R 中的大矩阵:尚不支持长向量

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我在具有 400GB RAM 的 64 位 Ubuntu 环境中运行 64 位 R 3.1，但在处理大型矩阵时遇到了奇怪的限制.

I am running 64 bit R 3.1 in a 64bit Ubuntu environment with 400GB of RAM, and I am encountering a strange limitation when dealing with large matrices.

我有一个名为 A 的数字矩阵，它有 4000 行 x 950,000 列.当我尝试访问其中的任何元素时，收到以下错误:

I have a numeric matrix called A, that is 4000 rows by 950,000 columns. When I try to access any element in it, I receive the following error:

Error: long vectors not supported yet: subset.c:733

虽然我的矩阵是通过scan读入的，但你可以用下面的代码复制

Although my matrix was read in via scan, you can replicate with the following code

test <- matrix(1,4000,900000) #no error test[1,1] #error

我的谷歌搜索显示这是 R 3.0 之前的常见错误消息，其中大小为 2^31-1 的向量是限制.但是，鉴于我的环境，情况并非如此.

My Googling reveals this was a common error message prior to R 3.0, where a vector of size 2^31-1 was the limit. However, this is not the case, given my environment.

对于这种矩阵，我不应该使用原生矩阵类型吗?

Should I not be using the native matrix type for this kind of matrix?

推荐答案

矩阵只是一个具有维度属性的原子向量，它允许 R 作为矩阵访问它.你的矩阵是一个长度为 4000*9000000 的向量，它是 3.6e+10 个元素(最大的整数值大约是 2.147e+9).原子向量支持对长向量进行子集(即访问超出 2.147e+9 限制的元素).只需将您的矩阵视为一个长向量.

A matrix is just an atomic vector with a dimension attribute which allows R to access it as a matrix. Your matrix is a vector of length 4000*9000000 which is 3.6e+10 elements (the largest integer value is approx 2.147e+9). Subsetting a long vector is supported for atomic vectors (i.e. accessing elements beyond the 2.147e+9 limit). Just treat your matrix as a long vector.

如果我们记得默认情况下 R 会按列填充矩阵，那么如果我们想检索 test[ 2701 , 850000 ] 处的值，我们可以通过以下方式访问它:

If we remember that by default R fills matrices column-wise then if we wanted to retrieve say the value at test[ 2701 , 850000 ] we could access it via:

i <- ( 2701 - 1 ) * 850000 + 2701 test[i] #[1] 1

请注意，这确实是长向量子集，因为:

Note that this really is long vector subsetting because:

2701L * 850000L #[1] NA #Warning message: #In 2701L * 850000L : NAs produced by integer overflow