firef0x/h2oai repository overview

⁠H2O

H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Flow notebook/web interface, and works seamlessly with big data technologies like Hadoop and Spark. H2O provides implementations of many popular algorithms such as GBM⁠, Random Forest⁠, Deep Neural Networks⁠, Word2Vec⁠ and Stacked Ensembles⁠. H2O is extensible so that developers can add data transformations and custom algorithms of their choice and access them through all of those clients.

Data collection is easy. Decision making is hard. H2O makes it fast and easy to derive insights from your data through faster and better predictive modeling. H2O allows online scoring and modeling in a single platform.

H2O-3 (this repository) is the third incarnation of H2O, and the successor to H2O-2⁠.

⁠Table of Contents

• Downloading H2O-3⁠
• Open Source Resources⁠
  • Issue Tracking and Feature Requests⁠
  • List of H2O Resources⁠
• Using H2O-3 Code Artifacts (libraries)⁠
• Building H2O-3⁠
• Launching H2O after Building⁠
• Building H2O on Hadoop⁠
• Sparkling Water⁠
• Documentation⁠
• Citing H2O⁠
• Community⁠ / Advisors⁠ / Investors⁠

⁠1. Downloading H2O-3

While most of this README is written for developers who do their own builds, most H2O users just download and use a pre-built version. If you are a Python or R user, the easiest way to install H2O is via PyPI⁠ or Anaconda⁠ (for Python) or CRAN⁠ (for R):

⁠Python

pip install h2o

⁠R

install.packages("h2o")

For the latest stable, nightly, Hadoop (or Spark / Sparkling Water) releases, or the stand-alone H2O jar, please visit: https://h2o.ai/download⁠

More info on downloading & installing H2O is available in the H2O User Guide⁠.

⁠2. Open Source Resources

Most people interact with three or four primary open source resources: GitHub (which you've already found), JIRA (for bug reports and issue tracking), Stack Overflow for H2O code/software-specific questions, and h2ostream (a Google Group / email discussion forum) for questions not suitable for Stack Overflow. There is also a Gitter H2O developer chat group, however for archival purposes & to maximize accessibility, we'd prefer that standard H2O Q&A be conducted on Stack Overflow.

⁠2.1 Issue Tracking and Feature Requests

You can browse and create new issues in our open source JIRA: http://jira.h2o.ai⁠

• You can browse and search for issues without logging in to JIRA:
  1. Click the Issues menu
  2. Click Search for issues
• To create an issue (either a bug or a feature request), please create yourself an account first:
  1. Click the Log In button on the top right of the screen
  2. Click Create an acccount near the bottom of the login box
  3. Once you have created an account and logged in, use the Create button on the menu to create an issue
  4. Create H2O-3 issues in the PUBDEV⁠ project. (Note: Sparkling Water questions should be filed under the SW⁠ project.)
• You can also vote for feature requests and/or other issues. Voting can help H2O prioritize the features that are included in each release.
  1. Go to the H2O JIRA page⁠.
  2. Click Log In to either log in or create an account if you do not already have one.
  3. Search for the feature that you want to prioritize, or create a new feature.
  4. Click on the Vote for this issue link. This is located on the right side of the issue under the People section.

⁠2.2 List of H2O Resources

• GitHub

  • https://github.com/h2oai/h2o-3⁠

• JIRA -- file bug reports / track issues here

  • The PUBDEV⁠ project contains issues for the current H2O-3 project)

• Stack Overflow -- ask all code/software questions here

  • http://stackoverflow.com/questions/tagged/h2o⁠

• Cross Validated (Stack Exchange) -- ask algorithm/theory questions here

  • https://stats.stackexchange.com/questions/tagged/h2o⁠

• h2ostream Google Group -- ask non-code related questions here

  • Web: https://groups.google.com/d/forum/h2ostream⁠
  • Mail to: [email protected]⁠

• Gitter H2O Developer Chat

  • https://gitter.im/h2oai/h2o-3⁠

• Documentation

  • H2O User Guide (main docs): http://docs.h2o.ai/h2o/latest-stable/h2o-docs/index.html⁠
  • All H2O documenation links: http://docs.h2o.ai⁠
  • Nightly build page (nightly docs linked in page): https://s3.amazonaws.com/h2o-release/h2o/master/latest.html⁠

• Download (pre-built packages)

  • http://h2o.ai/download⁠

• Jenkins (H2O build and test system)

  • http://test.h2o.ai⁠

• Website

  • http://h2o.ai⁠

• Twitter -- follow us for updates and H2O news!

  • https://twitter.com/h2oai⁠

• Awesome H2O -- share your H2O-powered creations with us

  • https://github.com/h2oai/awesome-h2o⁠

⁠3. Using H2O-3 Artifacts

Every nightly build publishes R, Python, Java, and Scala artifacts to a build-specific repository. In particular, you can find Java artifacts in the maven/repo directory.

Here is an example snippet of a gradle build file using h2o-3 as a dependency. Replace x, y, z, and nnnn with valid numbers.

// h2o-3 dependency information
def h2oBranch = 'master'
def h2oBuildNumber = 'nnnn'
def h2oProjectVersion = "x.y.z.${h2oBuildNumber}"

repositories {
  // h2o-3 dependencies
  maven {
    url "https://s3.amazonaws.com/h2o-release/h2o-3/${h2oBranch}/${h2oBuildNumber}/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}"
}

Refer to the latest H2O-3 bleeding edge nightly build page⁠ for information about installing nightly build artifacts.

Refer to the h2o-droplets GitHub repository⁠ for a working example of how to use Java artifacts with gradle.

⁠4. Building H2O-3

Getting started with H2O development requires JDK 1.7⁠, Node.js⁠, Gradle⁠, Python⁠ and R⁠. We use the Gradle wrapper (called gradlew) to ensure up-to-date local versions of Gradle and other dependencies are installed in your development directory.

⁠4.1. Before building

Installation of h2o requires properly set up Python environment and following packages:

grip
colorama
future
tabulate
requests
wheel

To install these packages you can use pip⁠ or conda⁠. If you have troubles installing these packages on Windows, please follow section Setup on Windows⁠ of this guide.

⁠4.2. Building from the command line (Quick Start)

To build H2O from the repository, perform the following steps.

⁠Recipe 1: Clone fresh, build, skip tests, and run H2O

# Build H2O
git clone https://github.com/h2oai/h2o-3.git
cd h2o-3
./gradlew build -x test

You may encounter problems: e.g. npm missing. Install it:
brew install npm

# Start H2O
java -jar build/h2o.jar

# Point browser to http://localhost:54321

⁠Recipe 2: Clone fresh, build, and run tests (requires a working install of R)

git clone https://github.com/h2oai/h2o-3.git
cd h2o-3
./gradlew syncSmalldata
./gradlew syncRPackages
./gradlew build

⁠Recipe 3: Pull, clean, build, and run tests

git pull
./gradlew syncSmalldata
./gradlew syncRPackages
./gradlew clean
./gradlew build

⁠Notes

• We recommend using ./gradlew clean after each git pull.

• Skip tests by adding -x test at the end the gradle build command line. Tests typically run for 7-10 minutes on a Macbook Pro laptop with 4 CPUs (8 hyperthreads) and 16 GB of RAM.

• Syncing smalldata is not required after each pull, but if tests fail due to missing data files, then try ./gradlew syncSmalldata as the first troubleshooting step. Syncing smalldata downloads data files from AWS S3 to the smalldata directory in your workspace. The sync is incremental. Do not check in these files. The smalldata directory is in .gitignore. If you do not run any tests, you do not need the smalldata directory.

• Running ./gradlew syncRPackages is supported on Windows, OS X, and Linux, and is strongly recommended but not required. ./gradlew syncRPackages ensures a complete and consistent environment with pre-approved versions of the packages required for tests and builds. The packages can be installed manually, but we recommend setting an ENV variable and using ./gradlew syncRPackages. To set the ENV variable, use the following format (where ${WORKSPACE} can be any path):

  mkdir -p ${WORKSPACE}/Rlibrary
  export R_LIBS_USER=${WORKSPACE}/Rlibrary
  

  Copy

⁠Recipe 4: Just building the docs

./gradlew clean && ./gradlew build -x test && (export DO_FAST=1; ./gradlew dist)
open target/docs-website/h2o-docs/index.html

⁠4.3. Setup on Windows

⁠Step 1: Download and install WinPython⁠.

From the command line, validate python is using the newly installed package by using which python (or sudo which python). Update the Environment variable⁠ with the WinPython path.

⁠Step 2: Install required Python packages:

pip install grip
pip install tabulate
pip install wheel

⁠Step 3: Install JDK

Install Java 1.7⁠ and add the appropriate directory C:\Program Files\Java\jdk1.7.0_65\bin with java.exe to PATH in Environment Variables. To make sure the command prompt is detecting the correct Java version, run:

javac -version

The CLASSPATH variable also needs to be set to the lib subfolder of the JDK:

CLASSPATH=/<path>/<to>/<jdk>/lib

⁠Step 4. Install Node.js

Install Node.js⁠ and add the installed directory C:\Program Files\nodejs, which must include node.exe and npm.cmd to PATH if not already prepended.

⁠Step 5. Install R, the required packages, and Rtools:

Install R⁠ and add the bin directory to your PATH if not already included.

Install the following R packages:

• RCurl⁠
• jsonlite⁠
• statmod⁠
• devtools⁠
• roxygen2⁠
• testthat⁠

To install these packages from within an R session:

pkgs <- c("RCurl", "jsonlite", "statmod", "devtools", "roxygen2", "testthat")
for (pkg in pkgs) {
  if (! (pkg %in% rownames(installed.packages()))) install.packages(pkg)
}

Note that libcurl⁠ is required for installation of the RCurl R package.

Finally, install Rtools⁠, which is a collection of command line tools to facilitate R development on Windows.

⁠Step 6. Install Cygwin⁠

NOTE: During installation of Cygwin, deselect the Python packages to avoid a conflict with the Python.org package.

⁠Step 6b. Validate Cygwin

If Cygwin is already installed, remove the Python packages or ensure that Native Python is before Cygwin in the PATH variable.

⁠Step 7. Update or validate the Windows PATH variable to include R, Java JDK, Cygwin.

⁠Step 8. Git Clone h2o-3⁠

If you don't already have a Git client, please install one. The default one can be found here http://git-scm.com/downloads⁠. Make sure that command prompt support is enabled before the installation.

Download and update h2o-3 source codes:

git clone https://github.com/h2oai/h2o-3

⁠Step 9. Run the top-level gradle build:

cd h2o-3
./gradlew.bat build

⁠4.4. Setup on OS X

If you don't have Homebrew⁠, we recommend installing it. It makes package management for OS X easy.

⁠Step 1. Install JDK

Install Java 1.7⁠. To make sure the command prompt is detecting the correct Java version, run:

javac -version

⁠Step 2. Install Node.js:

Using Homebrew:

brew install node

Otherwise, install from the NodeJS website⁠.

⁠Step 3. Install R and the required packages:

Install R⁠ and add the bin directory to your PATH if not already included.

Install the following R packages:

• RCurl⁠
• jsonlite⁠
• statmod⁠
• devtools⁠
• roxygen2⁠
• testthat⁠

To install these packages from within an R session:

pkgs <- c("RCurl", "jsonlite", "statmod", "devtools", "roxygen2", "testthat")
for (pkg in pkgs) {
  if (! (pkg %in% rownames(installed.packages()))) install.packages(pkg)
}

Note that libcurl⁠ is required for installation of the RCurl R package.

⁠Step 4. Git Clone h2o-3⁠

OS X should already have Git installed. To download and update h2o-3 source codes:

git clone https://github.com/h2oai/h2o-3

⁠Step 5. Run the top-level gradle build:

cd h2o-3
./gradlew build

⁠4.5. Setup on Ubuntu 14.04

⁠Step 1. Install Node.js

curl -sL https://deb.nodesource.com/setup_0.12 | sudo bash -
sudo apt-get install -y nodejs

⁠Step 2. Install JDK:

Install Java 1.7⁠. Installation instructions can be found here JDK installation⁠. To make sure the command prompt is detecting the correct Java version, run:

javac -version

⁠Step 3. Install R and the required packages:

Installation instructions can be found here R installation⁠. Click “Download R for Linux”. Click “ubuntu”. Follow the given instructions.

To install the required packages, follow the same instructions as for OS X above⁠.

⁠Step 4. Git Clone h2o-3⁠

If you don't already have a Git client:

sudo apt-get install git

Download and update h2o-3 source codes:

git clone https://github.com/h2oai/h2o-3

⁠Step 5. Run the top-level gradle build:

cd h2o-3
./gradlew build

⁠4.6. Setup on Ubuntu 13.10

⁠Step 1. Install Node.js

curl -sL https://deb.nodesource.com/setup_0.12 | sudo bash -
sudo apt-get install -y nodejs

⁠Steps 2-4. Follow steps 2-4 for Ubuntu 14.04 (above)

⁠4.7. Setting up your preferred IDE environment

For users of Intellij's IDEA, generate project files with:

./gradlew idea

For users of Eclipse, generate project files with:

./gradlew eclipse

⁠4.7 Setup on CentOS 7

cd /opt
sudo wget --no-cookies --no-check-certificate --header "Cookie: gpw_e24=http%3A%2F%2Fwww.oracle.com%2F; oraclelicense=accept-securebackup-cookie" "http://download.oracle.com/otn-pub/java/jdk/7u79-b15/jdk-7u79-linux-x64.tar.gz"

sudo tar xzf jdk-7u79-linux-x64.tar.gz
cd jdk1.7.0_79

sudo alternatives --install /usr/bin/java java /opt/jdk1.7.0_79/bin/java 2

sudo alternatives --install /usr/bin/jar jar /opt/jdk1.7.0_79/bin/jar 2
sudo alternatives --install /usr/bin/javac javac /opt/jdk1.7.0_79/bin/javac 2
sudo alternatives --set jar /opt/jdk1.7.0_79/bin/jar
sudo alternatives --set javac /opt/jdk1.7.0_79/bin/javac

cd /opt

sudo wget http://dl.fedoraproject.org/pub/epel/7/x86_64/e/epel-release-7-5.noarch.rpm
sudo rpm -ivh epel-release-7-5.noarch.rpm

sudo echo "multilib_policy=best" >> /etc/yum.conf
sudo yum -y update

sudo yum -y install R R-devel git python-pip openssl-devel libxml2-devel libcurl-devel gcc gcc-c++ make openssl-devel kernel-devel texlive texinfo texlive-latex-fonts libX11-devel mesa-libGL-devel mesa-libGL nodejs npm python-devel numpy scipy python-pandas

sudo pip install scikit-learn grip tabulate statsmodels wheel

mkdir ~/Rlibrary
export JAVA_HOME=/opt/jdk1.7.0_79
export JRE_HOME=/opt/jdk1.7.0_79/jre
export PATH=$PATH:/opt/jdk1.7.0_79/bin:/opt/jdk1.7.0_79/jre/bin
export R_LIBS_USER=~/Rlibrary

# install local R packages
R -e 'install.packages(c("RCurl","jsonlite","statmod","devtools","roxygen2","testthat"), dependencies=TRUE, repos="http://cran.rstudio.com/")'

cd
git clone https://github.com/h2oai/h2o-3.git
cd h2o-3

# Build H2O
./gradlew syncSmalldata
./gradlew syncRPackages
./gradlew build -x test

⁠5. Launching H2O after Building

To start the H2O cluster locally, execute the following on the command line:

java -jar build/h2o.jar

A list of available start-up JVM and H2O options (e.g. -Xmx, -nthreads, -ip), is available in the H2O User Guide⁠.

⁠6. Building H2O on Hadoop

Pre-built H2O-on-Hadoop zip files are available on the download page⁠. Each Hadoop distribution version has a separate zip file in h2o-3.

To build H2O with Hadoop support yourself, first install sphinx for python: pip install sphinx Then start the build by entering the following from the top-level h2o-3 directory:

(export BUILD_HADOOP=1; ./gradlew build -x test)
./gradlew dist

This will create a directory called 'target' and generate zip files there. Note that BUILD_HADOOP is the default behavior when the username is jenkins (refer to settings.gradle); otherwise you have to request it, as shown above.

⁠Adding support for a new version of Hadoop

In the h2o-hadoop directory, each Hadoop version has a build directory for the driver and an assembly directory for the fatjar.

You need to:

1. Add a new driver directory and assembly directory (each with a build.gradle file) in h2o-hadoop
2. Add these new projects to h2o-3/settings.gradle
3. Add the new Hadoop version to HADOOP_VERSIONS in make-dist.sh
4. Add the new Hadoop version to the list in h2o-dist/buildinfo.json

⁠Secure user impersonation

Hadoop supports secure user impersonation⁠ through its Java API. A kerberos-authenticated user can be allowed to proxy any username that meets specified criteria entered in the NameNode's core-site.xml file. This impersonation only applies to interactions with the Hadoop API or the APIs of Hadoop-related services that support it (this is not the same as switching to that user on the machine of origin).

Setting up secure user impersonation (for h2o):

1. Create or find an id to use as proxy which has limited-to-no access to HDFS or related services; the proxy user need only be used to impersonate a user
2. (Required if not using h2odriver) If you are not using the driver (e.g. you wrote your own code against h2o's API using Hadoop), make the necessary code changes to impersonate users (see org.apache.hadoop.security.UserGroupInformation⁠)
3. In either of Ambari/Cloudera Manager or directly on the NameNode's core-site.xml file, add 2/3 properties for the user we wish to use as a proxy (replace with the simple user name - not the fully-qualified principal name).
   • hadoop.proxyuser.<proxyusername>.hosts: the hosts the proxy user is allowed to perform impersonated actions on behalf of a valid user from
   • hadoop.proxyuser.<proxyusername>.groups: the groups an impersonated user must belong to for impersonation to work with that proxy user
   • hadoop.proxyuser.<proxyusername>.users: the users a proxy user is allowed to impersonate
   • Example: <property> <name>hadoop.proxyuser.myproxyuser.hosts</name> <value>host1,host2</value> </property> <property> <name>hadoop.proxyuser.myproxyuser.groups</name> <value>group1,group2</value> </property> <property> <name>hadoop.proxyuser.myproxyuser.users</name> <value>user1,user2</value> </property>
4. Restart core services such as HDFS & YARN for the changes to take effect

Impersonated HDFS actions can be viewed in the hdfs audit log ('auth:PROXY' should appear in the ugi= field in entries where this is applicable). YARN similarly should show 'auth:PROXY' somewhere in the Resource Manager UI.

To use secure impersonation with h2o's Hadoop driver:

Before this is attempted, see Risks with impersonation, below

When using the h2odriver (e.g. when running with hadoop jar ...), specify -principal <proxy user kerberos principal>, -keytab <proxy user keytab path>, and -run_as_user <hadoop username to impersonate>, in addition to any other arguments needed. If the configuration was successful, the proxy user will log in and impersonate the -run_as_user as long as that user is allowed by either the users or groups configuration property (configured above); this is enforced by HDFS & YARN, not h2o's code. The driver effectively sets its security context as the impersonated user so all supported Hadoop actions will be performed as that user (e.g. YARN, HDFS APIs support se