r

Running R on AWS Lambda

You can run the software environment for statistical computing R in AWS Lambda via SCAR using the grycap/r-base-lambda Docker image, based on the debian:stretch-slim one.

Usage on AWS Lambda via SCAR

You can run a container out of this image on AWS Lambda via SCAR using the following procedure:

1. Create the Lambda function

scar init -f scar-r.yaml

2. Execute the Lambda function with an script to compile and run R commands

scar run -f scar-r.yaml -s r-demo.sh

The first invocation will take considerably longer than the subsequent ones, where the container will be cached. You can modify the script and perform another scar run.

You can also run multiple concurrent invocations of this Lambda function to perform highly-parallel event-driven processing. See the SCAR Programming Model.

Appendix. How to create a minimalistic package for R

TL;DR;

R will be installed on a debian:stretch-slim Docker container. The R executable together with the dependent dynamic libraries will be packaged as a compressed file, that later will be deployed in a new container (when building the image in Docker Hub).

Step-by-step procedure

The installation is inspired on this one, with the following changes:

• Adapted to Python 3.
• Debian-based installation.
• Changes in R script to use the R_HOME environment variable.

1. Deploy a Docker container out of the debian:stretch-slim image:

docker run -ti --name rlang-deb-slim debian:stretch-slim bash

2. Install the required packages inside the container

apt-get install -y python3 gcc gcc  libgfortran3 python3-pip r-base wget liblapack3 zip

3. Install virtualenv and the Survival R package

pip3 install virtualenv
wget https://cran.r-project.org/src/contrib/Archive/survival/survival_2.39-4.tar.gz
R CMD INSTALL survival_2.39-4.tar.gz

4. Create a virtualenv and install rpy2, to use R from python (not strictly necessary for SCAR).

cd
virtualenv ~/env && source ~/env/bin/activate
pip3 install rpy2

5. Create the package that includes the executable together with the libraries.

You can use ldd to find out the dynamic libraries required by the R executable file:

ldd /usr/lib/R/bin/exec/R
    linux-vdso.so.1 (0x00007ffdd39fc000)
    libR.so => /usr/lib/libR.so (0x00007fe713e62000)
    libgomp.so.1 => /usr/lib/x86_64-linux-gnu/libgomp.so.1 (0x00007fe713c35000)
    libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007fe713a18000)
    libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fe713679000)
    libblas.so.3 => /usr/lib/libblas.so.3 (0x00007fe71340c000)
    libgfortran.so.3 => /usr/lib/x86_64-linux-gnu/libgfortran.so.3 (0x00007fe7130e6000)
    libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007fe712de2000)
    libquadmath.so.0 => /usr/lib/x86_64-linux-gnu/libquadmath.so.0 (0x00007fe712ba3000)
    libreadline.so.7 => /lib/x86_64-linux-gnu/libreadline.so.7 (0x00007fe712956000)
    libpcre.so.3 => /lib/x86_64-linux-gnu/libpcre.so.3 (0x00007fe7126e3000)
    liblzma.so.5 => /lib/x86_64-linux-gnu/liblzma.so.5 (0x00007fe7124bd000)
    libbz2.so.1.0 => /lib/x86_64-linux-gnu/libbz2.so.1.0 (0x00007fe7122ad000)
    libz.so.1 => /lib/x86_64-linux-gnu/libz.so.1 (0x00007fe712093000)
    librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007fe711e8b000)
    libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007fe711c87000)
    libicuuc.so.57 => /usr/lib/x86_64-linux-gnu/libicuuc.so.57 (0x00007fe7118df000)
    libicui18n.so.57 => /usr/lib/x86_64-linux-gnu/libicui18n.so.57 (0x00007fe711465000)
    /lib64/ld-linux-x86-64.so.2 (0x00007fe714684000)
    libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007fe71124e000)
    libtinfo.so.5 => /lib/x86_64-linux-gnu/libtinfo.so.5 (0x00007fe711024000)
    libicudata.so.57 => /usr/lib/x86_64-linux-gnu/libicudata.so.57 (0x00007fe70f5a7000)
    libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007fe70f225000)

Create a directory for the files and copy R inside:

mkdir $HOME/lambda && cd $HOME/lambda
cp -Lr /usr/lib/R/* $HOME/lambda/
cp $HOME/lambda/bin/exec/R $HOME/lambda

Do not forget the -L options in order to follow the symlinks when copying the files.

Copy the required libraries:

cp  /usr/lib/R/lib/libR.so $HOME/lambda/lib/
cp  /usr/lib/x86_64-linux-gnu/libgomp.so.1 $HOME/lambda/lib
cp  /lib/x86_64-linux-gnu/libpthread.so.0 $HOME/lambda/lib
cp  /usr/lib/libblas.so.3 $HOME/lambda/lib 
cp /usr/lib/x86_64-linux-gnu/libgfortran.so.3 $HOME/lambda/lib
cp  /usr/lib/x86_64-linux-gnu/libquadmath.so.0 $HOME/lambda/lib 
cp /lib/x86_64-linux-gnu/libreadline.so.7 $HOME/lambda/lib 
cp /lib/x86_64-linux-gnu/libpcre.so.3 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/liblzma.so.5 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/libbz2.so.1.0 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/libz.so.1 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/librt.so.1 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/libdl.so.2 $HOME/lambda/lib
cp /usr/lib/x86_64-linux-gnu/libicuuc.so.57 $HOME/lambda/lib
cp /usr/lib/x86_64-linux-gnu/libicui18n.so.57 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/libgcc_s.so.1 $HOME/lambda/lib
cp /lib/x86_64-linux-gnu/libtinfo.so.5 $HOME/lambda/lib
cp /usr/lib/x86_64-linux-gnu/libicudata.so.57 $HOME/lambda/lib
cp /usr/lib/x86_64-linux-gnu/libstdc++.so.6 $HOME/lambda/lib
cp /usr/lib/lapack/liblapack.so.3 $HOME/lambda/lib

Add the Python libraries to that folder

cp -r /root/env/lib/python3.5/site-packages/ $HOME/lambda

Modify the /root/lambda/bin/R shell-script file so that:

R_HOME_DIR=$R_HOME

This is required in order to later be able to start R from that folder.

6. Create the deployment package

cd $HOME/lambda
tar czvf /tmp/rlang-debslim.tgz *

7. (Optional) Test the application

Once the rlang-debslim.tgz file has been decompressed in another machine, you can run the application by defining the appropriate environment variables and then executing R, as follows:

export R_HOME=$HOME
export LD_LIBRARY_PATH=$HOME/lib
export PATH=$PATH:$HOME/bin
R