Using Hadoop Impersonation | DeployR 8.x

Applies to: DeployR 8.x (See comparison between 8.x and 9.x[1])

Looking for docs for Microsoft R Server 9? Start here[2].

Typically when invoking system commands from R, those commands will run as the user that started R. In the case of Hadoop, if user abc logs into a node on a Hadoop cluster and starts R, any system commands, such as system("hadoop fs -ls /"), will run as user abc. File permissions in HDFS will be honored accordingly, for example user abc will not be able to access files in HDFS if that user does not have proper permissions.

However when using DeployR, every R session is started as the same user. This is an artifact of the Rserve component that was used to create and interact with R sessions. In order to work around this circumstance, Hadoop Impersonation[3] will be used. Hadoop impersonation is employed by standard Hadoop services like Hue and WebHDFS.

The idea behind impersonation is that R will set an environment variable that tells Hadoop to run commands as a different user than the user who started the R session. You can use one of two Hadoop-supported environment variables:

  • HADOOP_USER_NAME for non-kerberos secured clusters
  • HADOOP_PROXY_USER for clusters secured with Kerberos.

This document assumes we are working with a Kerberos secured cluster.

The rest of the document will focus on the steps needed to get Hadoop Impersonation to work with DeployR.

Creating the 'rserve' User

Since, the DeployR Rserve component runs by default as the apache user who does not have a home directory, we recommend that you create a new user that:

  • Will be used when running Rserve
  • Has a home directory
  • Starts a bash shell

In this example, we will create the user rserve and change which user used to run Rserve.

Non Root Installation

If DeployR was installed as non-root, then you must ensure that the user that starts DeployR has a home directory and starts a bash shell. Nothing else is required.

Root Installation

If DeployR was installed as user root, do the following:

  1. Create the Linux user rserve.

  2. Go to the directory where DeployR is installed. For example:

    cd /opt/deploy/<version>

  3. Go the rserve sub-directory and open rserve.sh in an editor. For example:

    vi /opt/deploy/<version>/rserve/rserve.sh

  4. Replace all instances of apache with rserve.

    There are 2 instances of the string apache in the file.

  5. Give full write permissions to directory workdir. For example:

    chmod 777 /opt/deployr/<version>/rserve/workdir

  6. Edit /etc/group and add rserve as a member of group apache. For example:

    apache:x:502:rserve

  7. Restart Rserve.

    cd /opt/deploy/<version>/rserve
./rserve.sh stop
./rserve.sh start

Setting Up the Environment for the 'rserve' User

  • ScaleR: If you are using ScaleR inside Hadoop, add the following line to .bash_profile for user rserve. This will ensure all environment variables needed by ScaleR are set properly.

    . ./etc/profile.d/Revolution/bash_profile_additions

  • Kerberos: If your Hadoop cluster is secured using Kerberos, obtain a Kerberos ticket for principal hdfs. This ticket will act as the proxy for all other users.

    Be sure you are the Linux user rserve when obtaining the ticket. For example:

    su - rserve
kinit hdfs

We recommend that you use a cron job or equivalent to renew this ticket periodically to keep it from expiring.

Testing the Environment

  1. Create a private file in HDFS. In the following example, user revo owns the file:

    -rw-------   3 revo revo   14304763 2014-06-26 15:53 /share/AirlineDemoSmall/AirlineDemoSmall.csv

  2. Create a sample RScript that tries to access the file. For example:

    #in this case we read the file stored in HDFS into a dataframe

filename<-"/share/AirlineDemoSmall/AirlineDemoSmall.csv"
df<-read.table(pipe(paste('hadoop fs -cat ', filename, sep="")), sep=",", header=TRUE)
summary(df)

    When you run this program from the R console as user rserve, it will work because principal hdfs has a valid Kerberos ticket for the Linux user rserve.

  3. Modify the script to use the HADOOP_PROXY_USER environment variable. For example, add Sys.setenv(HADOOP_PROXY_USER='rserve'):

    #now we will run the script through the proxy

filename<-"/share/AirlineDemoSmall/AirlineDemoSmall.csv"
Sys.setenv(HADOOP_PROXY_USER='rserve')
df<-read.table(pipe(paste('hadoop fs -cat ', filename, sep="")), sep=",", header=TRUE)
summary(df)

    Unlike the previous step, when you run the script now, it will fail. This is due to the fact that the principal hdfs is no longer acting as a superuser for the command. Instead, it is acting as proxy for the user rserve. This is a subtle but important difference.

    > #now we will run the script through the proxy
>
> filename<-"/share/AirlineDemoSmall/AirlineDemoSmall.csv"
> Sys.setenv(HADOOP_PROXY_USER='rserve')
> df<-read.table(pipe(paste('hadoop fs -cat ', filename, sep="")), sep=",", header=TRUE)
cat: Permission denied: user=rserve, access=READ, inode="/share/AirlineDemoSmall/AirlineDemoSmall.csv":revo:revo:-rw-------
Error in read.table(pipe(paste("hadoop fs -cat ", filename, sep = "")),  :
 no lines available in input
> summary(df)
Error in object[[i]] : object of type 'closure' is not subsettable

  4. RScript for DeployR - We don't want to leave line of code that sets the HADOOP_PROXY_USER in our R Script. So we remove it and revert back to our original script. In addition, we will pass the filename into the script from our DeployR client application. So, the script simply becomes:

    df<-read.table(pipe(paste('hadoop fs -cat ', filename, sep="")), sep=",", header=TRUE)
summary(df)

We can now upload the script to DeployR using the Repository Manager. In our example, user testuser will create a directory called demo in the DeployR Repository Manager and name our RScript piperead.R.

Creating a DeployR Client

Create a DeployR client application to control which user will be running the script.

This example code is written in Visual Basic using the DeployR .NET client library. An equivalent example could be written in C#, Java or JavaScript.

Imports DeployR

Module Module1

    Sub Main()

        hdfsRead(False, "revo", "/share/AirlineDemoSmall/AirlineDemoSmall.csv", "piperead.R")

    End Sub

    Sub hdfsRead(ByVal bDebug As Boolean, _
                 ByVal sProxyUser As String, _
                 ByVal sHDFSfile As String, _
                 ByVal sRscript As String)


        Dim client As RClient
        Dim user As RUser
        Dim project As RProject
        Dim execution As RProjectExecution
        Dim options As New ProjectExecutionOptions
        Dim sEnv As String

        Try

            'set debug mode if we need it
            RClientFactory.setDebugMode(bDebug)

            'create an deployR client
            client = RClientFactory.createClient("http://localhost:7300/deployr", 10)

            'login
            Dim basic As New RBasicAuthentication("testuser", "changeme")
            user = client.login(basic, False)

            'create a temporary project
            project = user.createProject()

            'set the Environment Variable
            sEnv = "Sys.setenv(HADOOP_PROXY_USER='" + sProxyUser + "')"
            project.executeCode(sEnv)

            'collect the inputs
            options.rinputs.Add(RDataFactory.createString("filename", sHDFSfile))

            'execute the script
            execution = project.executeScript(sRscript, "demo", "testuser", "", options)

            'write the R console output
            Console.WriteLine(execution.about.console)

        Catch ex As Exception

            'print exception
            Console.WriteLine("Exception:  " + ex.Message)

            If (TypeOf ex Is HTTPRestException) Then
                Dim hex As HTTPRestException = DirectCast(ex, HTTPRestException)
                'print R console text, if available
                Console.WriteLine("Console:  " + hex.console)
            End If

        Finally

            'close the project
            project.close()

            'logout
            client.logout(user)

        End Try
    End Sub
End Module

Extending the Example

We can now extend this example to include two more RScripts for execution.

Second RScript

This script demonstrates how to copy a file from HDFS into the working directory of the R session. This RScript will be uploaded to the DeployR repository as copy_to_workspace.R, in directory demo for user testuser.

#copy a file from HDFS into the working directory

system(paste('hadoop fs -copyToLocal', filename,  getwd(), sep=" "))
df<-read.table(basename(filename), sep=",", header=TRUE)
summary(df)

Third RScript

This script runs a ScaleR algorithm as a MapReduce job in Hadoop. This RScript will be uploaded to the DeployR repository as scaleR_hadoop.R, in directory demo for user testuser.

#run an rxSummary on 'filename'

myNameNode <- "default"
myPort <- 0

myHadoopCluster <- RxHadoopMR(consoleOutput=TRUE, autoCleanup=TRUE, nameNode=myNameNode, port=myPort)
rxSetComputeContext(myHadoopCluster)

hdfsFS <- RxHdfsFileSystem(hostName=myNameNode, port=myPort)

colInfo <- list(DayOfWeek = list(type = "factor",
      levels = c("Monday", "Tuesday", "Wednesday", "Thursday",
      "Friday", "Saturday", "Sunday")))

airDS <- RxTextData(file = filename, missingValueString = "M",
      colInfo  = colInfo, fileSystem = hdfsFS)

adsSummary <- rxSummary(~ArrDelay+CRSDepTime+DayOfWeek, data = airDS)
print(adsSummary)

Update VB.NET code that executes all 3 examples

This is an update of the code shown here[4] that now reads in and executes all three scripts.

Imports DeployR

Module Module1

    Sub Main()

        hdfsRead(False, "revo", "/share/AirlineDemoSmall/AirlineDemoSmall.csv", "piperead.R")
        hdfsRead(False, "revo", "/share/AirlineDemoSmall/AirlineDemoSmall.csv", "copy_to_workspace.R")
        hdfsRead(False, "revo", "/share/AirlineDemoSmall/AirlineDemoSmall.csv", "scaleR_hadoop.R")

    End Sub

    Sub hdfsRead(ByVal bDebug As Boolean, _
                 ByVal sProxyUser As String, _
                 ByVal sHDFSfile As String, _
                 ByVal sRscript As String)


        Dim client As RClient
        Dim user As RUser
        Dim project As RProject
        Dim execution As RProjectExecution
        Dim options As New ProjectExecutionOptions
        Dim sEnv As String

        Try

            'set debug mode if we need it
            RClientFactory.setDebugMode(bDebug)

            'create an deployR client
            client = RClientFactory.createClient("http://localhost:7300/deployr", 10)

            'login
            Dim basic As New RBasicAuthentication("testuser", "changeme")
            user = client.login(basic, False)

            'create a temporary project
            project = user.createProject()

            'set the Environment Variable
            sEnv = "Sys.setenv(HADOOP_PROXY_USER='" + sProxyUser + "')"
            project.executeCode(sEnv)

            'collect the inputs
            options.rinputs.Add(RDataFactory.createString("filename", sHDFSfile))

            'execute the script
            execution = project.executeScript(sRscript, "demo", "testuser", "", options)

            'write the R console output
            Console.WriteLine(execution.about.console)

        Catch ex As Exception

            'print exception
            Console.WriteLine("Exception:  " + ex.Message)

            If (TypeOf ex Is HTTPRestException) Then
                Dim hex As HTTPRestException = DirectCast(ex, HTTPRestException)
                'print R console text, if available
                Console.WriteLine("Console:  " + hex.console)
            End If

        Finally

            'close the project
            project.close()

            'logout
            client.logout(user)

        End Try
    End Sub
End Module

References

  1. ^ comparison between 8.x and 9.x (msdn.microsoft.com)
  2. ^ Start here (msdn.microsoft.com)
  3. ^ Hadoop Impersonation (issues.apache.org)
  4. ^ code shown here (msdn.microsoft.com)

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