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Extract, PreProcess, and Analyze big data on CPUs
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Run with docker-compose. This depends on two containers:

Name Use Dockerfile location
mapd-core MapD Database Defaults to Community Edition on Docker Hub mapd/mapd-ce-cpu
mapd-ml-cpu Demo notebooks Dockerfile in top-level of mapd-ml-workshop repo


mapd-ml-cpu Server

To build the mapd-ml-cpu container, clone the repo and cd into it.

To build the container, run:

docker build -t mapd-ml-cpu .


If you need to move the containers to a new machine, run:

docker save -o mapd-ce-cpu.tar mapd/mapd-ce-cpu
docker save -o mapd-ml-cpu.tar mapd-ml-cpu

gzip mapd-ce-cpu.tar
gzip mapd-ml-cpu.tar

You will then have files which can be moved to the new machine: mapd-ce-cpu.tar.gz, mapd-ml-cpu.tar.gz. You will also want to grab the docker-compose.yml file.



Uses docker-compose.

Next, modify the docker-compose.yml file to update the path containing the /mapd-storage volume. The default is to store this into a mapd-storage-ml directory in the current dir. To point elsewhere, change the line:

  - ./mapd-storage-ml:/mapd_storage

to, for example:

  - /home/wamsi/mapd-storage-ml:/mapd_storage

This needs to be changed for both the mapd-core and the immerse-iml services.

Import the containers if on a clean machine:

docker load -i mapd-ce-cpu.tar.gz
docker load -i mapd-ml-cpu.tar.gz


If running for the first time, make sure you have docker installed and run it first.

docker ps


docker-compose up

macOS users need to provide host.docker.internal as hostname during setting up connections to MapD. The reason for this being no docker0 bridge on macOS.

Below is a URL for Notebooks:


Below is a URL for Immerse:


If you are setting up dockerfile in an AWS instance then the URL would be like:

http://<Public DNS Name>:9092

You should be able to find the Public DNS name in instances section of aws console. Make sure you allow the TCP/HTTP traffic in security group -> inbound settings. Replace default port 80 with Port numbers 9090, 9092, and 8888.

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