sinai-doron / meteors

# Meteor App Server

Description

This is the backend to support the Meteor App UI.

Table of Contents

• Design Decisions
  • Assumptions
  • Caching
  • Data Storage
  • Pagination
• Installation
• Running the App
• Testing

Design Decisions

Assumptions

1. Data set is finite and small, containing only 1000 records.

Caching

For caching, we utilized the cache-manager library to naively cache each HTTP call using the URL as the key. This decision was made for simplicity and ease of implementation.

However, a more advanced caching system could be beneficial for larger scenarios. Systems like Redis or other in-memory caching solutions could provide better performance. They would permit caching of query results and introduce more optimization opportunities.

Data Storage

The dataset, being small and finite, is stored as a JSON data structure for demonstration purposes. In more scalable scenarios, a relational DB would be more appropriate. A potential SQL data model might be:

CREATE TABLE meteorites (
    meteorite_id INT PRIMARY KEY,
    name VARCHAR(255),
    nametype VARCHAR(255),
    recclass VARCHAR(255),
    mass FLOAT,
    fall VARCHAR(255),
    year DATETIME
);

Using a relational database would provide benefits like caching, offsetting, relationships, and lookups. Still, given our dataset's size, the JSON structure should perform adequately.

Pagination

Given our primary assumption and the choice against a relational DB, pagination is straightforward. We slice the dataset and offset results based on the requested page.

Installation

$ npm install

Running the App Locally

# development
$ npm run start

# watch mode
$ npm run start:dev

# production mode
$ npm run start:prod

Running the App Docker

# build the container
$ docker build -t meteor-server .

# run the container
$ docker run -p 3001:3001 meteor-server

Testing

# unit tests
$ npm run test

# e2e tests
$ npm run test:e2e

# test coverage
$ npm run test:cov