我喜欢 data.table，它既快速又直观，还有什么更好的呢？data.table唉，这是我的问题：当在循环中引用 a 时foreach()（使用doMC实现），我偶尔会收到以下错误：
EXAMPEN IN APPENDIX
Error in { :
Internal error: .internal.selfref prot is not itself an extptr
这里令人讨厌的问题之一是我无法让它以任何一致性重现，但它会在一些长时间（几个小时）的任务中发生，所以我想确保它永远不会发生，如果可能的话。
由于我在每个循环中都引用了相同的data.table, DT，因此我尝试在每个循环的开头运行以下命令：
setattr(DT,".internal.selfref",NULL)
...删除无效/损坏的 self ref 属性。这有效，内部 selfref 错误不再发生。不过，这是一种解决方法。
解决根本问题的任何想法？
非常感谢您的帮助！
埃里克
附录：缩写 R 会话信息以确认最新版本：
R version 2.15.3 (2013-03-01)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
other attached packages:
[1] data.table_1.8.8 doMC_1.3.0
使用模拟数据的示例——您可能必须history()多次运行该函数（例如数百次）才能得到错误：
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Load packages and Prepare Data
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
require(data.table)
##this is the package we use for multicore
require(doMC)
##register n-2 of your machine's cores
registerDoMC(multicore:::detectCores()-2)
## Build simulated data
value.a <- runif(500,0,1)
value.b <- 1-value.a
value <- c(value.a,value.b)
answer.opt <- c(rep("a",500),rep("b",500))
answer.id <- rep( 6000:6499 , 2)
question.id <- rep( sample(c(1001,1010,1041,1121,1124),500,replace=TRUE) ,2)
date <- rep( (Sys.Date() - sample.int(150, size=500, replace=TRUE)) , 2)
user.id <- rep( sample(250:350, size=500, replace=TRUE) ,2)
condition <- substr(as.character(user.id),1,1)
condition[which(condition=="2")] <- "x"
condition[which(condition=="3")] <- "y"
##Put everything in a data.table
DT.full <- data.table(user.id = user.id,
answer.opt = answer.opt,
question.id = question.id,
date = date,
answer.id = answer.id,
condition = condition,
value = value)
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Daily Aggregation Function
##
##a basic function that aggregates all the values from
##all users for every question on a given day:
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
each.day <- function(val.date){
DT <- DT.full[ date < val.date ]
#count the number of updates per user (for weighting)
setkey(DT, question.id, user.id)
DT <- DT[ DT[answer.opt=="a",length(value),by="question.id,user.id"] ]
setnames(DT, "V1", "freq")
#retain only the most recent value from each user on each question
setkey(DT, question.id, user.id, answer.id)
DT <- DT[ DT[ ,answer.id == max(answer.id), by="question.id,user.id", ][[3]] ]
#now get a weighted mean (with freq) of the value for each question
records <- lapply(unique(DT$question.id), function(q.id) {
DT <- DT[ question.id == q.id ]
probs <- DT[ ,weighted.mean(value,freq), by="answer.opt" ]
return(data.table(q.id = rep(q.id,nrow(probs)),
ans.opt = probs$answer.opt,
date = rep(val.date,nrow(probs)),
value = probs$V1))
})
return(do.call("rbind",records))
}
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## foreach History Function
##
##to aggregate accross many days quickly
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
history <- function(start, end){
#define a sequence of dates
date.seq <- seq(as.Date(start),as.Date(end),by="day")
#now run a foreach to get the history for each date
hist <- foreach(day = date.seq, .combine = "rbind") %dopar% {
#setattr(DT,".internal.selfref",NULL) #resolves occasional internal selfref error
each.day(val.date = day)
}
}
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Examples
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
##aggregate only one day
each.day(val.date = "2012-12-13")
##generate a history
hist.example <- history (start = "2012-11-01", end = Sys.Date())