[Rcpp-devel] Struggling with cppFunction() and clusterExport()

[Matteo Fasiolo]

Thanks a lot for your replies, I will go for the package solution, given
that
I'm organizing all my code in a package in any case.
Matteo


On Thu, Sep 26, 2013 at 6:15 PM, Romain Francois
<romain at r-enthusiasts.com>wrote:

> The usual way is to put the function in a package and load the package.
>
> Otherwise, you could do something along these lines
>
> auto_function <- function( code, ... ){
>     dots <- list(code, ...)
>     function(...){
>         do.call( cppFunction, dots )( ... )
>     }
> }
>
> This way the function knows how to compile itself, for example:
>
> > fun <- auto_function(' double inner_Cpp(double a){ return 1;  } ' )
> # this takes a while the first time
> > fun( 2 )
> [1] 1
> # this is instant thanks to caching of sourceCpp
> > fun( 2 )
> [1] 1
>
> Romain
>
> Le 26/09/13 18:57, Matteo Fasiolo a écrit :
>
>  Dear Rcpp developers,
>>
>>   I'm trying to parallelize some of my algorithms but I have encountered
>> the following problem:
>>
>> # I have a cppFunction
>> cppFunction(' double inner_Cpp(double a){ return 1;  } ')
>>
>> # And an R wrapper around it
>> wrapper_R<- function(input)
>> {
>>    inner_Cpp(input)
>> }
>>
>> # And I want to call the wrappen in parallel within algorithm
>> algo <- function(input)
>> {
>>    cl <- makeCluster(2)
>>    clusterExport(cl, "inner_Cpp")
>>    a <- clusterApply(cl, 1:2, wrapper_R)
>>    stopCluster(cl)
>>    a
>> }
>>
>> algo(2)
>>
>> Error in checkForRemoteErrors(val) :
>>    2 nodes produced errors; first error: NULL value passed as symbol
>> address
>>
>> It seems that I'm unable to find the address of inner_Cpp.
>> If the inner function is an R function there is no problem:
>>
>> inner_R <- function(input) 1
>>
>> wrapper_R<- function(input)
>> {
>>    inner_R(input)
>> }
>>
>> algo <- function(input)
>> {
>>    cl <- makeCluster(2)
>>    clusterExport(cl, "inner_R")
>>    a <- clusterApply(cl, 1:2, wrapper_R)
>>    stopCluster(cl)
>>    a
>> }
>>
>> algo(2)
>>
>> [[1]]
>> [1] 1
>>
>> [[2]]
>> [1] 1
>>
>> Do you have any idea about why this is happening?
>> Given that I have just started parallelizing my algorithms in this
>> way, any suggestion/criticism about the overall approach is
>> more then welcome!
>>
>> Matteo
>>
>
>
> --
> Romain Francois
> Professional R Enthusiast
> +33(0) 6 28 91 30 30
>
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