Compass for Developers

MDBW 2019

This is a simple web application to demonstrate how aggregation pipelines are a powerful tool to run some analytics queries in MongoDB and how easy it is to inspect and interact with data in Compass and how quickly you can build and debug complex aggregations with the Aggregation Pipeline Builder in Compass.

How to set up and run the application

After checking out the repository, run npm install to install the dependencies. Then go to Darksky, create an account if you don't have one and get your secret key.

Copy config.example.js to config.js and add your secret key and environment configuration in there. You don't need to touch mongo.localhost and mongo.docker but if you want to connect to Atlas (see below) you will need to add the Atlas connection string to mongo.atlas.

Run on localhost

Run MongoDB locally and with mongoimport import data/weather_data.json to a database named mdbw19 into a collection named weather_data. The collection contains hourly weather observations for NYC and San Francisco from the beginning of 2012 almost to the end of 2017.

At this point, run npm start or npm run dev and go to localhost:3000.

Run with Docker compose

The application and the database are dockerized (intentionally, the data is not persisted in a volume). To start the deployment run:

docker-compose up

Once it's all up and running, seed the database with

./scripts/seed-docker-db.sh

Then go to localhost:3000.

Run on localhost and connect to Atlas

If you have a cluster configured in Atlas, you can connect the web application on localhost to it and use it as your database.

You can seed the database in Atlas with data by running:

mongoimport --uri=<atlas connection string> --collection weather_data --file data/weather_data.json

Once that is done, run the web application with:

DEBUG="mdbw19-compass-for-developers:*" MONGO_ENV=atlas npm run dev

Then go to localhost:3000.

---

You should see a webpage similar to the image below.

The real-time data is fetched from Darksky, the average weather conditions are calculated with an aggregation directly in MongoDB. During the session at MDBW we will see how to build and debug the correct pipeline in Compass.

If you go to http://localhost:3000/historical-weather, you will see a summary of the monthly average temperatures.