如何让doSMP与plyr很好地结合?

This code works:

这段代码:

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:

虽然这个代码失败:

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?

我使用的是r2.1.12、plyr 1.4和doSMP 1.0-1。有人想出办法来解决这个问题吗?

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

编辑:为了回应Andrie，这里有进一步的说明:

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.

前三个函数可以工作，但是它们都需要3秒。函数#2给出一个警告，没有注册任何并行后端，因此按顺序执行。函数#4给出了我在最初文章中引用的相同错误。

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

在我的mac上，下面的作品:

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:

但这种失败:

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:

这也失败:

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.

所以我认为对于每一个平行的后端是不可互换的。

3 个解决方案

#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:

虽然@hadley很好地回答了这个问题，但我想补充一点，我认为plyr现在可以与其他并行的后端一起工作。这里是一个博客条目的链接，其中包含了plyr与doSNOW一起使用的例子:

#2

Just to confirm @LeeZamparo's answer, plyr does now seem to work with snow, at least on on Windows 7 with R version 2.15.0. The last chunk of code in the question works, though with cryptic warnings:

只是为了证实@LeeZamparo的回答，plyr现在似乎确实可以在snow上运行，至少在Windows 7上可以在R版本2.15.0上运行。问题中的最后一段代码是有效的，尽管有一些隐晦的警告:

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)

library(microbenchmark)
mb <- microbenchmark(

      PP <- ddply(x, .(V), function(df) sum(df$Z),.parallel=TRUE),
      NP <- ddply(x, .(V), function(df) sum(df$Z),.parallel=FALSE) 
                     )

stopCluster(cl)

Cryptic warnings:

神秘的警告:

> warnings()
Warning messages:
1: <anonymous>: ... may be used in an incorrect context: ‘.fun(piece, ...

It's not quick, I guess that's the overhead...

它不快，我猜那是开销……

> mb
Unit: milliseconds
                                                             expr
1 NP <- ddply(x, .(V), function(df) sum(df$Z), .parallel = FALSE)
2 PP <- ddply(x, .(V), function(df) sum(df$Z), .parallel = TRUE)
        min        lq    median        uq       max
1  11.91518  15.74567  20.10944  23.30453  38.09237
2 314.58008 336.81160 348.42421 358.57337 575.11220

Check it gives the expected result

检查它是否给出了预期的结果

> PP
  V V1
1 X  4
2 Y  6
3 Z  5

Extra details about this session:

关于这次会议的额外细节:

> sessionInfo()
R version 2.15.0 (2012-03-30)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=English_Australia.1252  LC_CTYPE=English_Australia.1252   
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C                      
[5] LC_TIME=English_Australia.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] microbenchmark_1.1-3 doSNOW_1.0.6         iterators_1.0.6     
[4] foreach_1.4.0        plyr_1.7.1           snow_0.3-10          

loaded via a namespace (and not attached):
[1] codetools_0.2-8 compiler_2.15.0 tools_2.15.0

#3

It turns out plyr only works with doMC, but the developer is working on it.

事实证明，plyr只适用于doMC，但是开发人员正在研究它。