MongoDB: Data Modeling

Document Structure

MongoDB 用两种documents structure来描绘数据的关联关系: References and Embedded documents.

References(Normalized Data Models)

reference model

Embedded Data(Denormalized Data Models)

Embedded Data model

Atomicity

In MongoDB, operations are atomic at the document level. No single write operation can change more than one document. Operations that modify more than a single document in a collection still operate on one document at a time.

Model Relationship between Documents

Model One-to-One Relationships with Embedded Documents

Consider the following example that maps patron and address relationships.

  • In the normalized data model
    the address document contains a reference to the patron document.
{                          # patron document
   _id: "joe",
   name: "Joe Bookreader"
}

{                        # address document
   patron_id: "joe",
   street: "123 Fake Street",
   city: "Faketon",
   state: "MA",
   zip: "12345"
}
  • With the embedded data model
{
   _id: "joe",
   name: "Joe Bookreader",
   address: {
              street: "123 Fake Street",
              city: "Faketon",
              state: "MA",
              zip: "12345"
            }
}

Model One-to-Many Relationships with Embedded Documents

Consider the following example that maps patron and multiple address relationships.

  • In the normalized data model
{
   _id: "joe",
   name: "Joe Bookreader"
}

{
   patron_id: "joe",
   street: "123 Fake Street",
   city: "Faketon",
   state: "MA",
   zip: "12345"
}

{
   patron_id: "joe",
   street: "1 Some Other Street",
   city: "Boston",
   state: "MA",
   zip: "12345"
}
  • With the embedded data model
{
   _id: "joe",
   name: "Joe Bookreader",
   addresses: [
                {
                  street: "123 Fake Street",
                  city: "Faketon",
                  state: "MA",
                  zip: "12345"
                },
                {
                  street: "1 Some Other Street",
                  city: "Boston",
                  state: "MA",
                  zip: "12345"
                }
              ]
 }

Model One-to-Many Relationships with Document References

感觉，这个有点像是 Many-to-One...
Consider the following example that maps publisher and book relationships.

  • With the embedded data model
    Embedding the publisher document inside the book document would lead to repetition of the publisher data, as the following documents show:
{
   title: "MongoDB: The Definitive Guide",
   author: [ "Kristina Chodorow", "Mike Dirolf" ],
   published_date: ISODate("2010-09-24"),
   pages: 216,
   language: "English",
   publisher: {
              name: "O'Reilly Media",
              founded: 1980,
              location: "CA"
            }
}

{
   title: "50 Tips and Tricks for MongoDB Developer",
   author: "Kristina Chodorow",
   published_date: ISODate("2011-05-06"),
   pages: 68,
   language: "English",
   publisher: {
              name: "O'Reilly Media",
              founded: 1980,
              location: "CA"
            }
}
  • using references
{
   name: "O'Reilly Media",
   founded: 1980,
   location: "CA",
   books: [123456789, 234567890, ...]
}

{
    _id: 123456789,
    title: "MongoDB: The Definitive Guide",
    author: [ "Kristina Chodorow", "Mike Dirolf" ],
    published_date: ISODate("2010-09-24"),
    pages: 216,
    language: "English"
}

{
   _id: 234567890,
   title: "50 Tips and Tricks for MongoDB Developer",
   author: "Kristina Chodorow",
   published_date: ISODate("2011-05-06"),
   pages: 68,
   language: "English"
}

or
To avoid mutable, growing arrays, store the publisher reference inside the book document:

{
   _id: "oreilly",
   name: "O'Reilly Media",
   founded: 1980,
   location: "CA"
}

{
   _id: 123456789,
   title: "MongoDB: The Definitive Guide",
   author: [ "Kristina Chodorow", "Mike Dirolf" ],
   published_date: ISODate("2010-09-24"),
   pages: 216,
   language: "English",
   publisher_id: "oreilly"
}

{
   _id: 234567890,
   title: "50 Tips and Tricks for MongoDB Developer",
   author: "Kristina Chodorow",
   published_date: ISODate("2011-05-06"),
   pages: 68,
   language: "English",
   publisher_id: "oreilly"
}

Model Tree Structures

Consider the following hierarchy of categories:


model-tree

Model Tree Structures with Parent References

The Parent References pattern stores each tree node in a document; in addition to the tree node, the document stores the id of the node’s parent.

db.categories.insert( { _id: "MongoDB", parent: "Databases" } )
db.categories.insert( { _id: "dbm", parent: "Databases" } )
db.categories.insert( { _id: "Databases", parent: "Programming" } )
db.categories.insert( { _id: "Languages", parent: "Programming" } )
db.categories.insert( { _id: "Programming", parent: "Books" } )
db.categories.insert( { _id: "Books", parent: null } )

Model Tree Structures with Child References

The Child References pattern stores each tree node in a document; in addition to the tree node, document stores in an array the id(s) of the node’s children.

db.categories.insert( { _id: "MongoDB", children: [] } )
db.categories.insert( { _id: "dbm", children: [] } )
db.categories.insert( { _id: "Databases", children: [ "MongoDB", "dbm" ] } )
db.categories.insert( { _id: "Languages", children: [] } )
db.categories.insert( { _id: "Programming", children: [ "Databases", "Languages" ] } )
db.categories.insert( { _id: "Books", children: [ "Programming" ] } )

Model Tree Structures with an Array of Ancestors

The Array of Ancestors pattern stores each tree node in a document; in addition to the tree node, document stores in an array the id(s) of the node’s ancestors or path.

db.categories.insert( { _id: "MongoDB", ancestors: [ "Books", "Programming", "Databases" ], parent: "Databases" } )
db.categories.insert( { _id: "dbm", ancestors: [ "Books", "Programming", "Databases" ], parent: "Databases" } )
db.categories.insert( { _id: "Databases", ancestors: [ "Books", "Programming" ], parent: "Programming" } )
db.categories.insert( { _id: "Languages", ancestors: [ "Books", "Programming" ], parent: "Programming" } )
db.categories.insert( { _id: "Programming", ancestors: [ "Books" ], parent: "Books" } )
db.categories.insert( { _id: "Books", ancestors: [ ], parent: null } )

Model Tree Structures with Materialized Paths

The Materialized Paths pattern stores each tree node in a document; in addition to the tree node, document stores as a string the id(s) of the node’s ancestors or path.

db.categories.insert( { _id: "Books", path: null } )
db.categories.insert( { _id: "Programming", path: ",Books," } )
db.categories.insert( { _id: "Databases", path: ",Books,Programming," } )
db.categories.insert( { _id: "Languages", path: ",Books,Programming," } )
db.categories.insert( { _id: "MongoDB", path: ",Books,Programming,Databases," } )
db.categories.insert( { _id: "dbm", path: ",Books,Programming,Databases," } )

Model Tree Structures with Nested Sets

The Nested Sets pattern identifies each node in the tree as stops in a round-trip traversal of the tree. The application visits each node in the tree twice; first during the initial trip, and second during the return trip. The Nested Sets pattern stores each tree node in a document; in addition to the tree node, document stores the id of node’s parent, the node’s initial stop in the left field, and its return stop in the right field.

tree-set
db.categories.insert( { _id: "Books", parent: 0, left: 1, right: 12 } )
db.categories.insert( { _id: "Programming", parent: "Books", left: 2, right: 11 } )
db.categories.insert( { _id: "Languages", parent: "Programming", left: 3, right: 4 } )
db.categories.insert( { _id: "Databases", parent: "Programming", left: 5, right: 10 } )
db.categories.insert( { _id: "MongoDB", parent: "Databases", left: 6, right: 7 } )
db.categories.insert( { _id: "dbm", parent: "Databases", left: 8, right: 9 } )
  • You can query to retrieve the descendants of a node(a subtree):
var databaseCategory = db.categories.findOne( { _id: "Databases" } );
db.categories.find( { left: { $gt: databaseCategory.left }, right: { $lt: databaseCategory.right } } );

Database References

MongoDB applications use one of two methods for relating documents:

Manual references

where you save the _id field of one document in another document as a reference.

DBRefs

are references from one document to another using the value of the first document’s _id field, collection name, and, optionally, its database name.

format
{ "$ref" : <value>, "$id" : <value>, "$db" : <value> }

  • $ref
    The $ref field holds the name of the collection where the referenced document resides.

  • $id
    The $id field contains the value of the _id field in the referenced document.

  • $db
    Optional. Contains the name of the database where the referenced document resides.

The DBRef in this example points to a document in the creators collection of the users database that has ObjectId("5126bc054aed4daf9e2ab772") in its _id field.

{
  "_id" : ObjectId("5126bbf64aed4daf9e2ab771"),
  // .. application fields
  "creator" : {
                  "$ref" : "creators",
                  "$id" : ObjectId("5126bc054aed4daf9e2ab772"),
                  "$db" : "users"
               }
}

Reference

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