# Mapreduce performance and dispatch

**URL:** <https://discourse.julialang.org/t/mapreduce-performance-and-dispatch/101322>\
**Category:** Performance\
**Tags:** question\
**Created:** [July 7, 2023, 5:49pm UTC](https://discourse.julialang.org/t/mapreduce-performance-and-dispatch/101322 "2023-07-07T17:49:14Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![bmit](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/bmit/32/12443_2.png) [@bmit](https://discourse.julialang.org/u/bmit)\
**Post date:** [July 7, 2023, 5:49pm UTC](https://discourse.julialang.org/t/mapreduce-performance-and-dispatch/101322/1 "2023-07-07T17:49:14Z")

</div>

I’m having trouble getting `mapreduce` to dispatch correctly and am looking for tips. From profiling I can see that it dispatches to `map` and `reduce` independently rather than something better like `mapfoldl`.

There’s a similar issue here and I reuse that example:

[https://discourse.julialang.org/t/mapreduce-slower-than-sum/36046](https://discourse.julialang.org/t/mapreduce-slower-than-sum/36046)

```julia
using StaticArrays, BenchmarkTools

# hand-coded function
function prodsum(x, y; init=zeros(eltype(x)))
    v = init
    for i = 1:length(x)
        @inbounds v += x[i]*y[i]
    end
    return v
end

function test()
    n = 10000
    x = rand(SVector{3, Float64}, n)
    y = rand(Float64, n)

    @btime prodsum($x, $y) # 9.208 μs (0 allocations: 0 bytes)
    @btime sum($x .* $y) # 9.708 μs (2 allocations: 234.42 KiB)
    @btime mapreduce(*, +, $x, $y) # 11.000 μs (6 allocations: 234.55 KiB)
    @btime mapfoldl(splat(*), +, zip($x, $y)) # 9.208 μs (0 allocations: 0 bytes)
end

test();

```

How would I effectively use `mapreduce` in this case?

Btw, initialization produces some strange performance results:

```julia
function test_init()
    n=10000
    x = rand(SVector{3, Float64}, n)
    y = rand(Float64, n)
    x0 = zeros(SVector{3, Float64})

    @btime prodsum($x, $y, init=$x0) # 9.209 μs (0 allocations: 0 bytes)
    @btime sum($x .* $y, init=$x0) # 15.417 μs (2 allocations: 234.42 KiB)
    @btime mapreduce(*, +, $x, $y, init=$x0) # 15.291 μs (2 allocations: 234.42 KiB)
    @btime mapfoldl(splat(*), +, zip($x, $y), init=$x0) # 9.208 μs (0 allocations: 0 bytes)
end

test_init();

```