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map and reduce all support GDTable, but mapreduce does not.
using Distributed
# add two further julia processes which could run on other machinesaddprocs(2, exeflags="--threads=2")
# Distributed.@everywhere execute code on all machines@everywhereusing Dagger
# Dagger uses both Threads and Machines as processes
Dagger.all_processors()
using DTables, DataFrames, CSV, OnlineStats
url ="[https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv"](https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv%22)
files = [url, url, url, url, url]
d =DTable(DataFrame ∘ CSV.File ∘ download, files)
g = DTables.groupby(d, :species)
fetch(reduce(fit!, map(r -> (r.sepal_width,), g), init=Mean())) # worksfetch(mapreduce(r -> (r.sepal_width,), fit!, g, init=Mean())) # fails
map
andreduce
all supportGDTable
, butmapreduce
does not.the error is below
As the documentation recommends to use
mapreduce
overmap
+reduce
, it would be really good if mapreduce also supports GDTables.The text was updated successfully, but these errors were encountered: