Ubuntu EE GPU Installation With Tarball

Assumptions

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.

Preparation

Prepare your Ubuntu machine by updating your system, creating the OmniSci user, enabling a firewall, and installing CUDA.

sudo apt update
sudo apt upgrade

sudo apt install default-jre-headless

sudo reboot

sudo useradd -U mapd

sudo ufw disable
sudo ufw allow 9092/tcp
sudo ufw allow ssh
sudo ufw enable

Installation

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

1. Create your $MAPD_PATH directory. OmniSci recommends /opt/mapd.

2. Expand the OmniSci archive file in the $MAPD_PATH directory with the following command.

   tar -xvf <file_name>.tar.gz
   

Configuration

These are the steps to prepare your OmniSci environment.

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
   sudo ./install_mapd_systemd.sh

Activation

Start and use OmniSci Core and Immerse.

1. Start OmniSci Core

   cd $MAPD_PATH
   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.