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 OmniSci host only runs the daemons and services required to support OmniSci.
Your OmniSci host is connected to the Internet.
Prepare your Centos/RHEL 7 machine by updating your system, installing JDK and EPEL, creating the OmniSci user (named omnisci), installing kernel headers, installing CUDA drivers, and enabling a firewall.
Update and Reboot
Update the entire system and reboot to activate the latest kernel.
sudo yum update
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:
sudo yum install java-1.8.0-openjdk-headless
Install the Extra Packages for Enterprise Linux (EPEL) repository.
For CentOS, use Yum to install the epel-release package.
Create a group called omnisci and a user named
omnisci, who will be the owner of the OmniSci database.
You can create the group, user, and home directory using the
useradd command with the -U and -m
sudo useradd -U -m omnisci
Install CUDA Drivers
CUDA is a parallel computing platform and application programming interface (API) model. It uses a CUDA-enabled graphics processing unit (GPU) for general purpose processing. The CUDA platform provides direct access to the GPU virtual instruction set and parallel computation elements. For more information on CUDA unrelated to installing OmniSci, see http://www.nvidia.com/object/cuda_home_new.html.
Select the target platform by selecting the operating system (Linux), architecture (based on your environment), distribution (CentOS or RHEL), version (7), and installer type (OmniSci recommends rpm (network)).
In Download Installer..., right-click the Download button and copy the link location of the Base Installer. Do not use the installation instructions on the CUDA site:
Use one of the following methods to download the installer from the command line, using the download link you copied (in this example, https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.0.130-1.x86_64.rpm):
Reboot your system to ensure that all changes are active.
You might see a warning similar to the following: warning: cuda-repo-rhel7-10.0.130-1.x86_64.rpm: Header V3 RSA/SHA512 Signature, key ID 7fa2af80: NOKEY
Ignore it for now; you can verify CUDA driver installation at the Checkpoint.
Run nvidia-smi to verify that your drivers are installed correctly and recognize the GPUs in your environment. Depending on your environment, you should see something like this to verify that your NVIDIA GPUs and drivers are present:
If you see an error like the following, the NVIDIA drivers are probably installed incorrectly:
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver.
Make sure that the latest NVIDIA driver is installed and running.
You can use wget to download the OmniSci TAR file. Storing it
in the ~/Downloads directory works with the instructions below. For example:
sudo /usr/local/bin/wget https://releases.omnisci.com/ee/tar/omnisci-ee-latest-Linux-x86_64-render.tar.gz
You install the OmniSci application itself by expanding the TAR file.
Create an installs directory in your home folder:
sudo mkdir installs
Expand the OmniSci archive file in the installs directory with
the following command:
sudo tar -xvf omnisci-ee-latest-Linux-x86_64-render.tar.gz
Go to the opt folder and create a symbolic link to the
directory you just created:
ln -s ~/installs/omnisci-ee-latest-Linux-x86_64-render omnisci
Follow these steps to prepare your OmniSci environment.
Set Environment Variables
For convenience, you can update .bashrc with the required environment variables.
Open a terminal window.
Enter cd ~/ to go to your home directory.
Open .bashrc in a text editor. For example, sudo gedit .bashrc.
Edit the .bashrc file. Add the following export commands under “User specific aliases and functions.”
# User specific aliases and functions
Save the .bashrc file.
Open a new terminal window to use your changes.
The $OMNISCI_STORAGE directory must be dedicated to OmniSci: do not set it to a directory shared by other packages.
Run the systemd installer. This script requires sudo access. You
might be prompted for a password.
You are prompted for two paths during install: OMNISCI_PATH and OMNISCI_STORAGE. OMNISCI_PATH must be the same as the location of the symbolic link you created in step 5 of the installation process and the environment variable you just created. In a standard installation, that path is /opt/omnisci. OMNISCI_STORAGE defaults to /var/lib/omnisci.
The script creates a data
directory in $OMNISCI_STORAGE with the directories mapd_catalogs,
mapd_data, and mapd_export. The mapd_import and mapd_log
directories are created when you insert data the first time. If you are an OmniSci administrator, the mapd_log
directory is of particular interest.
Validate your OmniSci instance with your license key.
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 Immerse using a web browser connected to your host machine on
port 6273. For example, http://omnisci.mycompany.com:6273.
When prompted, paste your license key in the text box and click Apply.
Click Connect to start using OmniSci.
To verify that everything is working correctly, load some sample data, perform an omnisql query, and generate a pointmap using Immerse.
OmniSci ships with two sample datasets of airline flight information collected in 2008. To install the sample data, run the following command.
When prompted, choose whether to insert dataset 1 (7 million rows) or dataset 2 (10 thousand rows).
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 OmniSciDB by entering the following command in a terminal on the host machine (default password is HyperInteractive):
Enter a SQL query such as the following, based on dataset 2 above:
omnisql> 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,
Connect to Immerse using a web browser connected to your host machine on port 6273. For example, http://omnisci.mycompany.com:6273.
Create a new dashboard and a Scatter Plot to verify that backend rendering is working.
Click New Dashboard.
Click Add Chart.
Click Add Data Source.
Choose the flights_2008_10k or flights_2008_7M table as the data source, depending on the dataset you selected for ingest.
Click X Axis +Add Measure.
Click Y Axis +Add Measure.
The resulting chart shows, unsurprisingly, that there is a correlation between departure delay and arrival delay.