R: Memory management during xmlEventParse of Huge (> 20GB) files

Question

Based on this previous question ( see here ), I am trying to read in many large xml files via xmlEventParse, while preserving node-valued data. Working with this xml sample: https://www.nlm.nih.gov/databases/dtd/medsamp2015.xml .

The code below uses xpathSapply to retrieve the necessary values ​​and a sequence of if statements to combine the values ​​in a way that corresponds to a unique value (PMID) for each of the non-unique values ​​(LastName) in the record - for which LastNames cannot be. The goal is to write a series of small csv along the way (here, after every 1000 LastNames) to minimize the amount of memory used.

When run in a full-sized data set, the code successfully displays the files in batches, however, something is still stored in memory, which ultimately causes a system error after using the entire RAM. I watched the task manager while running the code and see how R-memory grows as the program moves. And if I stop the program in the middle, and then clear the R workspace, including hidden elements, the memory is still used by R. This happens until I turn off R - this is the memory freed up again.

Run this a few times yourself, and you will see that the use of R-memory is growing even after cleaning the workspace.

Please, help! This problem seems to be common among others reading in large XML files this way (see for example the comments on this question ).

:

library(XML)

filename <- "~/Desktop/medsamp2015.xml"

tempdat <- data.frame(pmid=as.numeric(),
                      lname=character(), 
                      stringsAsFactors=FALSE) 
cnt <- 1
branchFunction <- function() {
  func <- function(x, ...) {
    v1 <- xpathSApply(x, path = "//PMID", xmlValue)
    v2 <- xpathSApply(x, path = "//Author/LastName", xmlValue)
    print(cbind(c(rep(v1,length(v2))), v2))

    #below is where I store/write the temp data along the way
    #but even without doing this, memory is used (even after clearing)

    tempdat <<- rbind(tempdat,cbind(c(rep(v1,length(v2))), v2))
    if (nrow(tempdat) > 1000){
      outname <- paste0("~/Desktop/outfiles",cnt,".csv")
      write.csv(tempdat, outname , row.names = F)
      tempdat <<- data.frame(pmid=as.numeric(),
                            lname=character(), 
                            stringsAsFactors=FALSE)
      cnt <<- cnt+1
    }
  }
  list(MedlineCitation = func)
}

myfunctions <- branchFunction()

#RUN
xmlEventParse(
  file = filename, 
  handlers = NULL, 
  branches = myfunctions
)

Answer 1

, script invoke.sh, R script URL ... medsamp2015.xml ./data.

• invoke.sh script . R, , .

: - . , print() 62.

print( cbind(c(rep(v1, length(v2))), v2))

• : runtime.txt .
• .csv ./data.

: , : R Windows. , .

Script

  1 #!/usr/local/bin/bash -x
  2
  3 R --no-save -q --slave < ./47162861.R --args "https://www.nlm.nih.gov/databases/dtd" "medsamp2015.xml"

R - 47162861.R

# Set working directory

projectDir <- "~/dev/stackoverflow/47162861"
setwd(projectDir)

# -----------------------------------------------------------------------------
# Load required Packages...
requiredPackages <- c("XML")

ipak <- function(pkg) {
  new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
  if (length(new.pkg))
    install.packages(new.pkg, dependencies = TRUE)
  sapply(pkg, require, character.only = TRUE)
}

ipak(requiredPackages)

# -----------------------------------------------------------------------------
# Load required Files
# trailingOnly=TRUE means that only your arguments are returned
args <- commandArgs(trailingOnly = TRUE)

if ( length(args) != 0 ) {
  dataDir <- file.path(projectDir,"data")
  fileUrl = args[1]
  fileName = args[2]
} else {
  dataDir <- file.path(projectDir,"data")
  fileUrl <- "https://www.nlm.nih.gov/databases/dtd"
  fileName <- "medsamp2015.xml"
}

# -----------------------------------------------------------------------------
# Download file

# Does the directory Exist? If it does'nt create it
if (!file.exists(dataDir)) {
  dir.create(dataDir)
}

# Now we check if we have downloaded the data already if not we download it

if (!file.exists(file.path(dataDir, fileName))) {
  download.file(fileUrl, file.path(dataDir, fileName), method = "wget")
}

# -----------------------------------------------------------------------------
# Now we extrat the data

tempdat <- data.frame(pmid = as.numeric(), lname = character(),
  stringsAsFactors = FALSE)
cnt <- 1

branchFunction <- function() {
  func <- function(x, ...) {
    v1 <- xpathSApply(x, path = "//PMID", xmlValue)
    v2 <- xpathSApply(x, path = "//Author/LastName", xmlValue)
    print(cbind(c(rep(v1, length(v2))), v2))

    # below is where I store/write the temp data along the way
    # but even without doing this, memory is used (even after
    # clearing)

    tempdat <<- rbind(tempdat, cbind(c(rep(v1, length(v2))),
      v2))
    if (nrow(tempdat) > 1000) {
      outname <- file.path(dataDir, paste0(cnt, ".csv")) # Create FileName
      write.csv(tempdat, outname, row.names = F) # Write File to created directory
      tempdat <<- data.frame(pmid = as.numeric(), lname = character(),
        stringsAsFactors = FALSE)
      cnt <<- cnt + 1
    }
  }
  list(MedlineCitation = func)
}

myfunctions <- branchFunction()

# -----------------------------------------------------------------------------
# RUN
xmlEventParse(file = file.path(dataDir, fileName),
              handlers = NULL,
              branches = myfunctions)

~/dev/stackoverflow/47162861/data/medsamp2015.xml

$ ll                                                            
total 2128
drwxr-xr-x@ 7 hidden  staff   238B Nov 10 11:05 .
drwxr-xr-x@ 9 hidden  staff   306B Nov 10 11:11 ..
-rw-r--r--@ 1 hidden  staff    32K Nov 10 11:12 1.csv
-rw-r--r--@ 1 hidden  staff    20K Nov 10 11:12 2.csv
-rw-r--r--@ 1 hidden  staff    23K Nov 10 11:12 3.csv
-rw-r--r--@ 1 hidden  staff    37K Nov 10 11:12 4.csv
-rw-r--r--@ 1 hidden  staff   942K Nov 10 11:05 medsamp2015.xml

> ./invoke.sh > runtime.txt
+ R --no-save -q --slave --args https://www.nlm.nih.gov/databases/dtd medsamp2015.xml
Loading required package: XML

: runtime.txt