Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1808 (1cd77b505e*) started at 2026-02-26T17:11:11.136


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

Installing PkgEval dependencies (TestEnv)...
  Activating project at `~/.julia/environments/v1.14`

Set-up completed after 14.48s


################################################################################
# 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 v1.5.2
  [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 5.19s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   3200.4 ms  ✓ SearchModels
   6983.1 ms  ✓ SimilaritySearch
  2 dependencies successfully precompiled in 11 seconds. 81 already precompiled.

Precompilation completed after 34.76s


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

     Testing SimilaritySearch
      Status `/tmp/jl_so5U6l/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_so5U6l/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 v1.5.2
  [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  17.4s
Test Summary: | Pass  Total  Time
heap          |   16     16  0.2s
Test Summary: |  Pass  Total  Time
KnnHeap       | 30005  30005  4.0s
Test Summary: |  Pass  Total  Time
XKnn          | 25005  25005  3.1s
Test Summary: | Pass  Total  Time
XKnn pop ops  | 9603   9603  1.2s
[ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}})
  6.070179 seconds (404.94 k allocations: 25.067 MiB, 40.67% compilation time)
  3.593300 seconds (7 allocations: 512 bytes)
  5.763443 seconds (258.57 k allocations: 16.284 MiB, 39.60% compilation time)
  3.467174 seconds (7 allocations: 512 bytes)
  5.990932 seconds (241.99 k allocations: 15.372 MiB, 1.34% gc time, 41.59% compilation time)
  3.493491 seconds (7 allocations: 512 bytes)
  5.841742 seconds (237.19 k allocations: 15.105 MiB, 40.44% compilation time)
  3.462205 seconds (7 allocations: 512 bytes)
 16.157874 seconds (250.13 k allocations: 15.788 MiB, 13.64% compilation time)
 13.987111 seconds (7 allocations: 512 bytes)
 26.637536 seconds (7 allocations: 512 bytes)
 26.517285 seconds (7 allocations: 512 bytes)
 20.254644 seconds (516.39 k allocations: 31.838 MiB, 0.36% gc time, 8.68% compilation time)
 18.368473 seconds (7 allocations: 512 bytes)
 17.299590 seconds (410.09 k allocations: 25.733 MiB, 6.85% compilation time)
 12.787832 seconds (7 allocations: 512 bytes)
Test Summary:                          | Pass  Total     Time
indexing vectors with ExhaustiveSearch | 8000   8000  3m15.2s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
  3.921398 seconds (170.86 k allocations: 11.461 MiB, 1.26% gc time, 35.63% compilation time)
  2.597854 seconds (7 allocations: 512 bytes)
 18.985571 seconds (211.94 k allocations: 13.812 MiB, 7.69% compilation time)
 17.603708 seconds (7 allocations: 528 bytes)
 18.667794 seconds (7 allocations: 528 bytes)
 20.672220 seconds (7 allocations: 528 bytes)
  5.952990 seconds (154.91 k allocations: 10.120 MiB, 36.09% compilation time)
  3.620777 seconds (7 allocations: 512 bytes)
Test Summary:                            | Pass  Total     Time
indexing sequences with ExhaustiveSearch | 4000   4000  1m33.6s
[ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}})
 11.793108 seconds (167.56 k allocations: 10.958 MiB, 16.56% compilation time)
  9.524828 seconds (7 allocations: 512 bytes)
 13.369498 seconds (156.19 k allocations: 10.239 MiB, 14.91% compilation time)
  9.916271 seconds (7 allocations: 512 bytes)
 13.529735 seconds (156.10 k allocations: 10.235 MiB, 14.13% compilation time)
  9.676079 seconds (7 allocations: 512 bytes)
Test Summary:                       | Pass  Total     Time
indexing sets with ExhaustiveSearch | 3000   3000  1m10.1s
  1.196771 seconds (229.31 k allocations: 14.427 MiB, 96.66% compilation time)
  0.040252 seconds (7 allocations: 512 bytes)
  2.353311 seconds (237.81 k allocations: 15.244 MiB, 98.55% compilation time)
  0.033306 seconds (7 allocations: 512 bytes)
Test Summary:                                    | Pass  Total  Time
Normalized Cosine and Normalized Angle distances | 2000   2000  5.5s
  2.406192 seconds (292.22 k allocations: 18.009 MiB, 0.98% gc time, 97.70% compilation time)
  0.058250 seconds (7 allocations: 512 bytes)
Test Summary:           | Pass  Total  Time
Binary hamming distance | 1000   1000  3.1s

allknn   2%|▉                                            |  ETA: 0:03:58
allknn 100%|█████████████████████████████████████████████| Time: 0:00:05
ExhaustiveSearch allknn: 5.577714 seconds (1.82 M allocations: 111.397 MiB, 1.04% gc time, 99.96% compilation time)
Test Summary: | Pass  Total  Time
allknn        |    1      1  5.8s
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  5.7s
[ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:25.851
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-26T17:19:26.679
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) 2026-02-26T17:19:30.329
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) 2026-02-26T17:19:32.682
LOG n.size quantiles:[1.0, 2.0, 2.0, 2.0, 3.0]
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:33.144
D.map = UInt32[0x00000001, 0x00000003, 0x00000005, 0x00000006, 0x0000000c, 0x00000012, 0x00000014, 0x00000015, 0x00000024, 0x00000027, 0x00000029]
D.nn = Int32[1, 1, 3, 1, 5, 6, 6, 6, 6, 6, 3, 12, 5, 3, 5, 6, 1, 18, 6, 20, 21, 21, 1, 21, 6, 6, 6, 5, 1, 18, 1, 21, 5, 6, 6, 36, 6, 6, 39, 5, 41, 41, 5, 3, 6, 36, 41, 6, 5, 21, 41, 3, 21, 6, 6, 6, 5, 21, 6, 6, 20, 18, 41, 5, 18, 3, 1, 6, 18, 3, 3, 21, 41, 6, 5, 6, 1, 21, 6, 6, 6, 36, 6, 39, 12, 6, 36, 6, 18, 1, 12, 5, 5, 3, 6, 21, 3, 6, 5, 21]
D.dist = Float32[0.0, 0.07794881, 0.0, 0.09594178, 0.0, 0.0, 0.06628257, 0.03784871, 0.0041102767, 0.02679056, 0.06833321, 0.0, 0.0013086796, 0.06349188, 0.030682564, 0.04949665, 0.045156956, 0.0, 0.068244934, 0.0, 0.0, 0.076312006, 0.06696427, 0.076387346, 0.06222087, 0.045950353, 0.06660581, 0.02516836, 0.02354461, 0.035624027, 0.041629374, 0.0157758, 0.083291054, 0.09699547, 0.02748549, 0.0, 0.027823389, 0.020091832, 0.0, 0.040168405, 0.0, 0.07144022, 0.039489686, 0.054009914, 0.058938563, 0.0597232, 0.03598857, 0.014436781, 0.039533675, 0.01851219, 0.007684946, 0.034674764, 0.040165067, 0.086554945, 0.023664474, 0.015177071, 0.05829549, 0.0035920143, 0.037952125, 0.04053718, 0.010733247, 0.06735951, 0.01609075, 0.053498983, 0.029897332, 0.039971173, 0.04445839, 0.020834684, 0.025396883, 0.017625391, 0.016912341, 0.004609823, 0.052378953, 0.053532064, 0.04868841, 0.02503705, 0.075134695, 0.040415645, 0.07728344, 0.01937002, 0.030187726, 0.056500793, 0.093443215, 0.025059164, 0.0064671636, 0.056302786, 0.042770743, 0.048483193, 0.009534776, 0.028196573, 0.024325132, 0.014324486, 0.035816073, 0.051525235, 0.019408047, 0.015015185, 0.012380362, 0.0057997108, 0.034148514, 0.051704943]
Test Summary:        | Pass  Total   Time
neardup single block |    3      3  24.9s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:34.393
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-26T17:19:34.394
LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0]
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.197
LOG add_vertex! sp=6 ep=8 n=5 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-26T17:19:38.197
LOG n.size quantiles:[2.0, 2.0, 2.0, 2.0, 2.0]
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.199
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.199
[ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.199
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.199
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.484
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.484
D.map = UInt32[0x00000001, 0x00000003, 0x00000005, 0x00000006, 0x0000000c, 0x00000012, 0x00000014, 0x00000015, 0x00000024, 0x00000027, 0x00000029]
D.nn = Int32[1, 1, 3, 1, 5, 6, 6, 6, 6, 6, 3, 12, 5, 3, 5, 6, 1, 18, 6, 20, 21, 21, 1, 3, 6, 6, 6, 5, 1, 1, 1, 6, 5, 6, 6, 36, 6, 6, 39, 5, 41, 41, 5, 3, 6, 6, 41, 6, 5, 21, 41, 3, 21, 6, 6, 6, 5, 21, 6, 6, 20, 18, 41, 5, 18, 3, 1, 6, 18, 3, 3, 21, 41, 6, 5, 6, 1, 21, 6, 6, 6, 36, 6, 39, 12, 6, 36, 6, 18, 1, 12, 5, 5, 3, 6, 21, 3, 6, 5, 21]
D.dist = Float32[0.0, 0.07794881, 0.0, 0.09594178, 0.0, 0.0, 0.06628257, 0.03784871, 0.0041102767, 0.02679056, 0.06833321, 0.0, 0.0013086796, 0.06349188, 0.030682564, 0.04949665, 0.045156956, 0.0, 0.068244934, 0.0, 0.0, 0.076312006, 0.06696427, 0.089744985, 0.06222087, 0.045950353, 0.06660581, 0.02516836, 0.02354461, 0.074322045, 0.041629374, 0.06365925, 0.083291054, 0.09699547, 0.02748549, 0.0, 0.027823389, 0.020091832, 0.0, 0.040168405, 0.0, 0.07144022, 0.039489686, 0.054009914, 0.058938563, 0.072185874, 0.03598857, 0.014436781, 0.039533675, 0.01851219, 0.007684946, 0.034674764, 0.040165067, 0.086554945, 0.023664474, 0.015177071, 0.05829549, 0.0035920143, 0.037952125, 0.04053718, 0.010733247, 0.06735951, 0.01609075, 0.053498983, 0.029897332, 0.039971173, 0.04445839, 0.020834684, 0.025396883, 0.017625391, 0.016912341, 0.004609823, 0.052378953, 0.053532064, 0.04868841, 0.02503705, 0.075134695, 0.040415645, 0.07728344, 0.01937002, 0.030187726, 0.056500793, 0.093443215, 0.025059164, 0.0064671636, 0.056302786, 0.042770743, 0.048483193, 0.009534776, 0.028196573, 0.024325132, 0.014324486, 0.035816073, 0.051525235, 0.019408047, 0.015015185, 0.012380362, 0.0057997108, 0.034148514, 0.051704943]
Test Summary:       | Pass  Total  Time
neardup small block |    3      3  4.2s
[ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.629
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-26T17:19:38.629
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: 2026-02-26T17:19:38.629
[ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.630
[ Info: neardup> range: 49:64, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.630
[ Info: neardup> range: 65:80, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.630
[ Info: neardup> range: 81:96, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.630
[ Info: neardup> range: 97:100, current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.630
[ Info: neardup> finished current elements: 20, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:38.630
D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x00000027, 0x00000029, 0x0000002a, 0x0000002f]
D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 9, 15, 7, 14, 11, 14, 9, 9, 9, 10, 1, 2, 4, 7, 13, 9, 4, 2, 8, 4, 39, 10, 41, 42, 10, 2, 2, 16, 47, 6, 15, 7, 41, 3, 11, 42, 10, 9, 10, 7, 6, 4, 15, 2, 41, 10, 2, 3, 11, 9, 2, 3, 3, 7, 41, 16, 9, 6, 11, 11, 42, 16, 8, 2, 16, 39, 12, 8, 6, 16, 2, 1, 12, 5, 10, 3, 16, 7, 3, 9, 5, 7]
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, 0.045156956, 0.042070508, 0.0459888, 0.0579136, 0.02196902, 0.012866259, 0.021807611, 0.015647173, 0.037838876, 0.037478864, 0.044647455, 0.020117104, 0.02354461, 0.03319812, 0.02282548, 0.0020115376, 0.06536764, 0.06408036, 0.02006197, 0.0918892, 0.0049118996, 0.0155386925, 0.0, 0.02369225, 0.0, 0.0, 0.025245607, 0.03882265, 0.048925757, 0.056298018, 0.0, 0.014436781, 0.010776401, 0.0006581545, 0.007684946, 0.034674764, 0.04504335, 0.034682035, 0.005567193, 0.0042788386, 0.011667967, 0.013477445, 0.037952125, 0.0036193132, 0.05336839, 0.08811432, 0.01609075, 0.02454114, 0.042403996, 0.039971173, 0.02041334, 0.008511245, 0.027401865, 0.017625391, 0.016912341, 0.025670767, 0.052378953, 0.007443607, 0.034498036, 0.02503705, 0.004892528, 0.0021092892, 0.022405982, 0.01022321, 0.014095128, 0.02631241, 0.05339074, 0.025059164, 0.0064671636, 0.046740353, 0.046705604, 0.02743572, 0.014167964, 0.028196573, 0.024325132, 0.014324486, 0.008946478, 0.051525235, 0.007876873, 0.02408588, 0.012380362, 0.0012532473, 0.034148514, 0.035453677]
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: 2026-02-26T17:19:42.143
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=5 n=5 2026-02-26T17:19:42.531
[ Info: neardup> range: 17:32, current elements: 5, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:43.771
LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=5 ep=8 n=8 2026-02-26T17:19:43.772
[ Info: neardup> range: 33:48, current elements: 8, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:43.777
[ Info: neardup> range: 49:64, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:43.777
[ Info: neardup> range: 65:80, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:43.777
[ Info: neardup> range: 81:96, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:43.777
[ Info: neardup> range: 97:100, current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:45.153
[ Info: neardup> finished current elements: 11, n: 100, ϵ: 0.1, timestamp: 2026-02-26T17:19:45.153
D.map = UInt32[0x00000001, 0x00000003, 0x00000005, 0x00000006, 0x0000000c, 0x00000012, 0x00000014, 0x00000015, 0x00000024, 0x00000027, 0x00000029]
D.nn = Int32[1, 1, 3, 1, 5, 6, 6, 6, 6, 6, 3, 12, 5, 3, 5, 6, 1, 18, 6, 20, 21, 21, 1, 3, 6, 6, 6, 5, 1, 1, 1, 6, 5, 6, 6, 36, 6, 6, 39, 5, 41, 41, 5, 3, 6, 6, 41, 6, 5, 21, 41, 3, 21, 6, 6, 6, 5, 21, 6, 6, 20, 18, 41, 5, 18, 3, 1, 6, 18, 3, 3, 21, 41, 6, 5, 6, 1, 21, 6, 6, 6, 36, 6, 39, 12, 6, 36, 6, 18, 1, 12, 5, 5, 3, 6, 21, 3, 6, 5, 21]
D.dist = Float32[0.0, 0.07794881, 0.0, 0.09594178, 0.0, 0.0, 0.06628257, 0.03784871, 0.0041102767, 0.02679056, 0.06833321, 0.0, 0.0013086796, 0.06349188, 0.030682564, 0.04949665, 0.045156956, 0.0, 0.068244934, 0.0, 0.0, 0.076312006, 0.06696427, 0.089744985, 0.06222087, 0.045950353, 0.06660581, 0.02516836, 0.02354461, 0.074322045, 0.041629374, 0.06365925, 0.083291054, 0.09699547, 0.02748549, 0.0, 0.027823389, 0.020091832, 0.0, 0.040168405, 0.0, 0.07144022, 0.039489686, 0.054009914, 0.058938563, 0.072185874, 0.03598857, 0.014436781, 0.039533675, 0.01851219, 0.007684946, 0.034674764, 0.040165067, 0.086554945, 0.023664474, 0.015177071, 0.05829549, 0.0035920143, 0.037952125, 0.04053718, 0.010733247, 0.06735951, 0.01609075, 0.053498983, 0.029897332, 0.039971173, 0.04445839, 0.020834684, 0.025396883, 0.017625391, 0.016912341, 0.004609823, 0.052378953, 0.053532064, 0.04868841, 0.02503705, 0.075134695, 0.040415645, 0.07728344, 0.01937002, 0.030187726, 0.056500793, 0.093443215, 0.025059164, 0.0064671636, 0.056302786, 0.042770743, 0.048483193, 0.009534776, 0.028196573, 0.024325132, 0.014324486, 0.035816073, 0.051525235, 0.019408047, 0.015015185, 0.012380362, 0.0057997108, 0.034148514, 0.051704943]
Test Summary:                               | Pass  Total  Time
neardup small block with filterblocks=false |    3      3  6.5s
computing farthest point 1, dmax: Inf, imax: 1, n: 30
computing farthest point 2, dmax: 1.0929872, imax: 25, n: 30
computing farthest point 3, dmax: 1.0058656, imax: 7, n: 30
computing farthest point 4, dmax: 0.770507, imax: 20, n: 30
computing farthest point 5, dmax: 0.70430267, imax: 5, n: 30
computing farthest point 6, dmax: 0.7003674, imax: 29, n: 30
computing farthest point 7, dmax: 0.637146, imax: 18, n: 30
computing farthest point 8, dmax: 0.6190629, imax: 22, n: 30
computing farthest point 9, dmax: 0.61076885, imax: 24, n: 30
computing farthest point 10, dmax: 0.60343397, imax: 6, n: 30
Test Summary:            | Pass  Total  Time
farthest first traversal |    3      3  2.1s
Test Summary: | Pass  Total  Time
AdjacencyList |   15     15  1.5s
LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-26T17:19:54.766
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) 2026-02-26T17:19:56.671
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=0.9238095, maxvisits=114) 2026-02-26T17:20:12.107
LOG n.size quantiles:[3.0, 4.0, 4.0, 4.0, 5.0]
(i, j, d) = (4, 151, -1.1920929f-7)
(i, j, d, :parallel) = (4, 151, -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 => 26.042002379, :exact => 1.068866799)
Test Summary: | Pass  Total   Time
closestpair   |    4      4  27.6s
  7.908150 seconds (198.33 k allocations: 12.481 MiB, 4.30% gc time, 33.15% compilation time)
SEARCH Exhaustive 1: 0.007167 seconds
SEARCH Exhaustive 2: 0.007409 seconds
SEARCH Exhaustive 3: 0.007790 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) 2026-02-26T17:20:43.271
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) 2026-02-26T17:20:45.325
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=16, Δ=1.1851876, maxvisits=204) 2026-02-26T17:20:57.643
LOG n.size quantiles:[2.0, 3.0, 4.0, 4.0, 5.0]
LOG add_vertex! sp=13080 ep=13084 n=13079 BeamSearch(bsize=14, Δ=1.3066694, maxvisits=404) 2026-02-26T17:20:58.643
LOG n.size quantiles:[5.0, 5.0, 6.0, 6.0, 8.0]
LOG add_vertex! sp=24735 ep=24739 n=24734 BeamSearch(bsize=14, Δ=1.3066694, maxvisits=404) 2026-02-26T17:20:59.643
LOG n.size quantiles:[5.0, 5.0, 8.0, 8.0, 8.0]
LOG add_vertex! sp=34170 ep=34174 n=34169 BeamSearch(bsize=11, Δ=1.2155062, maxvisits=474) 2026-02-26T17:21:00.643
LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=42965 ep=42969 n=42964 BeamSearch(bsize=9, Δ=1.1, maxvisits=432) 2026-02-26T17:21:01.644
LOG n.size quantiles:[4.0, 5.0, 5.0, 7.0, 10.0]
LOG add_vertex! sp=52185 ep=52189 n=52184 BeamSearch(bsize=9, Δ=1.1, maxvisits=432) 2026-02-26T17:21:02.644
LOG n.size quantiles:[4.0, 4.0, 6.0, 7.0, 8.0]
LOG add_vertex! sp=60050 ep=60054 n=60049 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:21:03.645
LOG n.size quantiles:[5.0, 8.0, 8.0, 9.0, 10.0]
LOG add_vertex! sp=68750 ep=68754 n=68749 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:21:04.645
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 11.0]
LOG add_vertex! sp=77125 ep=77129 n=77124 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:21:05.645
LOG n.size quantiles:[5.0, 6.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=85035 ep=85039 n=85034 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:21:06.645
LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 9.0]
LOG add_vertex! sp=91270 ep=91274 n=91269 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598) 2026-02-26T17:21:07.646
LOG n.size quantiles:[4.0, 5.0, 5.0, 6.0, 8.0]
LOG add_vertex! sp=98950 ep=98954 n=98949 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598) 2026-02-26T17:21:08.646
LOG n.size quantiles:[5.0, 7.0, 8.0, 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, 13.0, 15.0, 18.0, 23.0, 92.0]
[ Info: minrecall: queries per second: 2931.3432795569615, recall: 0.903375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.1287501, maxvisits=696))
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, 92.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.155, maxvisits=642)), 1000, 8)
[ Info: rebuild: queries per second: 13233.599107674294, recall: 0.902625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.155, maxvisits=642))
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=14, Δ=1.14, maxvisits=732)), 1000, 8)
  0.683126 seconds (93.89 k allocations: 5.516 MiB, 84.92% compilation time)
[ Info: matrixhints: queries per second: 10957.450761352717, recall: 0.905
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.14, maxvisits=732))
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, 92.0]
  3.448486 seconds (160.08 k allocations: 10.559 MiB, 60.39% compilation time)
SEARCH Exhaustive 1: 0.004635 seconds
SEARCH Exhaustive 2: 0.004762 seconds
SEARCH Exhaustive 3: 0.004527 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) 2026-02-26T17:22:30.196
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) 2026-02-26T17:22:32.208
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=16, Δ=1.1851876, maxvisits=204) 2026-02-26T17:22:44.403
LOG n.size quantiles:[2.0, 3.0, 4.0, 4.0, 5.0]
LOG add_vertex! sp=15380 ep=15384 n=15379 BeamSearch(bsize=14, Δ=1.3066694, maxvisits=404) 2026-02-26T17:22:45.403
LOG n.size quantiles:[3.0, 6.0, 7.0, 7.0, 7.0]
LOG add_vertex! sp=26260 ep=26264 n=26259 BeamSearch(bsize=11, Δ=1.2155062, maxvisits=474) 2026-02-26T17:22:46.404
LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 9.0]
LOG add_vertex! sp=37295 ep=37299 n=37294 BeamSearch(bsize=11, Δ=1.2155062, maxvisits=474) 2026-02-26T17:22:47.404
LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 9.0]
LOG add_vertex! sp=47445 ep=47449 n=47444 BeamSearch(bsize=9, Δ=1.1, maxvisits=432) 2026-02-26T17:22:48.404
LOG n.size quantiles:[4.0, 5.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=56820 ep=56824 n=56819 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:22:49.406
LOG n.size quantiles:[5.0, 5.0, 5.0, 8.0, 9.0]
LOG add_vertex! sp=66320 ep=66324 n=66319 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:22:50.436
LOG n.size quantiles:[6.0, 6.0, 7.0, 8.0, 9.0]
LOG add_vertex! sp=75005 ep=75009 n=75004 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:22:51.436
LOG n.size quantiles:[3.0, 6.0, 6.0, 7.0, 7.0]
LOG add_vertex! sp=83565 ep=83569 n=83564 BeamSearch(bsize=8, Δ=1.1287501, maxvisits=462) 2026-02-26T17:22:52.436
LOG n.size quantiles:[5.0, 7.0, 8.0, 8.0, 8.0]
LOG add_vertex! sp=91255 ep=91259 n=91254 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598) 2026-02-26T17:22:53.436
LOG n.size quantiles:[3.0, 5.0, 6.0, 7.0, 11.0]
LOG add_vertex! sp=99405 ep=99409 n=99404 BeamSearch(bsize=11, Δ=1.1287501, maxvisits=598) 2026-02-26T17:22:54.436
LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 9.0]
quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0]
[ Info: minrecall: queries per second: 2937.0385633398328, recall: 0.903375
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.1287501, maxvisits=696))
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, 92.0]
[ Info: ===================== rebuild ==============================
(graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.155, maxvisits=642)), 1000, 8)
[ Info: rebuild: queries per second: 14643.896890916176, recall: 0.902625
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=13, Δ=1.155, maxvisits=642))
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=14, Δ=1.14, maxvisits=732)), 1000, 8)
  0.676105 seconds (94.97 k allocations: 5.669 MiB, 88.55% compilation time)
[ Info: matrixhints: queries per second: 12949.951403364867, recall: 0.905
graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=14, Δ=1.14, maxvisits=732))
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, 92.0]
Test Summary:                    | Pass  Total     Time
vector indexing with SearchGraph |   18     18  3m24.0s
     Testing SimilaritySearch tests passed 

Testing completed after 692.05s

PkgEval succeeded after 759.23s