Docker users

This section describes how to use H2O-3 on Docker. It walks you through the following steps:

  1. Installing Docker on Mac or Linux OS.

  2. Creating and modifying your Dockerfile.

  3. Building a Docker image from the Dockerfile.

  4. Running the Docker build.

  5. Launching H2O-3.

  6. Accessing H2O-3 from the web browser or from Python/R.

Prerequisites

  • Linux kernel verison 3.8+ or Mac OS 10.6+

  • VirtualBox

  • Latest version of Docker installed and configured

  • Docker daemon running (enter all following commands in the Docker daemon window)

  • In User directory (not root)

Note

  • Older Linux kernel versions can cause kernel panics that break Docker. There are ways around it, but attempt these at your own risk. Check the version of your kernel by running uname -r.

  • The Dockerfile always pulls the latest H2O-3 release.

  • The Docker image only needs to be built once.

Walkthrough

The following steps walk you through how to use H2O-3 on Docker.

Note

If the following commands don’t work, prepend them with sudo.

Step 1: Install and launch Docker

Depending on your operating system, select the appropriate installation method:

Note

By default, Docker allocates 2GB of memory for Mac installations. Be sure to increase this value. We suggest 3-4 times the size of the dataset for the amount of memory required.

Step 2: Create or download Dockerfile

  1. Create a folder on the Host OS to host your Dockerfile:

mkdir -p /data/h2o-{{branch_name}}

  1. Download or create a Dockerfile, which is a build recipe that builds the container. Download and use our Dockerfile template:

cd /data/h2o-<branch_name>
wget https://raw.githubusercontent.com/h2oai/h2o-3/master/Dockerfile

This Dockerfile will do the following:

  • Obtain and update the base image (Ubuntu 14.0.4).

  • Install Java 8.

  • Obtain and download the H2O-3 build from H2O-3’s S3 repository.

  • Expose ports 54321 and 54322 in preparation for launching H2O-3 on those ports.

Step 3: Build a Docker image from the Dockerfile

From the /data/h2o-<branch_name> directory, run the following (note that v5 represents the current version number):

docker build -t "h2o.ai/{{branch_name}}:v5"

Note

This process can take a few minutes because it assembles all the necessary parts for the image.

Step 4: Run the Docker build

On a mac, use the argument -p 54321:54321 to expressly map the port 54321 (this is not necessary on Linux).

docker run -ti -p 54321:54321 h2o.ai/{{branch_name}}:v5 /bin/bash

Step 5: Launch H2O-3

Navigate to the /opt directory and launch H2O-3. Update the value of -Xmx to the amount of memory you want ot allocate to the H2O-3 instance. By default, H2O-3 will launch on port 54321.

cd /opt
java -Xmx1g -jar h2o.jar

Step 6: Access H2O-3 from the web browser or Python/R

On Linux

On MacOS

After H2O-3 launches, copy and paste the IP address and port of the H2O-3 instance into the address bar of your browser. In the following example, the IP is 172.17.0.5:54321.

03:58:25.963 main      INFO WATER: Cloud of size 1 formed [/172.17.0.5:54321 (00:00:00.000)]

Locate the IP address of the Docker’s network (192.168.59.103 in the following example) that bridges to your Host OS by opening a new terminal window (not a bash for your container) and running boot2docker ip.

$ boot2docker ip
192.168.59.103

You can also view the IP address (192.168.99.100 in the following example) by scrolling to the top of the Docker daemon window:

                        ##         .
                  ## ## ##        ==
               ## ## ## ## ##    ===
           /"""""""""""""""""\___/ ===
      ~~~ {~~ ~~~~ ~~~ ~~~~ ~~~ ~ /  ===- ~~~
           \______ o           __/
             \    \         __/
              \____\_______/


docker is configured to use the default machine with IP 192.168.99.100
For help getting started, check out the docs at https://docs.docker.com

Access Flow

After obtaining the IP address, point your browser to the specified IP address and port to open Flow. In R and Python, you can access the instance by installing the latest version of the H2O R or Python package and then initializing H2O-3:

Python

R

# Initialize H2O
import h2o
docker_h2o = h2o.init(ip = "192.168.59.103", port = 54321)

# Initialize H2O
library(h2o)
dockerH2O <- h2o.init(ip = "192.168.59.103", port = 54321)