Talento90 / organization-api

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There are multiple solutions for this challenge and that's why I would like to explain my decisions.

So, after reading the requirements I decided to focus on the reads performance. To achieve that I decided to flatten the tree structure, doing this I can easily search for all relations of any organization because I have all the relations in the database.

Example:

{
    "org_name": "Paradise Island",
    "daughters": [{
        "org_name": "Banana tree",
        "daughters": [{
            "org_name": "Yellow Banana"
        },
        {
            "org_name": "Brown Banana"
        }]
    }]
}

+-----------------+-----------------+----------+
| org             | org_relative    | relation |
+-----------------+-----------------+----------+
| Banana tree     | Brown Banana    | daughter |
| Banana tree     | Paradise Island | parent   |
| Banana tree     | Yellow Banana   | daughter |
| Brown Banana    | Banana tree     | parent   |
| Brown Banana    | Yellow Banana   | sister   |
| Paradise Island | Banana tree     | daughter |
| Yellow Banana   | Banana tree     | parent   |
| Yellow Banana   | Brown Banana    | sister   |
+-----------------+-----------------+----------+

If I want to search the relations of Banana tree I just need to do a simple SELECT * FROM organization WHERE org = 'Banana tree' and I get all the direct relations (parent, daughter, sister).

Of course, there are no perfect solutions, and by improving the read operations I sacrificed the writes, basically it's a trade off.

Advantages

  • Fast and simple read operations

Disadvantages

  • Lose tree hierarchy (we can't rebuilt the tree)
  • Flatten tree (bunch of rows)

Setup Project

  1. Create database (scripts/create-database.sql)
  2. Install node dependencies (npm install)
  3. Run application (npm run start or npm run start-pm2)
  4. (Optional) Generate fake data (npm run generate)
  5. GET: http://localhost:5000/api/organizations/TestOrg?page=1

About

License:MIT License


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