lparvinsmith / mongodb-intro

An introduction to MongoDB

An Introduction to MongoDB

Relational databases are good at modeling data that fits into tables. What do you use if your data isn't that structured?

Objectives

By the end of the lesson, students should be able to:

• Describe tradeoffs between using a NoSQL database versus a relational database
• Use the MongoDB shell to interact with MongoDB databases and collections
• Create, Read, Update, and Delete documents in MongoDB collections using the Mongo shell

Installation

We'll walk through the instructions in INSTALL.md.

Terminology

Relational Database Term	MongoDB Term
database	database
table	collection
row	document
column	field

Creating a MongoDB database and a collection

First we start the mongo shell:

$ mongo
MongoDB shell version: 3.0.3
connecting to: test
>

The command to list databases is show databases

> show databases
local  0.078GB
>

The command to connect to a database is use <database name>:

> use crud
switched to db crud
> show databases
local  0.078GB
>

MongoDB lets us select a database that hasn't been created. When we add a collection, the database will be created.

Our first collection will be called contacts. It has no entries.

> db.contacts.count();
0

This is a common pattern in MongoDB: you can refer to things that don't yet exist, and it will cooperate. MongoDB won't create them until you give it something to remember.

Creating data

We're going to start keeping a contacts collection.

Our first contact is Joe Recruiter, with Staffing Inc. We can create his record this way:

Demonstration

db.contacts.insert({
    name: 'Joe Recruiter',
    company: 'Staffing Inc.',
    phone: {
        office: '617-555-1991 ext. 311',
        cell: '508-555-9215'
    },
    email: '[e-mail]'
});

MongoDB uses JSON natively, which makes it convenient for JavaScript web applications. Conveniently, MongoDB let's us specify the JSON as a JavaScript object.

Now that we've inserted data into it, the crud database exists:

>  show databases;
contacts  0.078GB
local     0.078GB
>

Code along

Let's add these people to the contacts database:

Ann Placement-Manager, Staffing Inc., office phone [phone] ext. 315, cell phone [phone], email [e-mail]

Martine H. R. Manager, TechCorp LLC, title Director of Human Resources, office phone [phone], cell phone [phone], home phone [phone], work email [e-mail], home email [e-mail]

We'll create a script to run using the MongoDB shell. We'll use var db = new Mongo().getDB('crud'); at the top of the script to ensure we connect to the correct database.

Retrieving and Reading Data

Demonstration

Let's start by looking at the entire database so far.

> db.contacts.find();
{ "_id" : ObjectId("5579a06aaa2cdce4a1f15f21"), "name" : "Joe Recruiter", "company" : "Staffing Inc.", "phone" : { "office" : "617-555-1991 ext. 311", "cell" : "508-555-9215" }, "email" : "[e-mail]" }
{ "_id" : ObjectId("5579a202aa2cdce4a1f15f22"), "name" : "Ann Placement-Manager", "company" : "Staffing Inc.", "phone" : { "office" : "617-555-1991 ext. 315", "cell" : "718-555-9151" }, "email" : "[e-mail]" }
{ "_id" : ObjectId("5579a20aaa2cdce4a1f15f23"), "name" : "Martine H. R. Manager", "title" : "Director of Human Resources", "company" : "TechCorp LLC", "phone" : { "office" : "617-555-7123", "cell" : "617-555-9918", "home" : "617-555-1122" }, "email" : { "work" : "[e-mail]", "home" : "[e-mail]" } }
>

That's kind of tough to read, so we can filter it through .pretty()

> db.contacts.find().pretty();
{
    "_id" : ObjectId("5579a06aaa2cdce4a1f15f21"),
    "name" : "Joe Recruiter",
    "company" : "Staffing Inc.",
    "phone" : {
        "office" : "617-555-1991 ext. 311",
        "cell" : "508-555-9215"
    },
    "email" : "[e-mail]"
}
{
    "_id" : ObjectId("5579a202aa2cdce4a1f15f22"),
    "name" : "Ann Placement-Manager",
    "company" : "Staffing Inc.",
    "phone" : {
        "office" : "617-555-1991 ext. 315",
        "cell" : "718-555-9151"
    },
    "email" : "[e-mail]"
}
{
    "_id" : ObjectId("5579a20aaa2cdce4a1f15f23"),
    "name" : "Martine H. R. Manager",
    "title" : "Director of Human Resources",
    "company" : "TechCorp LLC",
    "phone" : {
        "office" : "617-555-7123",
        "cell" : "617-555-9918",
        "home" : "617-555-1122"
    },
    "email" : {
        "work" : "[e-mail]",
        "home" : "[e-mail]"
    }
}

What do we see?

• MongoDB gave each of our documents a unique ID field, called _id.

• MongoDB doesn't care that Joe and Ann only have one email, while Martine has two emails. It also doesn't care that Martine has a job title, while Joe and Ann do not.

Note: In a MongoDB shell script use .forEach(printjson) to display the results of your query.

Searching for particular things

We can pass arguments to find, and MongoDB will give us all matching records:

> db.contacts.find({ _id: ObjectId("5579a20aaa2cdce4a1f15f23") }).pretty();
{
    "_id" : ObjectId("5579a20aaa2cdce4a1f15f23"),
    "name" : "Martine H. R. Manager",
    "title" : "Director of Human Resources",
    "company" : "TechCorp LLC",
    "phone" : {
        "office" : "617-555-7123",
        "cell" : "617-555-9918",
        "home" : "617-555-1122"
    },
    "email" : {
        "work" : "[e-mail]",
        "home" : "[e-mail]"
    }
}
> db.contacts.find({ company: "Staffing Inc." }).pretty();
{
    "_id" : ObjectId("5579a06aaa2cdce4a1f15f21"),
    "name" : "Joe Recruiter",
    "company" : "Staffing Inc.",
    "phone" : {
        "office" : "617-555-1991 ext. 311",
        "cell" : "508-555-9215"
    },
    "email" : "[e-mail]"
}
{
    "_id" : ObjectId("5579a202aa2cdce4a1f15f22"),
    "name" : "Ann Placement-Manager",
    "company" : "Staffing Inc.",
    "phone" : {
        "office" : "617-555-1991 ext. 315",
        "cell" : "718-555-9151"
    },
    "email" : "[e-mail]"
}
>

We got a call from 617-555-1122. Who is it?

db.contacts.find({ $or: [
    { phone: '617-555-1122'},
    { 'phone.office': '617-555-1122' },
    { 'phone.cell': '617-555-1122' },
    { 'phone.home': '617-555-1122' }
]});

Let's look at the SQL to MongoDB Mapping Chart.

Code along

Working with your groups so that you can assist each other.

• Make up five fictional people and add them to your contacts collection.

• For now, keep things in the formats we have used with Joe Recruiter, Ann Placement-Manager, and Martine H. R. Director.

• Make sure at least one of your people works for Staffing Inc. or TechCorp LLC.

• Search for your people and make sure you find them in the database.

Update

Demonstration

Suppose that Joe Recruiter has founded his own firm. We start with finding him in the database:

> db.contacts.find({name: "Joe Recruiter"}).pretty();
{
    "_id" : ObjectId("5579a06aaa2cdce4a1f15f21"),
    "name" : "Joe Recruiter",
    "company" : "Staffing Inc.",
    "phone" : {
        "office" : "617-555-1991 ext. 311",
        "cell" : "508-555-9215"
    },
    "email" : "[e-mail]"
}
>

With the same searh clause, we can update that document:

db.contacts.update({
    name: "Joe Recruiter"
},{ $set: {
    company: 'Recruiter Recruitment LLC',
    'phone.office': '508-555-1111'
}});

db.contacts.update({
    name: "Joe Recruiter"
}, {
    $set: { email: '[e-mail]' }
});

The $set key expects a dictionary of key-value pairs to update.

Code along

• One of the contacts we added got a job at Staffing Inc. Change his or her company, office phone number, and email.

• One of our contacts has a new job title. Update it.

Keeping a record of communications

MongoDB makes it easy to add an array of items to a document.

db.contacts.update({
    name: "Joe Recruiter"
}, {
    $push: { communications: {
        from: 'Bob',
        date: '20150914',
        summary: "Discussed entry level dev opportunity" }
    }
});

db.contacts.update({
    name: "Joe Recruiter"
}, {
    $push: { communications: {
        from: 'Bob',
        date: '20150916',
        summary: "Discussed entry level dev opportunity details" }
    }
});

Code along

Let's create a list of something attached to one of our contacts. Maybe she collects classic cars?

Deleting a field

Demonstration

We've secured a position and decide to remove our communications with Joe Recruiter:

db.contacts.update({
    name: "Joe Recruiter"
}, { $unset: { communications: 1 }});
})

Deleting a document

Joe Recruiter has retired and moved to Costa Rica so we remove him as a contact.

db.contacts.remove({ name: "Joe Recruiter"});

Lab: Veterinary Cat-astrophe

We're starting a veterinary practice to take care of all the cats we know.

Start with var db = new Mongo().getDB('crud'); at the top of your script, then add these cats:

• Tiger, male, age 7, black short hair, adopted from NYSPCA
• Reggie, male, age 7, half-Siamese striped tabby, adopted from NYSPCA
• Ting, seal point Siamese, age 8, male, Siamese rescue
• Boris, male, Russian blue, age 5, brother to Natasha, adopted from NYSPCA
• Natasha, female, Russian blue, age 5, sister to Boris, adopted from NYSPCA
• Bond, female, black and white tuxedo cat, age 4, found in Harvard Yard
• Sacco, male, half-Siamese, age 3, adopted from MSPCA, brother to Vanzetti
• Vanzetti, male, half-Siamese, age 3, adopted from MSPCA, brother to Sacco
• M, female, grey tuxedo cat, age 3, adopted from MSPCA
• Gilbert, male, 3/4-Siamese, age 3, adopted from MSPCA
• Sullivan, male 3/4-Siamese, age 3, adopted from MSPCA
• Domino, age 1, black and white tuxedo cat, rescued from Alabama
• Ann, female, age 8, grey leopard tabby, found under a barn, sister to Julian
• Julian, female, age 8, grey leopard tabby, found under a barn, sister to Ann

Some cats have favorite pastimes:

• Tiger likes sitting in the sun.
• Reggie likes complaining at the top of his voice.
• Boris likes echo-locating in ventilation systems.
• Sacco and Vanzetti like making mischief.
• Bond likes ordering people around.
• Domino likes harassing other cats.

Now, we're a veterinary practice. Make up at least fifteen vet visits and use the update + $push method to record them. Do not distribute them evenly: some cats should have no vet visits on record, others will have several.

If we want to clean up, db.dropDatabase(); drops the current database.

Review Objectives

Let's discuss the first objective. Based on what you've seen, what are some of the trade-offs between using a NoSQL database like MongoDB and using a relational database?