H₂O

Get started with H₂O in 3 easy steps

1. Download H₂O. This is a zip file that contains everything you need to get started.

2. From your terminal, run:

cd ~/Downloads
unzip h2o-3.0.1.7.zip
cd h2o-3.0.1.7
java -jar h2o.jar

3. Point your browser to http://localhost:54321

Use H₂O directly from Python

1. Prerequisite: Python 2.7

2. Install dependencies:

pip install requests
pip install tabulate

At the command line, copy and paste these commands one line at a time:

# The following command removes the H₂O module for Python.
pip uninstall h2o

# Next, use pip to install this version of the H₂O Python module.
pip install /Python/h2o-3.0.1.7-py2.py3-none-any.whl

Use H₂O directly from R

Copy and paste these commands into R one line at a time:

# The following two commands remove any previously installed H₂O packages for R.
if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }

# Next, we download packages that H₂O depends on.
if (! ("methods" %in% rownames(installed.packages()))) { install.packages("methods") }
if (! ("statmod" %in% rownames(installed.packages()))) { install.packages("statmod") }
if (! ("stats" %in% rownames(installed.packages()))) { install.packages("stats") }
if (! ("graphics" %in% rownames(installed.packages()))) { install.packages("graphics") }
if (! ("RCurl" %in% rownames(installed.packages()))) { install.packages("RCurl") }
if (! ("rjson" %in% rownames(installed.packages()))) { install.packages("rjson") }
if (! ("tools" %in% rownames(installed.packages()))) { install.packages("tools") }
if (! ("utils" %in% rownames(installed.packages()))) { install.packages("utils") }

# Now we download, install and initialize the H₂O package for R.
install.packages("h2o", type="source", repos=(c("/R")))
library(h2o)
localH2O = h2o.init()

# Finally, let's run a demo to see H₂O at work.
demo(h2o.kmeans)

Run H₂O on Hadoop in just 3 steps

1. Download H₂O for your version of Hadoop. This is a zip file that contains everything you need to get started.

wget /h2o-3.0.1.7-cdh5.2.zip
wget /h2o-3.0.1.7-cdh5.3.zip
wget /h2o-3.0.1.7-cdh5.4.2.zip
wget /h2o-3.0.1.7-hdp2.1.zip
wget /h2o-3.0.1.7-hdp2.2.zip
wget /h2o-3.0.1.7-mapr3.1.1.zip
wget /h2o-3.0.1.7-mapr4.0.1.zip

2. Unpack the zip file and launch a 6g instance of H₂O:

unzip h2o-3.0.1.7-*.zip
cd h2o-3.0.1.7-*
hadoop jar h2odriver.jar -nodes 1 -mapperXmx 6g -output hdfsOutputDirName

3. Point your browser to H2O (see "Open H2O Flow in your web browser" in the output below):

Determining driver host interface for mapper->driver callback...
[Possible callback IP address: 172.16.2.181]
[Possible callback IP address: 127.0.0.1]
...
Waiting for H2O cluster to come up...
H2O node 172.16.2.188:54321 requested flatfile
Sending flatfiles to nodes...
[Sending flatfile to node 172.16.2.188:54321]
H2O node 172.16.2.188:54321 reports H2O cluster size 1
H2O cluster (1 nodes) is up
(Note: Use the -disown option to exit the driver after cluster formation)

Open H2O Flow in your web browser: http://172.16.2.188:54321

(Press Ctrl-C to kill the cluster)
Blocking until the H2O cluster shuts down...

Gradle-style specification for Maven artifacts

See the h2o-droplets github repository for a working example.

def h2oProjectVersion = "3.0.1.7"

repositories {
 maven {
  url "/maven/repo/"
 }
}

dependencies {
 compile "ai.h2o:h2o-core:${h2oProjectVersion}"
 compile "ai.h2o:h2o-algos:${h2oProjectVersion}"
 compile "ai.h2o:h2o-web:${h2oProjectVersion}"
 compile "ai.h2o:h2o-app:${h2oProjectVersion}"
}