Slides

MongoDB

MongoDB Overview

  • document database (NoSQL)
  • horizontal sharding => can theoretically serve trillions of records
  • uses JavaScript for data definition and manipulation
  • built-in map-reduce for dynamic collections
  • indexing on fields by value or free-text search

"Mongo is not a toy, although it can be fun to play with." - Josh Burke

Concept: Database

to connect to a database you need a Mongo URI (or URL) identifying the server, port, etc.:

Connection URL format:

mongodb://username:password@host/database

for example

mongodb://mydatabasehost.com:27017/til

Note that the term "database" is overloaded: it refers to either:

  1. a single MongoDB process hosting many data sets
  2. a single MongoDB data set containing many related collections

Concept: Collection

a collection holds documents

this is analogous to a table in SQL

Concept: Document

In MongoDB, a document is essentially a single JavaScript object

Like in a relational database, a document can be created, read, updated, deleted, indexed, searched for, ...

Unlike in a relational database, a document can contain any value for its fields, including arrays and nested objects.

This nesting and type-flexibility makes it very appropriate to store whatever JavaScript objects your app uses, without needing to devise a mapping between nested objects and joined relational tables.

Mongo Console

MongoDB has a JavaScript REPL console, like node.

Launch it by typing mongo dbname on the command line -- e.g. for the til database, run mongo til

In this console, run help to see what's possible.

> db.entries.find({})
{ "_id" : ObjectId("5b5d0e45114a7c1433296d71"), "when" : ISODate("2018-07-29T00:45:57.074Z"), "text" : "hello" }
{ "_id" : ObjectId("5b5d1595e71e8e073c15b229"), "when" : ISODate("2018-07-29T01:17:09.191Z"), "text" : "hello there" }
{ "_id" : ObjectId("5b5e143b203dd808f88d2548"), "when" : ISODate("2018-07-29T19:23:39.695Z"), "text" : "chickens like corn" }
{ "_id" : ObjectId("5b5e27ba44c44608f97083f3"), "when" : ISODate("2018-07-29T20:46:50.749Z"), "text" : "dogs like to bark" }

> db.entries.find({ when: {'$gte': new Date(2018, 6, 29) }})
{ "_id" : ObjectId("5b5e143b203dd808f88d2548"), "when" : ISODate("2018-07-29T19:23:39.695Z"), "text" : "chickens like corn" }
{ "_id" : ObjectId("5b5e27ba44c44608f97083f3"), "when" : ISODate("2018-07-29T20:46:50.749Z"), "text" : "dogs like to bark" }


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