CentOS 7 Installation Recipe¶

Assumptions¶

These instructions assume the following:

• You are installing on a “clean” CentOS 7 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.

Preparation¶

Prepare your Centos 7 machine by installing JDK, EPEL, and CUDA, and enabling a firewall.

sudo yum install epel-release

sudo yum update
sudo reboot

sudo useradd -U mapd

curl -O -u mapd http://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-<VERSION INFO, for example 8.0.61-1.x86_64>.rpm

sudo rpm --install cuda-repo-rhel7-<VERSION INFO, for example 8.0.61-1.x86_64>.rpm
sudo yum clean expire-cache
sudo yum install cuda-drivers

sudo reboot

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

Installation¶

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

1. Download the MapD archive using the username and password provided by your sales representative.

2. Expand the archive wherever you choose (the home directory is fine):

   tar -xvf mapd2-latest-Linux-x86_64-nocuda.tar.gz
   

3. For convenience, you can rename the top-level directory mapd.

Configuration¶

Configure MapD by creating environment variables for your MapD storage directory and user. The $MAPD_STORAGE directory must be dedicated to MapD: do not set it to a directory shared by other packages.

1. Create a data directory environment variable and directory.

   export MAPD_STORAGE=/var/lib/mapd
   sudo mkdir -p $MAPD_STORAGE
   

2. Change the owner of the data directory to the MapD user (for example, mapd).

   export MAPD_USER=mapd
   sudo chown -R $MAPD_USER $MAPD_STORAGE
   

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

Initialization¶

These are the steps to initialize the database and prepare systemd commands for MapD Core.

1. Initialize the database. This example assumes MapD is installed in the home folder.

   export MAPD_PATH=/opt/mapd
   $MAPD_PATH/bin/initdb $MAPD_STORAGE
   

   The initdb script creates a data directory in MAPD_STORAGE, with the directories mapd_catalogs, mapd_data, mapd_export, mapd_import, mapd_log. The log directory is the one of most interest to a MapD administrator.

2. Set these Environment variables (substitute your own values where appropriate). You will use these values when you run the systemd installer in the next step.

   export MAPD_PATH=/opt/mapd
   export MAPD_STORAGE=/var/lib/mapd
   export MAPD_USER=mapd
   export MAPD_GROUP=mapd
   export LD_LIBRARY_PATH=/usr/lib/jvm/jre-1.8.0-openjdk/lib/amd64/server
   

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

   cd $MAPD_PATH/systemd
   ./install_mapd_systemd.sh
   

Activation¶

Start and use MapD Core and Immerse.

1. Start MapD Core

   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
   

Checkpoint

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.

sudo $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 MapD 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://mapd.mycompany.com:9092.

Create a new dashboard and a pointmap to verify that backend rendering is working.

1. Click New Dashboard.
2. Select the flights_2008_10K table as the datasource.
3. Click Connect to Table.
4. Click Add Chart.
5. Click SCATTER.
6. Click X Axis +Add Measure.
7. Choose arrdelay.
8. Click Y Axis +Add Measure.
9. Choose depdelay.

The resulting chart shows, unsurprisingly, that there is a correlation between departure delay and arrival delay.