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Introduction

Query timeline and event information from medical records using to provide a REST API to Spark.

Data

We use synthetic data generated to be of the same format and in line with the real data.

Use

The fastest approach is to spin up a Docker container containing a full Spark Jobserver stack. We have done some preparations, so that should be easy...

Setup: Word count

In order to test the setup, we will run an example provided by Spark Jobserver. Please follow the guide available here: https://github.com/data-intuitive/spark-jobserver.

The short version is this:

docker run -d -p 8090:8090 -v /tmp/api/data:/app/data tverbeiren/jobserver

If this step is working, you can proceed to the next one.

Tetraites API binary release

Let's assume you've started the docker container as described in

Start by downloading the assembly jar and store it under /tmp/api:

wget http://dl.bintray.com/tverbeiren/maven/info/verbeiren/tetraitesapi_2.11/0.0.2/tetraitesapi_2.11-0.0.2-assembly.jar
mv tetraitesapi_2.11-0.0.2-assembly.jar /tmp/api/

Now, in order to make life easy, some scripts are available. Two configuration files define the behavior of these scripts: config/settings.sh and config/initialize-docker.conf. Take a look at both to see what is going on. They are configured to work with the procedure described in this manual.

Start the Tetraites API:

scripts/initialize.sh

Test the available endpoints:

scripts/farmaTimeline.sh
scripts/gezoTimeline.sh

Tetraites API source

In order to compile from source, the following procedure should be sufficient (given all dependencies are available):

  1. Clone the project from github
  2. Run the script compileAndRun.sh

These two steps should be sufficient to be in the state ready for following the procedure for the binary release described above.