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.