Ubuntu Enterprise Edition GPU with Tarball
Last updated
Last updated
This is an end-to-end recipe for installing OmniSci Enterprise Edition on an Ubuntu machine running with NVIDIA Kepler or Pascal series GPU cards. This install has all of the functionality of OmniSci.
Here is a quick video overview of the installation steps.
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” Ubuntu 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 Ubuntu machine by updating your system, creating the OmniSci user (named omnisci), installing kernel headers, installing CUDA drivers, and enabling the firewall.
Update the entire system:
Install a “headless” Java Runtime Environment:
Verify that the apt-transport-https utility is installed:
Reboot to activate the latest kernel:
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 switches.
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 https://developer.nvidia.com/cuda-zone.
Install kernel headers with the following command:
Select the target platform by selecting the operating system (Linux), architecture (based on your environment), distribution (Ubuntu), version (based on your environment), and installer type (OmniSci recommends deb (network)).
Install the CUDA package per the instructions on the NVIDIA web site.
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:
Review the Install CUDA Drivers section and correct any errors.
To use Immerse, you must prepare your host machine to accept HTTP connections. You can configure your firewall for external access.
For more information, see https://help.ubuntu.com/lts/serverguide/firewall.html.
Most cloud providers provide a different mechanism for handling firewall configuration. The commands above might not run in cloud deployments.
These instructions follow conventions of the OmniSci Engineering team. By creating an omnisci-installs directory and using a symbolic link that points to the current version, you can conveniently roll back to a previous version in the unlikely event that you would want to do so.
Use the following command to create the /opt/omnisci-installs directory.
You can download the OmniSci archive file using curl, or wget.
To download the OmniSci archive file with curl, use the following command.
To download the OmniScia archive file with wget, use the following command.
You install the OmniSci application itself by expanding the TAR file.
Go to the /opt/omnisci-installs directory.
Expand the OmniSci archive file with the following command:
The expanded directory name is long and complex, with information about the version and build date. For example, the OmniSci 4.8.1 directory name is the following:
Go to the /opt directory and create a symlink to omnisci, using the name of the expanded directory for the current release. For example, for OmniSci 4.8.1, you use the following commands:
Follow these steps to prepare your OmniSci environment.
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.”
Save the .bashrc file. For example, in vi, [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.
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. 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.
Start and use OmniSciDB and Immerse.
Start OmniSciDB
Enable OmniSciDB to start when the system reboots.
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.
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).
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:
The results should be similar to the results below.
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 SCATTER.
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.
Choose depdelay.
Click Y Axis +Add Measure.
Choose arrdelay.
The resulting chart shows, unsurprisingly, that there is a correlation between departure delay and arrival delay.
