Solution 1:

How to design table like this in mongodb?

First, to clarify some naming conventions. MongoDB uses collections instead of tables.

I think there are no foreign keys!

Take the following model:

student
{ 
  _id: ObjectId(...),
  name: 'Jane',
  courses: [
    { course: 'bio101', mark: 85 },
    { course: 'chem101', mark: 89 }
  ]
}

course
{
  _id: 'bio101',
  name: 'Biology 101',
  description: 'Introduction to biology'
}

Clearly Jane's course list points to some specific courses. The database does not apply any constraints to the system (i.e.: foreign key constraints), so there are no "cascading deletes" or "cascading updates". However, the database does contain the correct information.

In addition, MongoDB has a DBRef standard that helps standardize the creation of these references. In fact, if you take a look at that link, it has a similar example.

How can I solve this task?

To be clear, MongoDB is not relational. There is no standard "normal form". You should model your database appropriate to the data you store and the queries you intend to run.

Solution 2:

You may be interested in using a ORM like Mongoid or MongoMapper.

http://mongoid.org/docs/relations/referenced/1-n.html

In a NoSQL database like MongoDB there are not 'tables' but collections. Documents are grouped inside Collections. You can have any kind of document – with any kind of data – in a single collection. Basically, in a NoSQL database it is up to you to decide how to organise the data and its relations, if there are any.

What Mongoid and MongoMapper do is to provide you with convenient methods to set up relations quite easily. Check out the link I gave you and ask any thing.

Edit:

In mongoid you will write your scheme like this:

class Student
  include Mongoid::Document

    field :name
    embeds_many :addresses
    embeds_many :scores    
end

class Address
  include Mongoid::Document

    field :address
    field :city
    field :state
    field :postalCode
    embedded_in :student
end

class Score
  include Mongoid::Document

    belongs_to :course
    field :grade, type: Float
    embedded_in :student
end


class Course
  include Mongoid::Document

  field :name
  has_many :scores  
end

Edit:

> db.foo.insert({group:"phones"})
> db.foo.find()                  
{ "_id" : ObjectId("4df6539ae90592692ccc9940"), "group" : "phones" }
{ "_id" : ObjectId("4df6540fe90592692ccc9941"), "group" : "phones" }
>db.foo.find({'_id':ObjectId("4df6539ae90592692ccc9940")}) 
{ "_id" : ObjectId("4df6539ae90592692ccc9940"), "group" : "phones" }

You can use that ObjectId in order to do relations between documents.

Solution 3:

We can define the so-called foreign key in MongoDB. However, we need to maintain the data integrity BY OURSELVES. For example,

student
{ 
  _id: ObjectId(...),
  name: 'Jane',
  courses: ['bio101', 'bio102']   // <= ids of the courses
}

course
{
  _id: 'bio101',
  name: 'Biology 101',
  description: 'Introduction to biology'
}

The courses field contains _ids of courses. It is easy to define a one-to-many relationship. However, if we want to retrieve the course names of student Jane, we need to perform another operation to retrieve the course document via _id.

If the course bio101 is removed, we need to perform another operation to update the courses field in the student document.

More: MongoDB Schema Design

The document-typed nature of MongoDB supports flexible ways to define relationships. To define a one-to-many relationship:

Embedded document

  1. Suitable for one-to-few.
  2. Advantage: no need to perform additional queries to another document.
  3. Disadvantage: cannot manage the entity of embedded documents individually.

Example:

student
{
  name: 'Kate Monster',
  addresses : [
     { street: '123 Sesame St', city: 'Anytown', cc: 'USA' },
     { street: '123 Avenue Q', city: 'New York', cc: 'USA' }
  ]
}

Child referencing

Like the student/course example above.

Parent referencing

Suitable for one-to-squillions, such as log messages.

host
{
    _id : ObjectID('AAAB'),
    name : 'goofy.example.com',
    ipaddr : '127.66.66.66'
}

logmsg
{
    time : ISODate("2014-03-28T09:42:41.382Z"),
    message : 'cpu is on fire!',
    host: ObjectID('AAAB')       // Reference to the Host document
}

Virtually, a host is the parent of a logmsg. Referencing to the host id saves much space given that the log messages are squillions.

References:

  1. 6 Rules of Thumb for MongoDB Schema Design: Part 1
  2. 6 Rules of Thumb for MongoDB Schema Design: Part 2
  3. 6 Rules of Thumb for MongoDB Schema Design: Part 3
  4. Model One-to-Many Relationships with Document References

Solution 4:

From The Little MongoDB Book

Yet another alternative to using joins is to denormalize your data. Historically, denormalization was reserved for performance-sensitive code, or when data should be snapshotted (like in an audit log). However, with the ever- growing popularity of NoSQL, many of which don’t have joins, denormalization as part of normal modeling is becoming increasingly common. This doesn’t mean you should duplicate every piece of information in every document. However, rather than letting fear of duplicate data drive your design decisions, consider modeling your data based on what information belongs to what document.

So,

student
{ 
    _id: ObjectId(...),
    name: 'Jane',
    courses: [
    { 
        name: 'Biology 101', 
        mark: 85, 
        id:bio101 
    },
  ]
}

If its a RESTful API data, replace the course id with a GET link to the course resource

Solution 5:

The purpose of ForeignKey is to prevent the creation of data if the field value does not match its ForeignKey. To accomplish this in MongoDB, we use Schema middlewares that ensure the data consistency.

Please have a look at the documentation. https://mongoosejs.com/docs/middleware.html#pre