Checkpoint

1. Go to /usr/lib64/ and verify that the file libcuda.so is in that location.
2. 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:

   

3. 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

   Review the Install CUDA Drivers section and correct any errors.

Firewall

To use Immerse, you must prepare your host machine to accept HTTP connections. You can configure your firewall for external access.

sudo firewall-cmd --zone=public --add-port=9092/tcp --permanent
sudo firewall-cmd --reload

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

Installation

You install the OmniSci application itself by expanding a TAR file.

1. Download the desired version of OmniSci from the URL provided you by your Account Executive.
2. Create your $MAPD_PATH directory. OmniSci recommends /opt/mapd.
3. Expand the OmniSci archive file in the $MAPD_PATH directory with the following command:

   tar -xvf <file_name>.tar.gz

Create the mapd User

Use the following command to create the mapd user. The -U switch also creates the mapd group.

sudo useradd -U mapd

Set Environment Variables

For convenience, you can update .bashrc with the required environment variables.

1. Open a terminal window.
2. Enter cd ~/ to go to your home directory.
3. Open .bashrc in a text editor. For example, sudo gedit .bashrc.
4. Edit the .bashrc file. Add the following export commands under “User specific aliases and functions.”

   # User specific aliases and functions
   export MAPD_USER=mapd
   export MAPD_GROUP=mapd
   export MAPD_STORAGE=/var/lib/mapd
   export MAPD_PATH=/opt/mapd
   export MAPD_LOG=/var/lib/mapd/data/mapd_log

5. Save the .bashrc file.
6. Open a new terminal window to use your changes.

The $MAPD_STORAGE directory must be dedicated to OmniSci: do not set it to a directory shared by other packages.

OmniSci Configuration File (mapd.conf)

You can also create a configuration file with optional settings. See Configuration.

Initialization

This step initializes the database and prepares systemd commands for OmniSci.

1. Run the systemd installer. This script requires sudo access. You might be prompted for a password. Accept the values provided (based on your environment variables) or make changes as needed. The script creates a data directory in $MAPD_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. The mapd_log directory is the one of most interest to a OmniSci administrator.

   cd $MAPD_PATH/systemd
   ./install_mapd_systemd.sh
   

Activation

Start and use OmniSci Core and Immerse.

1. Start OmniSci Core

   sudo systemctl start mapd_server
   sudo systemctl start mapd_web_server
   

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

   sudo systemctl enable mapd_server
   sudo systemctl enable mapd_web_server
   

Checkpoint

To verify that all systems are go, load some sample data, perform a mapdql 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.

cd $MAPD_PATH
./insert_sample_data

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

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

$MAPD_PATH/bin/mapdql
password: ••••••••••••••••

Enter a SQL query such as the following:

mapdql> 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

Connect to Immerse using a web browser connected to your host machine on port 9092. For example, http://omnisci.mycompany.com:9092.

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 table as the data source.
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.