Skeleton tutorial

Raffaele A Calogero

Dissecting the skeleton.R

The skeleton function allows to control a bash script, skeleton.sh, located in docker.io/repbioinfo/ubuntu image in /bin.

The skeleton function has three parameters:

skeleton(group="docker", scratch.folder, data.folder)

  • group, a character string. Two options: sudo or docker, depending to which group the user belongs

  • scratch.folder, a character string indicating the path of the scratch folder. In principle the scratch folder is a temporary folder located in a disk with high I/O, e.g. a SSD disk, but if the fast disk is not available it represents only a temporary folder where the data generated by the application are saved.

  • data.folder, a character string indicating the folder where input data are located and where output will be written

The first step in the skeleton function is storing the working folder and grabbing the process time for subsequent performance evaluation.

Then, it is tested if docker demon is running,

  #testing if docker is running
  test <- dockerTest()
  if(!test){
    cat("\nERROR: Docker seems not to be installed in your system\n")
    return()
  }

checking if data folder exists and setting it as working folder,

  #setting the data.folder as working folder
  if (!file.exists(data.folder)){
    cat(paste("\nIt seems that the ",data.folder, " folder does not exist\n"))
    return(2)
  }
  setwd(data.folder)

checking if scratch folder exists and creating a temporary folder.

  #check  if scratch folder exist
  if (!file.exists(scratch.folder)){
    cat(paste("\nIt seems that the ",scratch.folder, " folder does not exist\n"))
    return(3)
  }
  tmp.folder <- gsub(":","-",gsub(" ","-",date()))
  scrat_tmp.folder=file.path(scratch.folder, tmp.folder)
  writeLines(scrat_tmp.folder,paste(data.folder,"/tempFolderID", sep=""))
  cat("\ncreating a folder in scratch folder\n")
  dir.create(file.path(scrat_tmp.folder))

Executing the docker command:

  • first is created a parameter string, which is made of:

    • –cidfile creates in data.folder the dockerID file that contains the docker job ID

    • -v the temporary folder, created in the scratch folder, is mounted as /scratch

    • -v the data folder is mounted as /data

    • -d docker.io/repbioinfo/ubuntu sh /bin/skeleton.sh is the command that executes the skeleton.sh script.

  • the parameter string is passed to the runDocker that execute the job. runDocker check if docker is running and return false when is finished

  #executing the docker job
  if(group=="sudo"){
    params <- paste("--cidfile ",data.folder,"/dockerID -v ",scrat_tmp.folder,":/scratch -v ", data.folder, ":/data -d docker.io/repbioinfo/ubuntu sh /bin/skeleton.sh", sep="")
    resultRun <- runDocker(group="sudo", params=params)
  }else{
    params <- paste("--cidfile ",data.folder,"/dockerID -v ",scrat_tmp.folder,":/scratch -v ", data.folder, ":/data -d docker.io/repbioinfo/ubuntu sh /bin/skeleton.sh", sep="")
    resultRun <- runDocker(group="docker", params=params)
  }

The skeleton.sh scripts in docker.io/repbioinfo/ubuntu is the following:

It writes hello world in the helloworld.txt and moves helloworld.txt to the data folder together with the run.info file, used to store information about the run, and the out.info, used to tell to the R script when the doker job is finished. The skeleton.sh scripts is a prototype for the handling of docker application(s).

Lets go back to the skeleton.R dissection:

The resultRun is used to check when the docker job is finished. The log of the docker job is saved with a name made of the first 12 letters of the docker job ID. Then, the docker container is deleted as well as the temporary folder and few other files: out.info, dockerID, tempFolderID. Finally the home folder is restored as working directory.

 #when container ends
 if(resultRun=="false"){
   #everything is copied to the input folder
    system(paste("mv ", scrat_tmp.folder,"/* ",data.folder, sep=""))
     #saving log and removing docker container
    container.id <- readLines(paste(data.folder,"/dockerID", sep=""), warn = FALSE)
    system(paste("docker logs ", substr(container.id,1,12), " &> ", substr(container.id,1,12),".log", sep=""))
    system(paste("docker rm ", container.id, sep=""))
    #removing temporary folder
    cat("\n\nRemoving the temporary file ....\n")
    system(paste("rm -R ",scrat_tmp.folder))
    system("rm -fR out.info")
    system("rm -fR dockerID")
    system("rm  -fR tempFolderID")
    system(paste("cp ",paste(path.package(package="docker4seq"),"containers/containers.txt",sep="/")," ",data.folder, sep=""))
 }

Then, the computing time is estimated and saved in the run.info file

  #running time 2
  ptm <- proc.time() - ptm
  dir <- dir(data.folder)
  dir <- dir[grep("run.info",dir)]
  if(length(dir)>0){
    con <- file("run.info", "r")
    tmp.run <- readLines(con)
    close(con)
    tmp.run[length(tmp.run)+1] <- paste("user run time mins ",ptm[1]/60, sep="")
    tmp.run[length(tmp.run)+1] <- paste("system run time mins ",ptm[2]/60, sep="")
    tmp.run[length(tmp.run)+1] <- paste("elapsed run time mins ",ptm[3]/60, sep="")
    writeLines(tmp.run,"run.info")
  }else{
    tmp.run <- NULL
    tmp.run[1] <- paste("run time mins ",ptm[1]/60, sep="")
    tmp.run[length(tmp.run)+1] <- paste("system run time mins ",ptm[2]/60, sep="")
    tmp.run[length(tmp.run)+1] <- paste("elapsed run time mins ",ptm[3]/60, sep="")
    writeLines(tmp.run,"run.info")
  }
  setwd(home)