CentOS/RHEL 7 EE GPU Installation With Yum

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:

NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. 
Make sure that the latest NVIDIA driver is installed and running.

Firewall

To use Immerse, you must prepare your host machine to accept HTTP connections. Configure your firewall for external access:

sudo firewall-cmd --zone=public --add-port=6273/tcp --permanent
sudo firewall-cmd --reload

For more information, see https://fedoraproject.org/wiki/Firewalld?rd=FirewallD.

Installation

Update the repo file at \etc\yum.repos.d\CentOS-Sources.repo with the OmniSci repository specification:

[omnisci]
name='omnisci ee - cuda'
baseurl=https://releases.omnisci.com/ee/yum/stable/cuda
enabled=1
gpgcheck=1
repo_gpgcheck=0
gpgkey=https://releases.omnisci.com/GPG-KEY-mapd

Use yum to install OmniSci:

sudo yum install omnisci

Configuration

Follow these steps to prepare your OmniSci environment.

Initialization

Run the systemd installer. This script requires sudo access. You might be prompted for a password.

cd $OMNISCI_PATH/systemd
sudo ./install_omnisci_systemd.sh

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.

Activation

Start and use OmniSci Core and Immerse.

1. Start OmniSci Core

   cd $OMNISCI_PATH
   sudo systemctl start omnisci_server
   sudo systemctl start omnisci_web_server

2. Enable OmniSci Core to start when the system reboots.

   sudo systemctl enable omnisci_server
   sudo systemctl enable omnisci_web_server

Enter Your License Key

Validate your OmniSci instance with your license key.

1. 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.
2. Connect to Immerse using a web browser connected to your host machine on port 6273. For example, http://omnisci.mycompany.com:6273.
3. When prompted, paste your license key in the text box and click Apply.
4. Click Connect to start using OmniSci.

Checkpoint

To verify that everthing is working, load some sample data, perform an omnisql query, and generate a pointmap using Immerse.

1. OmniSci ships with two sample datasets of airline flight information collected in 2008. To install the sample data, run the following command.

   cd $OMNISCI_PATH
   sudo ./insert_sample_data

2. 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

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

   $OMNISCI_PATH/bin/omnisql
   password: ••••••••••••••••

4. 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,
   dest_city;
   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

5. Connect to Immerse using a web browser connected to your host machine on port 6273. For example, http://omnisci.mycompany.com:6273.
6. 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 or flights_2008_7M table as the data source, depending on which dataset you selected for ingest.
   6. Click X Axis +Add Measure.
   7. Choose depdelay.
   8. Click Y Axis +Add Measure.
   9. Choose arrdelay.
The resulting chart shows, unsurprisingly, that there is a correlation between departure delay and arrival delay.