`mapCube` in Distributed model is many times slower

[kongdd]

Serial: 8s

using YAXArrays, Statistics, Zarr
using DimensionalData
using Dates
axlist = (
    Dim{:time}(Date("2022-01-01"):Day(1):Date("2022-12-31")),
    Dim{:lon}(range(1, 10, length=1000)),
    Dim{:lat}(range(1, 5, length=1500)),
    Dim{:Variable}(["var1", "var2"])
    )

data = rand(axlist...)
ds = YAXArray(axlist, data)
c = ds[Variable = At("var1")] # see OpenNetCDF to get the file
c2 = setchunks(c, (365, 100, 150))

function mymean(output, xin)
    # @show "doing a mean"
    output[:] .= mean(xin)
end

indims = InDims("time")
outdims = OutDims()
@time resultcube = mapCube(mymean, c2; indims, outdims)

Parallel: 660 seconds

using Distributed
addprocs(4)
# @everywhere using Pkg
# @everywhere Pkg.activate(".")
@everywhere begin
  # using NetCDF
  using YAXArrays
  using Statistics
  using Zarr
end

@everywhere function mymean(output, xin)
    # @show "doing a mean"
    output[:] .= mean(xin)
end

indims = InDims("time")
outdims = OutDims()

# turn out to be slower? why?
@time resultcube2 = mapCube(mymean, c2; indims, outdims)