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avoid defining a one arg hash since it has some invalidation issues #3516

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Merged
bkamins merged 3 commits into from
Oct 17, 2025
+3 −4
Merged

avoid defining a one arg hash since it has some invalidation issues #3516

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04ee4ac
avoid defining a one arg hash since it has some invalidation issues
KristofferC Oct 16, 2025
973ae75
bump patch version
KristofferC Oct 17, 2025
6e421b1
Update src/join/core.jl
KristofferC Oct 17, 2025
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "DataFrames"
uuid = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
version = "1.8.0"
version = "1.8.1"

[deps]
Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
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3 changes: 1 addition & 2 deletions src/join/core.jl
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Expand Up @@ -33,8 +33,7 @@ Base.IndexStyle(::Type{<:OnCol}) = Base.IndexLinear()
return OnColRow(i, oc.cols, oc.h)
end

Base.hash(ocr1::OnColRow, h::UInt) = throw(MethodError(hash, (ocr1, h)))
@inline Base.hash(ocr1::OnColRow) = @inbounds ocr1.h[ocr1.row]
@inline Base.hash(ocr1::OnColRow, ::UInt) = @inbounds ocr1.h[ocr1.row]
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# Hashing one column at a time is faster since it can use SIMD
function _prehash(oc::OnCol)
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1 change: 0 additions & 1 deletion test/join.jl
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Expand Up @@ -1000,7 +1000,6 @@ end
end

for i in eachindex(c1), j in eachindex(oncols, tupcols)
@test_throws MethodError hash(oncols[j][1], zero(UInt))
DataFrames._prehash(oncols[j])
@test hash(oncols[j][i]) == hash(tupcols[j][i])
for k in eachindex(c1)
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