[MongoDB/en] Add Learn MongoDB in Y Minutes (#4214)

* [mongodb/en] Write introduction and getting started * [mongodb/en] Write code sample for CRUD operations * [mongodb/en] Write code sample for operators and database operations * [mongodb/en] Write further reading * [mongodb/en] Minor fixes for Markdown * [mongodb/en] Made each line 80 characters long
2024-12-23 17:41:41 +00:00 · 2021-08-22 08:51:43 -07:00 · 2021-08-22 08:51:43 -07:00 · 848a80d87f
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+---
+language: MongoDB 
+filename: mongo.js 
+contributors:
+  - ["Raj Piskala", "https://www.rajpiskala.ml/"]
+---
+
+MongoDB is a NoSQL document database for high volume data storage.
+
+MongoDB uses collections and documents for its storage. Each document consists
+of key-value pairs using JSON-like syntax, similar to a dictionary or JavaScript
+object.
+
+Likewise, as MongoDB is a NoSQL database, it uses its own query language, Mongo
+Query Language (MQL) which uses JSON for querying.
+
+## Getting Started
+
+### Installation
+
+MongoDB can either be installed locally following the instructions
+[here](https://docs.mongodb.com/manual/installation/) or you can create a
+remotely-hosted free 512 MB cluster
+[here](https://www.mongodb.com/cloud/atlas/register). Links to videos with
+instructions on setup are at the bottom.
+
+This tutorial assumes that you have the MongoDB Shell from
+[here](https://www.mongodb.com/try/download/shell). You can also download the
+graphical tool, MongoDB Compass, down below from the same link.
+
+### Components
+
+After installing MongoDB, you will notice there are multiple command line tools.
+The three most important of which are:
+
+- `mongod` - The database server which is responsible for managing data and
+  handling queries
+- `mongos` - The sharding router, which is needed if data will be distributed
+  across multiple machines
+- `mongo` - The database shell (using JavaScript) through which we can configure
+  our database
+
+Usually we start the `mongod` process and then use a separate terminal with
+`mongo` to access and modify our collections.
+
+### JSON & BSON
+
+While queries in MongoDB are made using a JSON-like\* format, MongoDB stores its
+documents internally in the Binary JSON (BSON format). BSON is not human
+readable like JSON as it's a binary encoding. However, this allows for end users
+to have access to more types than regular JSON, such as an integer or float
+type. Many other types, such as regular expressions, dates, or raw binary are
+supported too.
+
+[Here](https://docs.mongodb.com/manual/reference/bson-types/) is the full list
+of all types that are supported.
+
+- We refer JSON-like to mean JSON but with these extended types. For example,
+  you can make queries directly with a regular expression or timestamp in
+  MongoDB and you can receive data that has those types too.
+
+```js
+/////////////////////////////////////////////////////////
+/////////////////// Getting Started /////////////////////
+/////////////////////////////////////////////////////////
+
+// Start up the mongo database server
+// NOTE - You will need to do this in a separate terminal as the process will 
+// take over the terminal. You may want to use the --fork option
+mongod // --fork
+
+// Connecting to a remote Mongo server
+// mongo "mongodb+srv://host.ip.address/admin" --username your-username
+
+// Mongoshell has a proper JavaScript interpreter built in
+3 + 2 // 5
+
+// Show available databases
+// MongoDB comes with the following databases built-in: admin, config, local
+show dbs
+
+// Switch to a new database (pre-existing or about to exist)
+// NOTE: There is no "create" command for a database in MongoDB. 
+// The database is created upon data being inserted into a collection
+use employees
+
+// Create a new collection
+// NOTE: Inserting a document will implicitly create a collection anyways,
+// so this is not required
+db.createCollection('engineers')
+db.createCollection('doctors')
+
+// See what collections exist under employees
+show collections
+
+/////////////////////////////////////////////////////////
+// Basic Create/Read/Update/Delete (CRUD) Operations: ///
+/////////////////////////////////////////////////////////
+
+/////////////// Insert (Create) /////////////////////////
+
+// Insert one employee into the database
+// Each insertion returns acknowledged true or false
+// Every document has a unique _id value assigned to it automatically
+db.engineers.insertOne({ name: "Jane Doe", age: 21, gender: 'Female' })
+
+// Insert a list of employees into the `engineers` collection
+// Can insert as an array of objects
+db.engineers.insert([
+  { name: "Foo Bar", age: 25, gender: 'Male' },
+  { name: "Baz Qux", age: 27, gender: 'Other' },
+])
+
+// MongoDB does not enforce a schema or structure for objects
+// Insert an empty object into the `engineers` collection
+db.engineers.insertOne({})
+
+// Fields are optional and do not have to match rest of documents
+db.engineers.insertOne({ name: "Your Name", gender: "Male" })
+
+// Types can vary and are preserved on insertion
+// This can require additional validation in some languages to prevent problems
+db.engineers.insert({ name: ['Foo', 'Bar'], age: 3.14, gender: true })
+
+// Objects or arrays can be nested inside a document
+db.engineers.insertOne({
+  name: "Your Name",
+  gender: "Female",
+  skilledIn: [
+    "MongoDB",
+    "NoSQL",
+  ],
+  "date-of-birth": {
+    "date": 1993-07-20T09:44:18.674Z,
+    "age": 26
+  },
+})
+
+// We can override the _id field
+// Works fine
+db.engineers.insertOne({
+  _id: 1,
+  name: "An Engineer",
+  age: 25,
+  gender: "Female",
+})
+
+// Be careful, as _id must ALWAYS be unique for the collection otherwise 
+// the insertion will fail
+// Fails with a WriteError indicating _id is a duplicate value
+db.engineers.insertOne({
+  _id: 1,
+  name: "Another Engineer",
+  age: 25,
+  gender: "Male",
+})
+
+// Works fine as this is a different collection
+db.doctors.insertOne({
+  _id: 1,
+  name: "Some Doctor",
+  age: 26,
+  gender: "Other",
+})
+
+/////////////////// Find (Read) ////////////////////////
+// Queries are in the form of db.collectionName.find(<filter>)
+// Where <filter> is an object
+
+// Show everything in our database so far, limited to a 
+// maximum of 20 documents at a time
+// Press i to iterate this cursor to the next 20 documents
+db.engineers.find({})
+
+// We can pretty print the result of any find() query
+db.engineers.find({}).pretty()
+
+// MongoDB queries take in a JS object and search for documents with matching 
+// key-value pairs
+// Returns the first document matching query
+// NOTE: Order of insertion is not preserved in the database, output can vary
+db.engineers.findOne({ name: 'Foo Bar' })
+
+// Returns all documents with the matching key-value properties as a cursor 
+// (which can be converted to an array)
+db.engineers.find({ age: 25 })
+
+// Type matters when it comes to queries
+// Returns nothing as all ages above are integer type
+db.engineers.find({ age: '25' })
+
+// find() supports nested objects and arrays just like create()
+db.engineers.find({
+  name: "Your Name",
+  gender: "Female",
+  skilledIn: [
+    "MongoDB",
+    "NoSQL",
+  ],
+  "date-of-birth": {
+    "date": 1993-07-20T09:44:18.674Z,
+    "age": 26
+  },
+})
+
+///////////////////////// Update ////////////////////////
+// Queries are in the form of db.collectionName.update(<filter>, <update>)
+// NOTE: <update> will always use the $set operator.
+// Several operators are covered later on in the tutorial.
+
+// We can update a single object
+db.engineers.updateOne({ name: 'Foo Bar' }, { $set: { name: 'John Doe', age: 100 }})
+
+// Or update many objects at the same time
+db.engineers.update({ age: 25 }, { $set: { age: 26 }})
+
+// We can use { upsert: true } if we would like it to insert if the document doesn't already exist,
+// or to update if it does
+// Returns matched, upserted, modified count
+db.engineers.update({ name: 'Foo Baz' },
+  { $set:
+    {
+      age: 26,
+      gender: 'Other'
+    }
+  },
+  { upsert: true }
+)
+
+/////////////////////// Delete /////////////////////////
+// Queries are in the form of db.collectionName.find(<filter>)
+
+// Delete first document matching query, always returns deletedCount
+db.engineers.deleteOne({ name: 'Foo Baz' })
+
+// Delete many documents at once
+db.engineers.deleteMany({ gender: 'Male' })
+
+// NOTE: There are two methods db.collection.removeOne(<filter>) and 
+// db.collection.removeMany(<filter>) that also delete objects but have a
+// slightly different return value.
+// They are not included here as they have been deprecated in the NodeJS driver.
+
+/////////////////////////////////////////////////////////
+//////////////////// Operators //////////////////////////
+/////////////////////////////////////////////////////////
+
+// Operators in MongoDB have a $ prefix. For this tutorial, we are only looking 
+// at comparison and logical operators, but there are many other types of
+// operators
+
+//////////////// Comparison Operators ///////////////////
+
+// Find all greater than or greater than equal to some condition
+db.engineers.find({ $gt: { age: 25 }})
+db.engineers.find({ $gte: { age: 25 }})
+
+// Find all less than or less than equal to some condition
+db.engineers.find({ $lte: { age: 25 }})
+db.engineers.find({ $lte: { age: 25 }})
+
+// Find all equal or not equal to
+// Note: the $eq operator is added implicitly in most queries
+db.engineers.find({ $eq: { age: 25 }})
+db.engineers.find({ $ne: { age: 25 }})
+
+// Find all that match any element in the array
+db.engineers.find({ age: ${ in: [ 20, 23, 24, 25 ]}})
+
+//////////////// Logical Operators ///////////////////
+
+// Join two query clauses together
+// NOTE: MongoDB does this implicitly for most queries
+db.engineers.find({ $and: [
+  gender: 'Female',
+  age: {
+    $gte: 18
+  }
+]})
+
+// Match either query condition
+db.engineers.find({ $or: [
+  gender: 'Female',
+  age: {
+    $gte: 18
+  }
+]})
+
+// Negates the query
+db.engineers.find({ $not: {
+  gender: 'Female'
+}})
+
+// Must match none of the query conditions
+db.engineers.find({ $nor [
+  gender: 'Female,
+  age: {
+    $gte: 18
+  }
+]})
+
+/////////////////////////////////////////////////////////
+//////////////// Database Operations: ///////////////////
+/////////////////////////////////////////////////////////
+
+// Delete (drop) the employees database
+// THIS WILL DELETE ALL DOCUMENTS IN THE DATABASE!
+db.dropDatabase()
+
+// Create a new database with some data
+use example
+db.test.insertOne({ name: "Testing data, please ignore!", type: "Test" })
+
+// Quit Mongo shell
+exit
+
+// Import/export database as BSON:
+
+// Mongodump to export data as BSON for all databases
+// Exported data is found in under "MongoDB Database Tools/bin/dump"
+// NOTE: If the command is not found, navigate to "MongoDB Database Tools/bin" 
+// and use the executable from there mongodump
+
+// Mongorestore to restore data from BSON
+mongorestore dump
+
+// Import/export database as JSON:
+// Mongoexport to export data as JSON for all databases
+mongoexport --collection=example
+
+// Mongoimport to export data as JSON for all databases
+mongoimport  --collection=example
+```
+
+## Further Reading
+
+### Setup Videos
+
+- [Install MongoDB - Windows 10](https://www.youtube.com/watch?v=85A6m1soKww)
+- [Install MongoDB - Mac](https://www.youtube.com/watch?v=DX15WbKidXY)
+- [Install MongoDB - Linux
+  (Ubuntu)](https://www.youtube.com/watch?v=wD_2pojFWoE)
+
+### Input Validation
+
+From the examples above, if input validation or structure is a concern, I would
+take a look at the following ORMs:
+
+- [Mongoose (Node.js)](https://mongoosejs.com/docs/) - Input validation through
+  schemas that support types, required values, minimum and maximum values.
+- [MongoEngine (Python)](http://mongoengine.org/) - Similar to Mongoose, but I
+  found it somewhat limited in my experience
+- [MongoKit (Python)](https://github.com/namlook/mongokit) - Another great
+  alternative to MongoEngine that I find easier to use than MongoEngine
+
+For statically strongly typed languages (e.g. Java, C++, Rust), input validation
+usually doesn't require a library as they define types and structure at compile
+time.
+
+### Resources
+
+If you have the time to spare, I would strongly recommend the courses on
+[MongoDB University](https://university.mongodb.com/). They're by MongoDB
+themselves and go into much more detail while still being concise. They're a mix
+of videos and quiz questions and this was how I gained my knowledge of MongoDB.
+
+I would recommend the following video series for learning MongoDB:
+
+- [MongoDB Crash Course - Traversy
+  Media](https://www.youtube.com/watch?v=-56x56UppqQ)
+- [MongoDB Tutorial for Beginners -
+  Amigoscode](https://www.youtube.com/watch?v=Www6cTUymCY)
+
+Language-specific ones that I used before:
+
+- [Build A REST API With Node.js, Express, & MongoDB - Web Dev
+  Simplified](https://www.youtube.com/watch?v=fgTGADljAeg)
+- [MongoDB with Python Crash Course - Tutorial for Beginners -
+  FreeCodeCamp](https://www.youtube.com/watch?v=E-1xI85Zog8)
+- [How to Use MongoDB with Java - Random
+  Coder](https://www.youtube.com/watch?v=reYPUvu2Giw)
+- [An Introduction to Using MongoDB with Rust -
+  MongoDB](https://www.youtube.com/watch?v=qFlftfLGwPM)
+
+Most of the information above was cross-referenced with the [MongoDB
+docs](https://www.mongodb.com/). Here are the docs for each section:
+
+- [MongoDB Types](https://docs.mongodb.com/manual/reference/bson-types/) - List
+  of all types that MongoDB supports natively
+- [MongoDB Operators](https://docs.mongodb.com/manual/reference/operator/) -
+  List of operators MongoDB supports natively
+- [MongoDB CRUD](https://docs.mongodb.com/manual/reference/command/nav-crud/) -
+  Commands for create, read, update, delete
+
+If you've been enjoying MongoDB so far and want to explore intermediate
+features, I would look at
+[aggregation](https://docs.mongodb.com/manual/reference/command/nav-aggregation/),
+[indexing](https://docs.mongodb.com/manual/indexes/), and
+[sharding](https://docs.mongodb.com/manual/sharding/).
+
+- Aggregation - useful for creating advanced queries to be executed by the
+  database
+- Idexing allows for caching, which allows for much faster execution of queries
+- Sharding allows for horizontal data scaling and distribution between multiple
+  machines.