我正在尝试使用 R 对大型数据集进行更简单的分析（素食包） ；我在具有较小数据集的本地机器（10 核，16GB 内存）上运行它取得了一些成功。然而，当我扩展我的分析以包含更大的数据集时，代码以如下错误终止：
error: cannot allocate vector of size XX gb
因此，我对 Amazon AWS 实例（更具体地说，一个 r3.8xlarge 实例：32 核，244GB ram）尝试了相同的分析，但我得到了同样的错误，这次最具体的是：
error: cannot allocate vector of size 105.4 gb
我尝试过的两个系统（本地和 AWS）都是 Ubuntu 机器，并且sessionInfo()有
R version 3.0.2 (2013-09-25)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
以下是我正在运行的相关代码行：
# read in data as DFs for mapping file
print("Loading mapping file...")
map_df = read.table(map, sep="\t", header=TRUE, strip.white=T)
rownames(map_df) = map_df[,1] # make first column the index so that we can join on it
map_df[,1] <- NULL # remove first column (we just turned it into the index)
# read in data as DF for biom file
print("Loading biom file...")
biom_df = data.frame(read.table(biom_file, sep="\t", header=TRUE), stringsAsFactors=FALSE)
biom_cols = dim(biom_df)[2] # number of columns in biom file, represents all the samples
otu_names <- as.vector(biom_df[,biom_cols]) # get otu taxonomy (last column) and save for later
biom_df[,biom_cols] <- NULL # remove taxonomy column
biom_df <- t(biom_df) # transpose to get OTUs as columns
biom_cols = dim(biom_df)[2] # number of columns in biom file, represents all the OTUs (now that we've transposed)
# merge our biom_df with map_df so that we reduce the samples down to those given in map_df
merged = merge(biom_df, map_df, by="row.names")
merged_cols = dim(merged)[2]
# clear some memory
rm(biom_df)
print("Total memory used:")
print(object.size(x=lapply(ls(), get)), units="Mb")
# simper analysis
print("Running simper analysis...")
sim <- simper(merged[,2:(biom_cols+1)], merged[,merged_cols], parallel=10)
有什么想法吗？