Question

This code works:

library(plyr)
x <- data.frame(V= c("X", "Y", "X", "Y", "Z" ), Z = 1:5)
ddply(x, .(V), function(df) sum(df$Z),.parallel=FALSE) 

While this code fails:

library(doSMP)
workers <- startWorkers(2)
registerDoSMP(workers)
x <- data.frame(V= c("X", "Y", "X", "Y", "Z" ), Z = 1:5)
ddply(x, .(V), function(df) sum(df$Z),.parallel=TRUE) 
stopWorkers(workers)

>Error in do.ply(i) : task 3 failed - "subscript out of bounds"
In addition: Warning messages:
1: <anonymous>: ... may be used in an incorrect context: ‘.fun(piece, ...)’

2: <anonymous>: ... may be used in an incorrect context: ‘.fun(piece, ...)’

I am using R 2.1.12, plyr 1.4 and doSMP 1.0-1. Has anyone figured out a way around this?

edit: In response to Andrie, here is a further illustration:

system.time(ddply(x, .(V), function(df) Sys.sleep(1), .parallel=FALSE)) #1
system.time(ddply(x, .(V), function(df) Sys.sleep(1), .parallel=TRUE)) #2
library(doSMP)
workers <- startWorkers(2)
registerDoSMP(workers)
x <- data.frame(V= c("X", "Y", "X", "Y", "Z" ), Z = 1:5)
system.time(ddply(x, .(V), function(df) Sys.sleep(1), .parallel=FALSE)) #3
system.time(ddply(x, .(V), function(df) Sys.sleep(1), .parallel=TRUE)) #4
stopWorkers(workers)

The first three functions work, but they all take about 3 seconds. Function #2 gives a warning that no parallel backend is registered, and thus executes sequentially. Function #4 gives the same error I referenced in my original post.

/edit: curioser and curiouser: On my mac, the following works:

library(plyr)
library(doMC)
registerDoMC()
x <- data.frame(V= c("X", "Y", "X", "Y", "Z" ), Z = 1:5)
ddply(x, .(V), function(df) sum(df$Z),.parallel=TRUE)

But this fails:

library(plyr)
library(doSMP)
workers <- startWorkers(2)
registerDoSMP(workers)
x <- data.frame(V= c("X", "Y", "X", "Y", "Z" ), Z = 1:5)
ddply(x, .(V), function(df) sum(df$Z),.parallel=TRUE) 
stopWorkers(workers)

And this fails too:

library(plyr)
library(snow)
library(doSNOW)
cl <- makeCluster(2, type = "SOCK")
registerDoSNOW(cl)
x <- data.frame(V= c("X", "Y", "X", "Y", "Z" ), Z = 1:5)
ddply(x, .(V), function(df) sum(df$Z),.parallel=TRUE) 
stopCluster(cl)

So I suppose the various parallel back ends for foreach are not interchangeable.

Answer 1

While the question has been answered well by @hadley, I want to add that I think plyr now works with other foreach parallel back-ends. Here is a link to a blog entry containing an example where plyr is used in conjunction with doSNOW: