HEAVY.AI Installation on Ubuntu

This is an end-to-end recipe for installing HEAVY.AI on a Ubuntu 20.04 machine using CPU and GPU devices.

The order of these instructions is significant. To avoid problems, install each component in the order presented.

Assumptions

These instructions assume the following:

  • You are installing on a “clean” Ubuntu 20.04 host machine with only the operating system installed.

  • Your HEAVY.AI host only runs the daemons and services required to support HEAVY.AI.

  • Your HEAVY.AI host is connected to the Internet.

Preparation

Prepare your Ubuntu machine by updating your system, creating the HEAVY.AI user (named heavyai), installing kernel headers, installing CUDA drivers, and optionally enabling the firewall.

Update and Reboot

  1. Update the entire system:

sudo apt update
sudo apt upgrade

2. Install the utilities needed to create Heavy.ai repositories and download archives:

sudo apt install curl
sudo apt install libncurses5

3. Install the headless JDK and the utility apt-transport-https:

sudo apt install default-jre-headless apt-transport-https

4. Reboot to activate the latest kernel:

sudo reboot

Create the HEAVY.AI User

Create a group called heavyai and a user named heavyai, who will be the owner of the HEAVY.AI software and data on the filesystem.

  1. Create the group, user, and home directory using the useradd command with the --user-group and --create-home switches.

sudo useradd --user-group --create-home --group sudo heavyai

2. Set a password for the user:

sudo passwd heavyai

3. Log in with the newly created user:

sudo su - heavyai

Installation

Install the HEAVY.AI using APT and a tarball.

The installation using the APT package manager is recommended to those who want a more automated install and upgrade procedure.

Install Nvidia Drivers ᴳᴾᵁ ᴼᴾᵀᴵᴼᴺ

If your system uses NVIDIA GPUs, but the drivers not installed, install them now. See Install NVIDIA Drivers and Vulkan on Ubuntu for details.

Installing with APT

Download and add a GPG key to APT.

curl https://releases.heavy.ai/GPG-KEY-heavyai | sudo apt-key add -

Add a source apt depending on the edition (Enterprise, Free, or Open Source) and execution device (GPU or CPU) you are going to use.

echo "deb https://releases.heavy.ai/ee/apt/ stable cuda" \
| sudo tee /etc/apt/sources.list.d/heavyai.list

Use apt to install the latest version of HEAVY.AI.

sudo apt update
sudo apt install heavyai

If you need to install a specific version of HEAVY.AI, because you are upgrading from Omnisci or for different reasons, you must run the following command:

hai_version="6.0.0"
sudo apt install heavyai=$(apt-cache madison heavyai | grep $hai_version | cut -f 2 -d '|' | xargs)

Installing with a Tarball

First create the installation directory.

sudo mkdir /opt/heavyai && chown $USER /opt/heavyai

Download the archive and install the software. A different archive is downloaded depending on the Edition (Enterprise, Free, or Open Source) and the device used for runtime (GPU or CPU).

curl \
https://releases.heavy.ai/ee/tar/heavyai-ee-latest-Linux-x86_64-render.tar.gz \
| sudo tar zxf - --strip-components=1 -C /opt/heavyai

Configuration

Follow these steps to prepare your HEAVY.AI environment.

Set Environment Variables

For convenience, you can update .bashrc with these environment variables

echo "# HEAVY.AI variable and paths
export HEAVYAI_PATH=/opt/heavyai
export HEAVYAI_BASE=/var/lib/heavyai
export HEAVYAI_LOG=$HEAVYAI_BASE/storage/log
export PATH=$HEAVYAI_PATH/bin:$PATH" \
>> ~/.bashrc
source ~/.bashrc

Although this step is optional, you will find references to the HEAVYAI_BASE and HEAVYAI_PATH variables. These variables contain respectively the paths where configuration, license, and data files are stored and where the software is installed. Setting them is strongly recommended.

Initialization

Run the systemd installer to create heavyai services, a minimal config file, and initialize the data storage.

cd $HEAVYAI_PATH/systemd
./install_heavy_systemd.sh

Accept the default values provided or make changes as needed.

The script creates a data directory in $HEAVYAI_BASE/storage (default /var/lib/heavyai/storage) with the directories catalogs, data, export and log.The import directory is created when you insert data the first time. If you are HEAVY.AI administrator, the log directory is of particular interest.

Activation

Start and use HeavyDB and Heavy Immerse. ¹

Heavy Immerse is not available in the OSS Edition, so if running the OSS Edition the systemctl command using the heavy_web_server has no effect.

Enable the automatic startup of the service at reboot and start the HEAVY.AI services.

sudo systemctl enable heavydb --now
sudo systemctl enable heavy_web_server --now

Configure Firewall ᴼᴾᵀᴵᴼᴺᴬᴸ

If a firewall is not already installed and you want to harden your system, install theufw.

sudo apt install ufw
sudo ufw allow ssh

To use Heavy Immerse or other third-party tools, you must prepare your host machine to accept incoming HTTP(S) connections. Configure your firewall for external access.

sudo ufw disable
sudo ufw allow 6273:6278/tcp
sudo ufw enable

Most cloud providers use a different mechanism for firewall configuration. The commands above might not run in cloud deployments.

For more information, see https://help.ubuntu.com/lts/serverguide/firewall.html.

Licensing HEAVY.AI ᵉᵉ⁻ᶠʳᵉᵉ ᵒⁿˡʸ

If you are using Enterprise or Free Edition, you need to validate your HEAVY.AI instance with your license key.

Skip this section if you are on Open Source Edition ²

  1. Copy your license key of Enterprise or Free Edition from the registration email message. If you do not have a license and you want to evaluate HEAVI.AI in an unlimited

    enterprise environment, contact your Sales Representative or register for your 30-day trial of Enterprise Edition here. If you need a Free License you can get one here.

  2. Connect to Heavy Immerse using a web browser connected to your host machine on port 6273. For example, http://heavyai.mycompany.com:6273.

  3. When prompted, paste your license key in the text box and click Apply.

  4. Log into Heavy Immerse by entering the default username (admin) and password (HyperInteractive), and then click Connect.

    .

Final Checks

To verify that everything is working, load some sample data, perform a heavysql query, and generate a Pointmap using Heavy Immerse ¹

Load Sample Data and Run a Simple Query

HEAVY.AI ships with two sample datasets of airline flight information collected in 2008, and a census of New York City trees. To install sample data, run the following command.

cd $HEAVYAI_PATH
sudo ./insert_sample_data --data /var/lib/heavyai/storage
#     Enter dataset number to download, or 'q' to quit:
Dataset           Rows    Table Name          File Name
1)    Flights (2008)    7M      flights_2008_7M     flights_2008_7M.tar.gz
2)    Flights (2008)    10k     flights_2008_10k    flights_2008_10k.tar.gz
3)    NYC Tree Census (2015)    683k    nyc_trees_2015_683k    nyc_trees_2015_683k.tar.gz

Connect to HeavyDB by entering the following command in a terminal on the host machine (default password is HyperInteractive):

$HEAVYAI_PATH/bin/heavysql
password: ••••••••••••••••

Enter a SQL query such as the following

SELECT origin_city AS "Origin", 
dest_city AS "Destination", 
AVG(airtime) AS "Average Airtime" 
FROM flights_2008_10k WHERE distance < 175 
GROUP BY origin_city, dest_city;

The results should be similar to the results below.

Origin|Destination|Average Airtime
Austin|Houston|33.055556
Norfolk|Baltimore|36.071429
Ft. Myers|Orlando|28.666667
Orlando|Ft. Myers|32.583333
Houston|Austin|29.611111
Baltimore|Norfolk|31.714286

Create a Dashboard Using Heavy Immerse ᵉᵉ⁻ᶠʳᵉᵉ ᵒⁿˡʸ ¹

After installing Enterprise or Free Edition, check if Heavy Immerse is running as intended.

  1. Connect to Heavy Immerse using a web browser connected to your host machine on port 6273. For example, http://heavyai.mycompany.com:6273.

  2. Log into Heavy Immerse by entering the default username (admin) and password (HyperInteractive), and then click Connect.

Create a new dashboard and a Scatter Plot to verify that backend rendering is working.

  1. Click New Dashboard.

  2. Click Add Chart.

  3. Click SCATTER.

  4. Click Add Data Source.

  5. Choose the flights_2008_10k table as the data source.

  6. Click X Axis +Add Measure.

  7. Choose depdelay.

  8. Click Y Axis +Add Measure.

  9. Choose arrdelay.

  10. Click Size +Add Measure.

  11. Choose airtime.

  12. Click Color +Add Measure.

  13. Choose dest_state.

The resulting chart shows, unsurprisingly, that there is a correlation between departure delay and arrival delay.

¹ In the OS Edition, Heavy Immerse is unavailable.

² The OS Edition does not require a license key.

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