This is an end-to-end recipe for installing HEAVY.AI on a CentOS/RHEL 7 machine using CPU and GPU devices.
The order of these instructions is significant. To avoid problems, install each component in the order presented.
These instructions assume the following:
You are installing on a “clean” CentOS/RHEL 7 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.
Prepare your Centos/RHEL machine by updating your system and optionally enabling or configuring a firewall.
Update the entire system and reboot the system if needed.
Install the utilities needed to create HEAVY.AI repositories and download archives
Follow these instructions to install a headless JDK and configure an environment variable with a path to the library. The “headless” Java Development Kit does not provide support for keyboard, mouse, or display systems. It has fewer dependencies and is best suited for a server host. For more information, see https://openjdk.java.net.
Open a terminal on the host machine.
Install the headless JDK using the following command:
Create a group called heavyai and a user named heavyai, who will own HEAVY.AI software and data on the file system.
You can create the group, user, and home directory using the useradd command with the --user-group and --create-home switches:
Set a password for the user:
Log in with the newly created user:
Install HEAVY.AI using yum or a tarball.
The installation using the yum package manager is recommended to those who want a more automated install and upgrade procedure.
If your system includes NVIDIA GPUs, but the drivers are not installed, install them now.
See Install NVIDIA Drivers and Vulkan on CentOS/RHEL for details.
Create a yum repository depending on the edition (Enterprise, Free, or Open Source) and execution device (GPU or CPU) you are going to use.
Add the GPG-key to the newly added repository.
Use yum to install the latest version of HEAVY.AI.
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:
First create the installation directory.
Download the archive and install the latest version of the software. A different archive is downloaded depending on the edition (Enterprise, Free, or Open Source) and the device used for runtime.
Follow these steps to prepare your HEAVY.AI environment.
For your convenience, you can update .bashrc with these environment variables
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. Installing them is strongly recommended.
Run the systemd installer to initialize the HEAVY.AI services and the database storage.
Accept the default values provided or make changes as needed.
The script creates a data directory in $HEAVYAI_BASE/storage (typically /var/lib/heavyai) with the directories catalogs, data, export and log. The directory import is created when you insert data the first time. If you are a HeavyDB administrator, the log directory is of particular interest.
Start and use HeavyDB and Heavy Immerse. ¹
Note that Heavy Immerse is not available in the OS SEdition, 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.
If a firewall is not already installed and you want to harden your system, install and start firewalld.
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:
Most cloud providers use a different mechanism for firewall configuration. The commands above might not run in cloud deployments.
For more information, see https://fedoraproject.org/wiki/Firewalld?rd=FirewallD.
If you are on Enterprise or Free Edition, you need to validate your HEAVY.AI instance with your license key. You can skip this section if you are using Open Source Edition. ²
Open a terminal window.
Enter cd ~/ to go to your home directory.
Open .bashrc in a text editor. For example, vi .bashrc.
Edit the .bashrc file. Add the following export commands under “User specific aliases and functions.”
Save the .bashrc file. For example, in vi enter[esc]:x!
Open a new terminal window to use your changes.
Copy your license key from the registration email message. If you have not received your license key, contact your Sales Representative or register for your 30-day trial here.
Connect to Heavy Immerse using a web browser connected to your host machine on port 6273. For example, http://heavyai.mycompany.com:6273.
When prompted, paste your license key in the text box and click Apply.
Log into Heavy Immerse by entering the default username (admin) and password (HyperInteractive), and then click Connect.
The $HEAVYAI_BASE directory must be dedicated to HEAVYAI; do not set it to a directory shared by other packages.
To verify that everything is working, load some sample data, perform a heavysql query, and generate a Pointmap using Heavy Immerse. ¹
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.
Connect to HeavyDB by entering the following command in a terminal on the host machine (default password is HyperInteractive):
Enter a SQL query such as the following:
The results should be similar to the results below.
After installing Enterprise or Free Edition, check if Heavy Immerse is running as intended.
Connect to Heavy Immerse using a web browser connected to your host machine on port 6273. For example, http://heavyai.mycompany.com:6273.
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.
Click New Dashboard.
Click Add Chart.
Click SCATTER.
Click Add Data Source.
Choose the flights_2008_10k table as the data source.
Click X Axis +Add Measure.
Choose depdelay.
Click Y Axis +Add Measure.
Choose arrdelay.
Click Size +Add Measure.
Choose airtime.
Click Color +Add Measure.
Choose dest_state.
The resulting chart shows, unsurprisingly, that there is a correlation between departure delay and arrival delay.
Create a new dashboard and a Table chart to verify that Heavy Immerse is working.
Click New Dashboard.
Click Add Chart.
Click Bubble.
Click Select Data Source.
Choose the flights_2008_10k table as the data sour
Click Add Dimension.
Choose carrier_name.
Click Add Measure.
Choose depdelay.
Click Add Measure.
Choose arrdelay.
Click Add Measure.
Choose #Records.
The resulting chart shows, unsurprisingly, that also the average departure delay is correlated to the average of arrival delay, while there is quite a difference between Carriers.
