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Documents¶
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MongoDB stores data records as BSON documents. BSON is a binary representation of JSON documents, though it contains more data types than JSON. For the BSON spec, see bsonspec.org. See also BSON Types.
Document Structure¶
MongoDB documents are composed of field-and-value pairs and have the following structure:
{
field1: value1,
field2: value2,
field3: value3,
...
fieldN: valueN
}
The value of a field can be any of the BSON data types, including other documents, arrays, and arrays of documents. For example, the following document contains values of varying types:
var mydoc = {
_id: ObjectId("5099803df3f4948bd2f98391"),
name: { first: "Alan", last: "Turing" },
birth: new Date('Jun 23, 1912'),
death: new Date('Jun 07, 1954'),
contribs: [ "Turing machine", "Turing test", "Turingery" ],
views : NumberLong(1250000)
}
The above fields have the following data types:
- _id holds an ObjectId.
- name holds an embedded document that contains the fields first and last.
- birth and death hold values of the Date type.
- contribs holds an array of strings.
- views holds a value of the NumberLong type.
Field Names¶
Field names are strings.
Documents have the following restrictions on field names:
- The field name _id is reserved for use as a primary key; its value must be unique in the collection, is immutable, and may be of any type other than an array.
- The field names cannot start with the dollar sign ($) character.
- The field names cannot contain the dot (.) character.
- The field names cannot contain the null character.
BSON documents may have more than one field with the same name. Most MongoDB interfaces, however, represent MongoDB with a structure (e.g. a hash table) that does not support duplicate field names. If you need to manipulate documents that have more than one field with the same name, see the driver documentation for your driver.
Some documents created by internal MongoDB processes may have duplicate fields, but no MongoDB process will ever add duplicate fields to an existing user document.
Field Value Limit¶
For indexed collections, the values for the indexed fields have a Maximum Index Key Length limit. See Maximum Index Key Length for details.
Dot Notation¶
MongoDB uses the dot notation to access the elements of an array and to access the fields of an embedded document.
Arrays¶
To specify or access an element of an array by the zero-based index position, concatenate the array name with the dot (.) and zero-based index position, and enclose in quotes:
"<array>.<index>"
For example, given the following field in a document:
{
...
contribs: [ "Turing machine", "Turing test", "Turingery" ],
...
}
To specify the third element in the contribs array, use the dot notation "contribs.2".
Embedded Documents¶
To specify or access a field of an embedded document with dot notation, concatenate the embedded document name with the dot (.) and the field name, and enclose in quotes:
"<embedded document>.<field>"
For example, given the following field in a document:
{
...
name: { first: "Alan", last: "Turing" },
...
}
To specify the field named last in the name field, use the dot notation "name.last".
See also
Embedded Documents for dot notation examples with embedded documents.
Document Limitations¶
Documents have the following attributes:
Document Size Limit¶
The maximum BSON document size is 16 megabytes.
The maximum document size helps ensure that a single document cannot use excessive amount of RAM or, during transmission, excessive amount of bandwidth. To store documents larger than the maximum size, MongoDB provides the GridFS API. See mongofiles and the documentation for your driver for more information about GridFS.
Document Field Order¶
MongoDB preserves the order of the document fields following write operations except for the following cases:
- The _id field is always the first field in the document.
- Updates that include renaming of field names may result in the reordering of fields in the document.
Changed in version 2.6: Starting in version 2.6, MongoDB actively attempts to preserve the field order in a document. Before version 2.6, MongoDB did not actively preserve the order of the fields in a document.
The _id Field¶
The _id field has the following behavior and constraints:
By default, MongoDB creates a unique index on the _id field during the creation of a collection.
The _id field is always the first field in the documents. If the server receives a document that does not have the _id field first, then the server will move the field to the beginning.
The _id field may contain values of any BSON data type, other than an array.
Warning
To ensure functioning replication, do not store values that are of the BSON regular expression type in the _id field.
The following are common options for storing values for _id:
Use an ObjectId.
Use a natural unique identifier, if available. This saves space and avoids an additional index.
Generate an auto-incrementing number. See Create an Auto-Incrementing Sequence Field.
Generate a UUID in your application code. For a more efficient storage of the UUID values in the collection and in the _id index, store the UUID as a value of the BSON BinData type.
Index keys that are of the BinData type are more efficiently stored in the index if:
- the binary subtype value is in the range of 0-7 or 128-135, and
- the length of the byte array is: 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, or 32.
Use your driver’s BSON UUID facility to generate UUIDs. Be aware that driver implementations may implement UUID serialization and deserialization logic differently, which may not be fully compatible with other drivers. See your driver documentation for information concerning UUID interoperability.
Note
Most MongoDB driver clients will include the _id field and generate an ObjectId before sending the insert operation to MongoDB; however, if the client sends a document without an _id field, the mongod will add the _id field and generate the ObjectId.
Other Uses of the Document Structure¶
In addition to defining data records, MongoDB uses the document structure throughout, including but not limited to:
Query filters or specifications. Query filter documents specify the conditions that determine which records to select for read, update, and delete operations.
You can use <field>:<value> expressions to specify the equality condition and query operator expressions.
{ <field1>: <value1>, <field2>: { <operator>: <value> }, ... }
For examples, see Query filters or specifications.
Update specifications. Update specifications documents use update operators to specify the data modifications to perform on specific fields during an db.collection.update() operation.
{ <operator1>: { <field1>: <value1>, ... }, <operator2>: { <field2>: <value2>, ... }, ... }
Index specifications. Index specifications document define the field to index and the index type:
{ <field1>: <type1>, <field2>: <type2>, ... }