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)).
If installing on RHEL, you need to obtain and install the
vulkan-filesystem package manually. Perform these additional steps:
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.
Most cloud providers use a different mechanism for firewall configuration. The commands above might not run in cloud deployments.
Create a repo file at /etc/yum.repos.d/omnisci.repo with
the OmniSci repository specification:
name='omnisci ee - cuda'
Use yum to install OmniSci:
sudo yum install 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, vi .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. For example, in vi enter[esc]:x!
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.
Accept the values provided (based on your
environment variables) or make changes as needed. The script creates a data
directory in $OMNISCI_STORAGE with the directories mapd_catalogs,
mapd_data, and mapd_export. 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 everthing is working, 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, and a census of New York City trees. To install the sample
data, run the following command.
When prompted, choose dataset 2.
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 table as the data source.
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.