Ubuntu CE CPU Installation With Tarball

Note MapD has been rebranded to OmniSci.

This is an end-to-end recipe for installing OmniSci Community Edition on an Ubuntu machine running without GPUs only. This install has all of the functionality of OmniSci, except for backend rendering (Pointmap, Scatterplot, and other charts might not be available.)

Here is a quick video overview of the installation process.

The installation phases are:
Important The order of these instructions is significant. To avoid problems, install each component in the order presented.

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, and enabling a firewall.

Update and Reboot

  1. Update the entire system: 
    sudo apt update
sudo apt upgrade
  2. Install a “headless” Java Runtime Environment: 
    sudo apt install default-jre-headless
  3. Verify that the apt-transport-https utility is installed: 
    sudo apt install apt-transport-https
  4. Reboot to activate the latest kernel: 
    sudo reboot

Create the OmniSci User

Create a group called mapd and a user named mapd, who will be the owner of the OmniSci database. You can create both the group and user with the useradd command and the -U switch.

sudo useradd -U mapd

Enable the Firewall

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

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

For more information, see https://help.ubuntu.com/lts/serverguide/firewall.html.

Note Most cloud providers provide a different mechanism for handling firewall configuration. The commands above might not run in cloud deployments.

Installation

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

  1. Create an installs directory in your home folder: 
    cd ~
sudo mkdir installs
cd installs
  2. Download the desired version of OmniSci from the URL provided you by your Account Executive.
  3. Expand the OmniSci archive file in the installs directory with the following command:  
    sudo tar -xvf <file_name>.tar.gz
  4. List the contents of the installs directory and copy the name of the directory created when expanding the archive. For example: 
    mapd-ee-4.3.0-20181119-b7f85d00bd-Linux-x86_64-render
  5. Go to the opt folder and create a symbolic link to the directory you just copied: 
    cd /opt
ln -s ~/installs/<onmisci_directory> mapd

Configuration

These are the steps to prepare your OmniSci environment.

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.

Initialization

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

cd $MAPD_PATH/systemd
sudo ./install_mapd_systemd.sh

You are prompted for two paths during install: MAPD_PATH and MAPD_STORAGE. MAPD_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/mapd. MAPD_STORAGE defaults to /var/lib/mapd.

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 of particular interest to OmniSci administrators.

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 everything is working correctly, load some sample data, perform a mapdql 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 $MAPD_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. 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: ••••••••••••••••
  4. Enter a SQL query such as the following, based on dataset 2 above: 
    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
  5. Connect to Immerse using a web browser connected to your host machine on port 9092. For example, http://omnisci.mycompany.com:9092.
  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 the 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. 4_firstScatterplot.png