技巧以管理R会话中的可用内存 [英] Tricks to manage the available memory in an R session

问题描述

人们使用什么技巧来管理交互式R会话的可用内存?我使用下面的函数(基于Petr Pikal和David Hinds在2004年r-help列表中的发布)列出(和/或排序)最大的对象，并偶尔rm()其中一些.但是到目前为止，最有效的解决方案是...在具有足够内存的64位Linux下运行.

What tricks do people use to manage the available memory of an interactive R session? I use the functions below [based on postings by Petr Pikal and David Hinds to the r-help list in 2004] to list (and/or sort) the largest objects and to occassionally rm() some of them. But by far the most effective solution was ... to run under 64-bit Linux with ample memory.

人们还想分享其他有趣的技巧吗?请每个帖子一篇.

Any other nice tricks folks want to share? One per post, please.

# improved list of objects
.ls.objects <- function (pos = 1, pattern, order.by,
                        decreasing=FALSE, head=FALSE, n=5) {
    napply <- function(names, fn) sapply(names, function(x)
                                         fn(get(x, pos = pos)))
    names <- ls(pos = pos, pattern = pattern)
    obj.class <- napply(names, function(x) as.character(class(x))[1])
    obj.mode <- napply(names, mode)
    obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class)
    obj.size <- napply(names, object.size)
    obj.dim <- t(napply(names, function(x)
                        as.numeric(dim(x))[1:2]))
    vec <- is.na(obj.dim)[, 1] & (obj.type != "function")
    obj.dim[vec, 1] <- napply(names, length)[vec]
    out <- data.frame(obj.type, obj.size, obj.dim)
    names(out) <- c("Type", "Size", "Rows", "Columns")
    if (!missing(order.by))
        out <- out[order(out[[order.by]], decreasing=decreasing), ]
    if (head)
        out <- head(out, n)
    out
}
# shorthand
lsos <- function(..., n=10) {
    .ls.objects(..., order.by="Size", decreasing=TRUE, head=TRUE, n=n)
}

推荐答案

为进一步说明频繁重启的常见策略，我们可以使用

To further illustrate the common strategy of frequent restarts, we can use littler which allows us to run simple expressions directly from the command-line. Here is an example I sometimes use to time different BLAS for a simple crossprod.

 r -e'N<-3*10^3; M<-matrix(rnorm(N*N),ncol=N); print(system.time(crossprod(M)))'

同样，

 r -lMatrix -e'example(spMatrix)'

(通过--packages | -l开关)加载Matrix包并运行spMatrix函数的示例.由于r总是从新鲜"开始，因此此方法在包装开发过程中也是一个很好的测试.

loads the Matrix package (via the --packages | -l switch) and runs the examples of the spMatrix function. As r always starts 'fresh', this method is also a good test during package development.

最后但并非最不重要的一点是，在使用'#！/usr/bin/r'shebang-header的脚本中，r对于自动批处理模式也非常有效. Rscript是无法使用littler的替代方法(例如，在Windows上).

Last but not least r also work great for automated batch mode in scripts using the '#!/usr/bin/r' shebang-header. Rscript is an alternative where littler is unavailable (e.g. on Windows).

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