MongoDB and Mongoose - Arquisoft/radarin_en2b GitHub Wiki

MongoDB

MongoDB is a NoSQL database system which stores data in the form of BSON (binary representation of JSON) documents. In terms of Node.js, mongodb is the native driver for interacting with a mongodb instance and mongoose is an Object modeling tool for MongoDB.

Installing Mongoose and MongoDB

First, we need to install mongoose if it is not already done. Mongoose is installed in (package.json) like any other dependency using npm:

npm install mongoose

To be able to use schema definitions for GeoJSON types we need first to have installed node.js, mongodb and mogoose. documentation

npm install mongoose-geojson-schema --save

In order to run the mongo db database we only need docker as it is the manager of doing it.

Connecting to MongoDB

// import the mongoose module

const mongoose = require("mongoose")

// example of setting up a default mongoose connection

mongoose.connect('mongodb://localhost:27017/myapp', {useNewUrlParser: true, useUnifiedTopology: true});

// or (if we want and need to specify several more paramentes in the uri)

mongoose.connect('mongodb://username:password@host:port/database?options...', {useNewUrlParser: true, useUnifiedTopology: true});

// to handle initial connection errors

mongoose.connect(...).catch(error => handleError(error));

// to handle errors after initial connection was established, we should listen for error events on the connection.

mongoose.connection.on('error', err => {

logError(err);

});

connection documentation

Queries

In the following link (here) there are lots of query methods and examples of how to do them.

We can also use helper functions that mongoose models provides us for CRUD operations. Each of these functions returns a mongoose query object. Link to the documentation here

To make a query which specifies a GeoJSON data (in this case a point), $near operator requires a 2dsphere index and has the following syntax and considering a collection places:

db.places.find(
    {
        location:
        { $near :
            {
                $geometry: { type: "Point",  coordinates: [ -73.9667, 40.78 ] },
                $minDistance: 1000,
                $maxDistance: 5000
            }
        }
    }
)

If specifying latitude and longitude coordinates as in the example before, list the longitude first and then latitude:

Valid longitude values are between -180 and 180, both inclusive.
Valid latitude values are between -90 and 90, both inclusive.

The query returns documents that are at least 1000 meters from and at most 5000 meters from the specified GeoJSON point, sorted from nearest to farthest.

$near documentation

Schema

Mongoose schemas have a timestamps option that tells Mongoose to automatically manage createdAt and updatedAt properties on your documents. For example, here's how you can enable timestamps on a User model.

When you enable timestamps, Mongoose adds createdAt and updatedAt properties to your schema. By default, createdAt and updatedAt are of type Date. When you update a document, Mongoose automatically increments updatedAt.

const GeoJSON = require('mongoose-geojson-schema')

const mongoose = require("mongoose")

const schema = mongoose.Schema(
    {
        webId: String,
    location: mongoose.Schema.Types.Point,
    authKey: String
    },
    { timestamps: true }
);

const User = mongoose.model("User", schema); // User is a collection

const doc = await User.create({ webId: "https://in..../user/asdfg",
    location: {
        type: "Point",
        coordinates: [43.53573, -5.66152 ]
    }, 
    authKey: "auth123456789"});

doc.createdAt; // 2020-07-06T20:36:59.414Z

doc.updatedAt; // 2020-07-06T20:36:59.414Z

doc.createdAt instanceof Date; // true

timestamps link

Another option is to have the timestamps disabled (default behaviour) and do it manually as following but in my opinion the first is the best option:

const schema = mongoose.Schema({
    webId: String,
    location: mongoose.Schema.Types.Point,
    timestamp: Date,
    authKey: String
})

var user = {
    webId: "https://in..../user/asdfg",
    location: {
	type: "Point",
	coordinates: [43.53573, -5.66152 ]
    }, 
    timestamp: ISODate("2021-02-28T12:00:00.000Z"),
    authKey: "auth123456789"
}

module.exports = mongoose.model("User", schema)

Indexes

Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement.

indexes

compound indexes

examples of different indexes