faster iteration over a Flatten of heterogenous iterators

[adienes]

seems to help in many cases. would fix the precise MWE given in #52552, but does not necessarily fix comprehensively all perf issues of all heterogenous flattens. but, may as well be better when it's possible

setup:

julia> using BenchmarkTools

julia> A = rand(Int, 100000); B = 1:100000;

julia> function g(it)
           s = 0
           for i in it
               s += i
           end
           s
       end

before:

julia> @btime g($(Iterators.flatten((A, B))))
  12.461 ms (698979 allocations: 18.29 MiB)

julia> @btime g($(Iterators.flatten(i for i in (A, B))))
  12.393 ms (698979 allocations: 18.29 MiB)

julia> @btime g($(Iterators.flatten([A, B])))
  15.115 ms (999494 allocations: 25.93 MiB)

julia> @btime g($(Iterators.flatten((A, Iterators.flatten((A, B))))))
  82.585 ms (2997964 allocations: 106.78 MiB)

after:

julia> @btime g($(Iterators.flatten((A, B))))
  135.958 μs (2 allocations: 64 bytes)

julia> @btime g($(Iterators.flatten(i for i in (A, B))))
  149.500 μs (2 allocations: 64 bytes)

julia> @btime g($(Iterators.flatten([A, B])))
  17.130 ms (999498 allocations: 25.93 MiB)

julia> @btime g($(Iterators.flatten((A, Iterators.flatten((A, B))))))
  13.716 ms (398983 allocations: 10.67 MiB)

[adienes]

@nanosoldier runbenchmarks("collection" || "scalar" || "array", vs=":master")

[nanosoldier]

Your benchmark job has completed - possible performance regressions were detected. A full report can be found here.