CentOS/RHEL Enterprise Edition GPU with Tarball

This is an end-to-end recipe for installing OmniSci Enterprise Edition on a CentOS/RHEL 7 machine running with NVIDIA Volta, Kepler, or Pascal series GPU cards using a tarball.

Here is a quick video overview of the installation process.

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” CentOS/RHEL 7 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 Centos/RHEL 7 machine by updating your system, installing JDK and EPEL, creating the OmniSci user (named omnisci), installing kernel headers, installing CUDA drivers, and enabling a firewall.

Update and Reboot

Update the entire system and reboot to activate the latest kernel.

sudo yum update
sudo reboot

JDK

Follow these instructions to install a headless JDK and configure an environment variable with a path to the library. The “headless” Java Development Kit does not provide support for keyboard, mouse, or display systems. It has fewer dependencies and is best suited for a server host. For more information, see https://openjdk.java.net.

  1. Open a terminal on the host machine.

  2. Install the headless JDK using the following command:

    sudo yum install java-1.8.0-openjdk-headless

EPEL

Install the Extra Packages for Enterprise Linux (EPEL) repository.

For CentOS, use Yum to install the epel-release package.

sudo yum install epel-release

Use the following install command for RHEL.

yum install https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm

RHEL-based distributions require Dynamic Kernel Module Support (DKMS) to build the GPU driver kernel modules. For more information, see https://fedoraproject.org/wiki/EPEL.

Create the OmniSci User

Create a group called omnisci and a user named omnisci, who will be the owner of the OmniSci database. You can create the group, user, and home directory using the useradd command with the -U and -m switches.

sudo useradd -U -m omnisci

Install CUDA Drivers

CUDA is a parallel computing platform and application programming interface (API) model. It uses a CUDA-enabled graphics processing unit (GPU) for general purpose processing. The CUDA platform provides direct access to the GPU virtual instruction set and parallel computation elements. For more information on CUDA unrelated to installing OmniSci, see https://developer.nvidia.com/cuda-zone.

Install Kernel Headers

Install kernel headers and development packages:

sudo yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)

If installing kernel headers does not work correctly, follow these steps instead:

  1. Identify the Linux kernel you are using by issuing the uname -r command.

  2. Use the name of the kernel (3.10.0-862.11.6.el7.x86_64 in the following code example) to install kernel headers and development packages:

    sudo yum install kernel-devel-3.10.0-862.11.6.el7.x86_64 kernel-headers-3.10.0-862.11.6.el7.x86_64

Install the CUDA Package

To install the CUDA package:

  1. Select the target platform by selecting the operating system (Linux), architecture (based on your environment), distribution (CentOS or RHEL), version (7), and installer type (OmniSci recommends rpm (network)).

  2. Install CUDA per the instructions on the NVIDIA website.

If installing on RHEL, you need to obtain and install the vulkan-filesystem package manually. Perform these additional steps:

  1. Download the rpm file

    wget http://mirror.centos.org/centos/7/os/x86_64/Packages/vulkan-filesystem-1.1.97.0-1.el7.noarch.rpm
  2. Install the rpm file

    sudo rpm --install vulkan-filesystem-1.1.97.0-1.el7.noarch.rpm

You might see a warning similar to the following:

warning: cuda-repo-rhel7-10.0.130-1.x86_64.rpm: Header V3 RSA/SHA512 Signature, key ID 7fa2af80: NOKEY

Ignore it for now; you can verify CUDA driver installation at the Checkpoint.

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:

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

If it is not installed on your host machine, install firewalld.

sudo yum install firewalld
sudo systemctl start firewalld
sudo systemctl enable firewalld
sudo systemctl status firewalld

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=6273/tcp --permanent
sudo firewall-cmd --reload

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

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

Installation

These instructions follow conventions of the OmniSci Engineering team. By creating an omnisci-installs directory and using a symbolic link that points to the current version, you can conveniently roll back to a previous version in the unlikely event that you would want to do so.

Create the omnisci-installs Directory

Use the following command to create the /opt/omnisci-installs directory.

sudo mkdir /opt/omnisci-installs

Download the OmniSci Archive File

You can download the OmniSci archive file using curl, or wget.

To download the OmniSci archive file with curl, use the following command.

sudo curl https://releases.omnisci.com/ee/tar/omnisci-ee-latest-Linux-x86_64-render.tar.gz --output /opt/omnisci-installs/omnisci.tar.gz

To download the OmniSci TAR file with wget, use the following command.

sudo wget https://releases.omnisci.com/ee/tar/omnisci-ee-latest-Linux-x86_64-render.tar.gz -O /opt/omnisci-installs/omnisci.tar.gz

Expand the Archive File

  1. Go to the /opt/omnisci-installs directory.

  2. Expand the OmniSci archive file with the following command:

    sudo tar -xvf omnisci.tar.gz
  3. The expanded directory name is long and complex, with information about the version and build date. For example, the OmniSci 4.8.1 directory name is the following:

    omnisci-ee-4.8.1-20190827-0f29e432f1-Linux-x86_64-render

    Go to the /opt directory and create a symlink to omnisci, using the name of the expanded directory for the current release. For example, for OmniSci 4.8.1, you use the following commands:

    cd /opt
    sudo ln -s /opt/omnisci-installs/omnisci-ee-4.8.1-20190827-0f29e432f1-Linux-x86_64-render omnisci

Configuration

Follow these 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, vi .bashrc.

  4. Edit the .bashrc file. Add the following export commands under “User specific aliases and functions.”

    # User specific aliases and functions
    export OMNISCI_USER=omnisci
    export OMNISCI_GROUP=omnisci
    export OMNISCI_STORAGE=/var/lib/omnisci
    export OMNISCI_PATH=/opt/omnisci
    export OMNISCI_LOG=/var/lib/omnisci/data/mapd_log
  5. Save the .bashrc file. For example, in vi, [esc]:x!

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

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

Initialization

Run the systemd installer.

cd $OMNISCI_PATH/systemd
./install_omnisci_systemd.sh

You are prompted for two paths during install: OMNISCI_PATH and OMNISCI_STORAGE. OMNISCI_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/omnisci. OMNISCI_STORAGE defaults to /var/lib/omnisci.

The script creates a data directory in $OMNISCI_STORAGE with the directories mapd_catalogs, mapd_data, and mapd_export. The 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 OmniSciDB and Immerse.

  1. Start OmniSciDB

    sudo systemctl start omnisci_server
    sudo systemctl start omnisci_web_server
  2. Enable OmniSciDB to start automatically 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. Log into Immerse by entering the default username (omnisci) and password (HyperInteractive), and then clicking Connect.

    .

Checkpoint

To verify that everything is working correctly, 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, and a census of New York City trees. To install sample data, run the following command.

    cd $OMNISCI_PATH
    sudo ./insert_sample_data
  2. When prompted, choose 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 OmniSciDB 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 Select 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.