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GH-16182: Updating user guide page Welcome to reflect makersaurus guidelines #16183

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1f6307f
ht/welcome massive restructure
hannah-tillman Apr 26, 2024
3702bca
ht/added getting started
hannah-tillman Apr 26, 2024
fa5ce34
ht/added flow users
hannah-tillman Apr 26, 2024
fb572ec
ht/added python users
hannah-tillman Apr 26, 2024
263d351
ht/added r users
hannah-tillman Apr 26, 2024
da953e5
ht/added sparkling users
hannah-tillman Apr 26, 2024
78c1761
ht/added api users
hannah-tillman Apr 26, 2024
82271ec
ht/added java users
hannah-tillman Apr 26, 2024
9a30a70
ht/added hadoop users
hannah-tillman Apr 26, 2024
cd74e4a
ht/added docker users
hannah-tillman Apr 26, 2024
b45b083
ht/added kubernetes users
hannah-tillman Apr 26, 2024
dc52ce3
ht/added experienced users
hannah-tillman Apr 26, 2024
3f442b9
ht/welcome & docker page fixes
hannah-tillman Apr 26, 2024
3bccf93
ht/hadoop page fixes
hannah-tillman Apr 26, 2024
6a74711
ht/getting started page fixes
hannah-tillman Apr 26, 2024
7d73d91
ht/link fixes
hannah-tillman Apr 26, 2024
1ab5c90
ht/link fixes
hannah-tillman Apr 26, 2024
d456f7d
ht/link & spacing fixes
hannah-tillman Apr 26, 2024
cdd6bb3
ht/minor fix
hannah-tillman Apr 26, 2024
aa0b7fa
ht/direct link for several sections
hannah-tillman May 2, 2024
66f6f4b
ht/h2o > h2o-3 + others
hannah-tillman Jun 5, 2024
3cad433
ht/flow algo section w/ links to algo pages
hannah-tillman Jun 5, 2024
93bb209
ht/added available algos + linux fix
hannah-tillman Jun 5, 2024
34b455d
Update h2o-docs/src/product/getting-started/docker-users.rst
hannah-tillman Jun 27, 2024
323e6f5
Update h2o-docs/src/product/getting-started/docker-users.rst
hannah-tillman Jun 27, 2024
cc4cfa0
ht/requested updates; updated flow list to reflect app
hannah-tillman Jun 27, 2024
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ht/added infogram to welcome page
hannah-tillman Jun 27, 2024
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ht/rerun checks
hannah-tillman Aug 20, 2024
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20 changes: 20 additions & 0 deletions h2o-docs/src/product/getting-started/api-users.rst
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API users
=========

Our REST APIs are generated immediately out of the code, allowing you to implement machine learning in many ways. For example, REST APIs can be used to call a model created by sensor data and to set up auto-alerts if the sensor data falls below a specified threshold.

REST API references
-------------------

See the definitive `guide to H2O-3's REST API <https://docs.h2o.ai/h2o/latest-stable/h2o-docs/rest-api-reference.html>`__.

Schemas
~~~~~~~

See the definitive `guide to H2O-3's REST API schemas <https://docs.h2o.ai/h2o/latest-stable/h2o-docs/rest-api-reference.html#schema-reference>`__.


REST API example
~~~~~~~~~~~~~~~~

See an `in-depth explanation of how H2O-3 REST API commands are used <https://github.com/h2oai/h2o-3/blob/master/h2o-docs/src/api/REST/h2o_3_rest_api_overview.md>`__. This explanation includes versioning, experimental APIs, verbs, status codes, formats, schemas, payloads, metadata, and examples.
161 changes: 161 additions & 0 deletions h2o-docs/src/product/getting-started/docker-users.rst
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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:

- `Mac installation <https://docs.docker.com/installation/mac/#installation>`__
- `Ubuntu installation <https://docs.docker.com/installation/ubuntulinux/>`__
- `Other OS installations <https://docs.docker.com/installation/>`__

.. 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:

.. code-block:: bash

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

2. Download or create a Dockerfile, which is a build recipe that builds the container. Download and use our `Dockerfile template <https://github.com/h2oai/h2o-3/blob/master/Dockerfile>`__:

.. code-block:: bash

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):

.. code-block:: bash

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).

.. code-block:: bash

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``.

.. code-block:: bash

cd /opt
java -Xmx1g -jar h2o.jar

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

.. tabs::
.. tab:: On Linux

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``.

.. code-block:: bash

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

.. tab:: On MacOS

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``.

.. code-block:: bash

$ 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:

.. tabs::
.. code-tab:: python

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

.. code-tab:: r R

# Initialize H2O
library(h2o)
dockerH2O <- h2o.init(ip = "192.168.59.103", port = 54321)
80 changes: 80 additions & 0 deletions h2o-docs/src/product/getting-started/experienced-users.rst
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Experienced users
=================

If you've used previous versions of H2O-3, the following links will help guide you through the process of upgrading H2O-3.

Changes
-------

Change log
~~~~~~~~~~

`This page houses the most recent changes in the latest build of H2O-3 <https://github.com/h2oai/h2o-3/blob/master/Changes.md>`__. It lists new features, improvements, security updates, documentation improvements, and bug fixes for each release.

API-related changes
~~~~~~~~~~~~~~~~~~~

The `API-related changes <https://docs.h2o.ai/h2o/latest-stable/h2o-docs/api-changes.html>`__ section describes changes made to H2O-3 that can affect backward compatibility.

Developers
----------

If you're looking to use H2O-3 to help you develop your own apps, the following links will provide helpful references.

Gradle
~~~~~~

H2O-3's build is completely managed by Gradle. Any IDEA with Gradle support is sufficient for H2O-3 development. The latest versions of IntelliJ IDEA are thoroughly tested and proven to work well.

Open the folder with H2O-3 in IntelliJ IDEA and it will automatically recognize that Gradle is requried and will import the project. The Gradle wrapper present in the repository itself may be used manually/directly to build and test if required.

For JUnit tests to pass, you may need multiple H2O-3 nodes. Create a "Run/Debug" configuration:

::

Type: Application
Main class: H2OApp
Use class path of module: h2o-app

After starting multiple "worker" node processes in addition to the JUnit test process, they will cloud up and run the multi-node JUnit tests.

Maven install
~~~~~~~~~~~~~

You can view instructions for using H2O-3 with Maven on the `Downloads page <https://h2o.ai/resources/download/>`__.

1. Select H2O Open Source Platform or scroll down to H2O.
2. Select the version of H2O-3 you want to install (latest stable or nightly build).
3. Click the Use from Maven tab.

`This page provides information on how to build a version of H2O-3 that generates the correct IDE files <https://github.com/h2oai/h2o-3/blob/master/build.gradle>`__ for your Maven installation.

Developer resources
~~~~~~~~~~~~~~~~~~~

Documentation
'''''''''''''

See the detailed `instructions on how to build and launch H2O-3 <https://github.com/h2oai/h2o-3#4-building-h2o-3>`__, including how to clone the repository, how to pull from the repository, and how to install required dependencies.

Droplet project templates
^^^^^^^^^^^^^^^^^^^^^^^^^

`This page provides template information <https://github.com/h2oai/h2o-droplets>`__ for projects created in Java, Scala, or Sparkling Water.

Blogs
'''''

Learn more about performance characteristics when implementing new algorithms in this `KV Store guide blog <https://www.h2o.ai/blog/kv-store-memory-analytics-part-2-2/>`__.

This `blog post by Cliff <https://www.h2o.ai/blog/hacking-algorithms-in-h2o-with-cliff/>`__ walks you through building a new algorithm, using K-Means, Quantiles, and Grep as examples.

Join the H2O community
----------------------

`Join our community support and outreach <https://h2o.ai/community/>`__ by accessing self-paced courses, scoping out meetups, and interacting with other users and our team.

Contributing code
~~~~~~~~~~~~~~~~~

If you're interested in contributing code to H2O-3, we appreciate your assistance! See `how to contribute to H2O-3 <https://github.com/h2oai/h2o-3/blob/master/CONTRIBUTING.md>`__. This document describes how to access our list of issues, or suggested tasks for contributors, and how to contact us.
6 changes: 6 additions & 0 deletions h2o-docs/src/product/getting-started/flow-users.rst
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Flow users
==========

H2O Flow is a notebook-style open source UI for H2O-3. It's a web-based interactive environment that lets you combine code execution, text, mathematics, plots, and rich media in a single document (similar to iPython Notebooks).

See more about `H2O Flow <../flow.html>`__.
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