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)
Embedded Data(Denormalized Data Models)
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 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.
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"
}
}
