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Tucana

This is a project from Data Science Engineering team at [24]7.ai for creating a service for deploying a combination of Spark models using Mleap technology and generic rules (in Javascript or Python) in production. The library is built on top of akka-HTTP. Currently the server supports two operations: returning the predicted class with maximum probability and top N classes and their probabilities

Dependencies

  1. JDK 8. OpenJDK 8 can be used without any issues.
  2. Scala: Version 2.11.12
    • The binaries should be in the path
  3. Maven: Version 3.3.9 or above
    • The binaries should be in the path
  4. [Optional, for development] IntelliJ IDEA Community Edition

Running with docker

Installing docker

Following are the links for docker installation.

  1. Ubuntu/Debian
  2. CentOS
  3. Windows

Building and packaging

  1. cd Tucana
  2. mvn clean package -DskipTests

Running Tucana tests

  1. cd ../Docker

  2. To run the complete test suite:

    ./run-docker.sh "test"

Using docker shell with Tucana

The following commands would drop you into a docker bash shell with all ModelServer dependencies ready. There you can run other usual commands.

  1. cd ../docker
  2. ./run-docker.sh

It is also possible to mount a host folder with your data into the docker container, and use those files and folders. For example, to load /home/abc from host to docker, use the following command:

 ./run-docker.sh -m /home/abc

Once you are inside the container, this folder will be available at /tucana/project inside the container.