Ubuntu EE GPU Installation With Tarball

This is an end-to-end recipe for installing MapD Enterprise Edition on an Ubuntu machine running with NVIDIA Kepler or Pascal series GPU cards. This install has all of the functionality of MapD.

Here is a quick video overview of the installation process.

The installation phases are:

Note: The order of these instructions is significant. Please install each component in the order presented to prevent aggravated hair loss.


These instructions assume the following:
  • You are installing on a “clean” Ubuntu host machine with only the operating system installed.
  • Your MapD host only runs the daemons and services required to support MapD.
  • Your MapD host is connected to the Internet.


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

Update and Reboot

Update the entire system.

sudo apt update
sudo apt upgrade

Install a “headless” Java Runtime Environment.

sudo apt install default-jre-headless

Reboot to activate the latest kernel.

sudo reboot

Create the MapD User

Create the mapd group and mapd user, who will be the owner of the MapD 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.

Install CUDA Drivers

Download the DEB package provided by NVIDIA from the NVIDIA CUDA Zone.

  1. Install the CUDA repository, update local repository cache, and then install the CUDA Toolkit and GPU drivers.

    sudo dpkg --install cuda-repo-ubuntu1604_8.0.44-1_amd64.deb
    sudo apt update
    sudo apt install cuda-drivers linux-image-extra-virtual

    Where cuda-repo-ubuntu1604_8.0.44-1_amd64.deb is the name of the package provided by NVIDIA.

  2. Reboot.

    sudo reboot
  3. Verify installation of the GPU drivers by running the following command.



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

  1. Create an ~/installs directory

  2. Download the MapD archive to the ~/installs directory.

  3. Expand the archive provided by your MapD sales representative in the ~/installs directory with the following command.

    tar -xvf <file_name>.tar.gz
  4. Create a symbolic link. The symbolic link lets you navigate to the MapD directory without typing the lengthy directory name, and lets you upgrade to a new version by redirecting the link.

    cd ~/
    ln -s ~/installs/<MapD Directory> mapd

For example, for MapD version 3.2.0, the symbolic link command was:

ln -s ~/installs/mapd-ee-3.2.0-20170817-8ab3117-Linux-x86_64-cuda mapd


These are the steps to prepare your MapD environment.

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

  1. Go to your home directory.

  2. Use ctrl-h to show hidden files.

  3. Edit the .bashrc file. Add the following export commands under user specific aliases.

    # User specific aliases and functions
    export MAPD_USER=mapd
    export MAPD_GROUP=mapd
    export MAPD_STORAGE=/var/lib/mapd
    export MAPD_PATH=/home/mapd/mapd
  4. Save the .bashrc file.

  5. Open a new terminal window to use your changes.

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

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


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

  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 MapD administrator.

    cd $MAPD_PATH/systemd
    sudo ./install_mapd_systemd.sh


Start and use MapD Core and Immerse.

  1. Start MapD Core

    cd $MAPD_PATH
    sudo systemctl start mapd_server
    sudo systemctl start mapd_web_server
  2. Enable MapD Core to start when the system reboots.

    sudo systemctl enable mapd_server
    sudo systemctl enable mapd_web_server


To verify that all systems are go, load some sample data, perform a mapdql query, and generate a pointmap using Immerse.

MapD ships with two sample datasets of airline flight information collected in 2008. 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).

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

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,
Origin|Destination|Average Airtime
Ft. Myers|Orlando|28.666667
Orlando|Ft. Myers|32.583333

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