Using H2O with Microsoft R Open on Linux Machine


Microsoft R Open Page:

Ubuntu Download link:

$ wget
$ tar -xvf microsoft-r-open-3.3.3.tar.gz
$ cd microsoft-r-open
$ sudo bash

Installation will be done into the following folder:

$ ll /usr/lib64/microsoft-r/3.3/lib64/R/bin/

drwxr-xr-x 11 root root 4096 Apr 20 15:28 ./
drwxr-xr-x 4 root root 4096 Apr 20 15:28 ../
drwxr-xr-x 3 root root 4096 Apr 20 15:28 backup/
drwxr-xr-x 3 root root 4096 Apr 20 15:28 bin/
-rw-r--r-- 1 root root 18011 Mar 28 13:35 COPYING
drwxr-xr-x 4 root root 4096 Apr 20 15:28 doc/
drwxr-xr-x 2 root root 4096 Apr 20 15:28 etc/
drwxr-xr-x 3 root root 4096 Apr 20 15:28 include/
drwxr-xr-x 2 root root 4096 Apr 20 15:28 lib/
drwxr-xr-x 47 root root 4096 Apr 20 15:28 library/
drwxr-xr-x 2 root root 4096 Apr 20 15:28 modules/
drwxr-xr-x 13 root root 4096 Apr 20 15:28 share/
-rw-r--r-- 1 root root 46 Mar 28 13:35 SVN-REVISION

Note If you already have R installed in the machine you may see Microsoft R link is not created and previous R is still available at /usr/bin/R. If that is the case you may need to create the symbolic link as below.

Creating symbolic link:

$ sudo ln -s /usr/lib64/microsoft-r/3.3/lib64/R/bin/R /usr/bin/MSR

Launching R:

You just need to do the following:

$ R

If you have created the symbolic link then use the following


Installing RCurl which is must to have for H2O:

> install.packages(“RCurl”)

Now installing H2O latest from the H2O Download link (

> install.packages(“h2o”, type = “source”, repos = (c(“”))) :

Once H2O is installed you can use it. Here is the full execution log:



R version 3.3.3 (2017-03-06) -- "Another Canoe"
Copyright (C) 2017 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

Microsoft R Open 3.3.3
The enhanced R distribution from Microsoft
Microsoft packages Copyright (C) 2017 Microsoft Corporation
Using the Intel MKL for parallel mathematical computing(using 16 cores).
Default CRAN mirror snapshot taken on 2017-03-15.

> library(h2o)
Your next step is to start H2O:
    > h2o.init()
For H2O package documentation, ask for help:
    > ??h2o
After starting H2O, you can use the Web UI at http://localhost:54321
For more information visit
Attaching package: ‘h2o’
The following objects are masked from ‘package:stats’:
    cor, sd, var
The following objects are masked from ‘package:base’:
    &&, %*%, %in%, ||, apply, as.factor, as.numeric, colnames,
    colnames<-, ifelse, is.character, is.factor, is.numeric, log,
    log10, log1p, log2, round, signif, trunc

> h2o.init()
H2O is not running yet, starting it now...
Note: In case of errors look at the following log files:
openjdk version "1.8.0_121"
OpenJDK Runtime Environment (build 1.8.0_121-8u121-b13-0ubuntu1.16.04.2-b13)
OpenJDK 64-Bit Server VM (build 25.121-b13, mixed mode)

Starting H2O JVM and connecting: .. Connection successful!

R is connected to the H2O cluster:
    H2O cluster uptime: 2 seconds 536 milliseconds
    H2O cluster version: 3.10.4.
    H2O cluster version age: 22 hours and 35 minutes
    H2O cluster name: H2O_started_from_R_avkash_tco537
    H2O cluster total nodes: 1
    H2O cluster total memory: 26.67 GB
    H2O cluster total cores: 32
    H2O cluster allowed cores: 2
    H2O cluster healthy: TRUE
    H2O Connection ip: localhost
    H2O Connection port: 54321
    H2O Connection proxy: NA
    H2O Internal Security: FALSE
    R Version: R version 3.3.3 (2017-03-06)

Note: As started, H2O is limited to the CRAN default of 2 CPUs.
       Shut down and restart H2O as shown below to use all your CPUs.
           > h2o.shutdown()
           > h2o.init(nthreads = -1)

> h2o.clusterStatus()

Cluster name: H2O_started_from_R_avkash_tco537
Cluster size: 1
Cluster is locked

h2o healthy last_ping num_cpus sys_load
1 localhost/ TRUE 1.492729e+12 32 0.88
  mem_value_size free_mem pojo_mem swap_mem free_disk max_disk pid

1 0 28537698304 93668352 0 47189065728 235825790976 25530
  num_keys tcps_active open_fds rpcs_active



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