 0.08866972, 0.04650581, 0.0066159964, 0.04738444, 0.04387802, 0.040899098, 0.05076605, 0.049355447, 0.027330637, 0.09630424, 0.0049835443, 0.029360592, 0.0, 0.09292692, 0.061741054, 0.06972951, 0.06501216, 0.026535153, 0.027074039, 0.01903665, 0.003498733, 0.059140027, 0.026993573, 0.07240844, 0.047238052, 0.06287962, 0.0, 0.02521485, 0.0, 0.0, 0.074219406, 0.011822104, 0.0516513, 0.034773707, 0.007727802, 0.07264614, 0.040582657, 0.038595617, 0.044444025, 0.034823895, 0.07704383, 0.034912825, 0.009171128, 0.02268207, 0.059152782, 0.045794904, 0.047423303, 0.042392075, 0.043292403, 0.03528577, 0.054734647, 0.023819387, 0.03712076, 0.0, 0.0046494603, 0.057346642, 0.028516114, 0.08038497, 0.044635475, 0.008715153, 0.026891947, 0.044828117, 0.029662669, 0.023314238]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  6.9s
computing farthest point 1, dmax: Inf, imax: 11, n: 30
computing farthest point 2, dmax: 1.2809794, imax: 1, n: 30
computing farthest point 3, dmax: 1.0320628, imax: 7, n: 30
computing farthest point 4, dmax: 0.9287589, imax: 29, n: 30
computing farthest point 5, dmax: 0.73432875, imax: 9, n: 30
computing farthest point 6, dmax: 0.73336923, imax: 30, n: 30
computing farthest point 7, dmax: 0.670085, imax: 19, n: 30
computing farthest point 8, dmax: 0.6586287, imax: 16, n: 30
computing farthest point 9, dmax: 0.6118384, imax: 6, n: 30
computing farthest point 10, dmax: 0.50663316, imax: 5, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  1.8s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.6s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2025-10-21T17:03:00.543
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=12, Δ=0.975, maxvisits=114) 2025-10-21T17:03:11.363
LOG n.size quantiles:[3.0, 3.0, 4.0, 5.0, 7.0]
(i, j, d) = (37, 374, -1.1920929f-7)
(i, j, d, :parallel) = (37, 374, -1.1920929f-7, :parallel)
[ Info: NOTE: the exact method will be faster on small datasets due to the preprocessing step of the approximation method
[ Info: ("closestpair computation time", :approx => 18.37352574, :exact => 0.916742021)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  19.8s
  5.978617 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.004517 seconds
SEARCH Exhaustive 2: 0.004593 seconds
SEARCH Exhaustive 3: 0.005899 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) 2025-10-21T17:03:39.446
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=1.1851876, maxvisits=210) 2025-10-21T17:03:44.722
LOG n.size quantiles:[2.0, 3.0, 3.0, 5.0, 5.0]
LOG add_vertex! sp=17185 ep=17189 n=17184 BeamSearch(bsize=12, Δ=1.2733874, maxvisits=436) 2025-10-21T17:03:45.722
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=30435 ep=30439 n=30434 BeamSearch(bsize=10, Δ=1.0, maxvisits=382) 2025-10-21T17:03:46.722
LOG n.size quantiles:[5.0, 5.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=41315 ep=41319 n=41314 BeamSearch(bsize=6, Δ=1.075, maxvisits=466) 2025-10-21T17:03:47.722
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 9.0]
LOG add_vertex! sp=53005 ep=53009 n=53004 BeamSearch(bsize=6, Δ=1.075, maxvisits=466) 2025-10-21T17:03:48.722
LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 9.0]
LOG add_vertex! sp=61445 ep=61449 n=61444 BeamSearch(bsize=11, Δ=1.21275, maxvisits=466) 2025-10-21T17:03:49.722
LOG n.size quantiles:[6.0, 7.0, 8.0, 8.0, 8.0]
LOG add_vertex! sp=70380 ep=70384 n=70379 BeamSearch(bsize=11, Δ=1.21275, maxvisits=466) 2025-10-21T17:03:50.723
LOG n.size quantiles:[7.0, 7.0, 7.0, 7.0, 10.0]
LOG add_vertex! sp=78725 ep=78729 n=78724 BeamSearch(bsize=11, Δ=1.21275, maxvisits=466) 2025-10-21T17:03:51.723
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=85250 ep=85254 n=85249 BeamSearch(bsize=10, Δ=0.925, maxvisits=446) 2025-10-21T17:03:52.723
LOG n.size quantiles:[4.0, 5.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=95020 ep=95024 n=95019 BeamSearch(bsize=10, Δ=0.925, maxvisits=446) 2025-10-21T17:03:53.724
LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 90.0]
[ Info: minrecall: queries per second: 11930.98037617403, recall: 0.900375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.157625, maxvisits=812))
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=1.155, maxvisits=566)), 1000, 8)
[ Info: rebuild: queries per second: 14865.634804304247, recall: 0.8965
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.155, maxvisits=566))
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=16, Δ=1.155, maxvisits=812)), 1000, 8)
  1.784082 seconds (612.31 k allocations: 31.315 MiB, 2.04% gc time, 95.26% compilation time)
[ Info: matrixhints: queries per second: 12006.244111387497, recall: 0.899
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=16, Δ=1.155, maxvisits=812))
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]
  2.182334 seconds (1.00 k allocations: 140.711 KiB)
SEARCH Exhaustive 1: 0.002119 seconds
SEARCH Exhaustive 2: 0.002038 seconds
SEARCH Exhaustive 3: 0.002192 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) 2025-10-21T17:05:05.565
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=1.1851876, maxvisits=210) 2025-10-21T17:05:11.208
LOG n.size quantiles:[2.0, 3.0, 3.0, 5.0, 5.0]
LOG add_vertex! sp=20515 ep=20519 n=20514 BeamSearch(bsize=12, Δ=1.2733874, maxvisits=436) 2025-10-21T17:05:12.208
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=35930 ep=35934 n=35929 BeamSearch(bsize=10, Δ=1.0, maxvisits=382) 2025-10-21T17:05:13.208
LOG n.size quantiles:[5.0, 5.0, 6.0, 8.0, 8.0]
LOG add_vertex! sp=48215 ep=48219 n=48214 BeamSearch(bsize=6, Δ=1.075, maxvisits=466) 2025-10-21T17:05:14.208
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 8.0]
LOG add_vertex! sp=59425 ep=59429 n=59424 BeamSearch(bsize=11, Δ=1.21275, maxvisits=466) 2025-10-21T17:05:15.209
LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=70015 ep=70019 n=70014 BeamSearch(bsize=11, Δ=1.21275, maxvisits=466) 2025-10-21T17:05:16.209
LOG n.size quantiles:[6.0, 6.0, 7.0, 8.0, 8.0]
LOG add_vertex! sp=79775 ep=79779 n=79774 BeamSearch(bsize=11, Δ=1.21275, maxvisits=466) 2025-10-21T17:05:17.210
LOG n.size quantiles:[5.0, 6.0, 6.0, 8.0, 9.0]
LOG add_vertex! sp=88770 ep=88774 n=88769 BeamSearch(bsize=10, Δ=0.925, maxvisits=446) 2025-10-21T17:05:18.210
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 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: 14014.165209882514, recall: 0.900375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.157625, maxvisits=812))
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=1.155, maxvisits=566)), 1000, 8)
[ Info: rebuild: queries per second: 15653.100494924429, recall: 0.8965
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.155, maxvisits=566))
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=16, Δ=1.155, maxvisits=812)), 1000, 8)
  1.636865 seconds (567.91 k allocations: 29.100 MiB, 95.72% compilation time)
[ Info: matrixhints: queries per second: 13547.952959177077, recall: 0.899
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=16, Δ=1.155, maxvisits=812))
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  2m43.3s
     Testing SimilaritySearch tests passed 

Testing completed after 690.0s

PkgEval succeeded after 753.34s