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Retrieve documents in MongoDB collection
documents = find(conn,collection)
documents = find(conn,collection,Name,Value)
returns all documents in a collection by using the MongoDB® connection.documents
= find(conn
,collection
)
specifies additional options using one or more name-value pair arguments. For
example, documents
= find(conn
,collection
,Name,Value
)'Limit',10
limits the number of documents returned to
10.
Connect to MongoDB, retrieve all documents in a collection, and import them into MATLAB®. Here, each document in the collection represents an employee.
Create a MongoDB connection to the database mongotest
. Here, the database server dbtb01
hosts this database using port number 27017
.
server = "dbtb01"; port = 27017; dbname = "mongotest"; conn = mongo(server,port,dbname)
conn = mongo with properties: Database: 'mongotest' UserName: '' Server: {'dbtb01'} Port: 27017 CollectionNames: {'airlinesmall', 'employee', 'largedata' ... and 3 more} TotalDocuments: 23485919
conn
is the
mongo
object that contains the MongoDB connection. The object properties contain information about the connection and the
database.
The database name is mongotest
.
The user name is blank.
The database server is dbtb01
.
The port number is 27017
.
This database contains six document collections. The first three collection names are
airlinesmall
, employee
, and
largedata
.
This database contains 23,485,919 documents.
Verify the MongoDB connection.
isopen(conn)
ans = logical 1
The database connection is successful because the isopen
function returns 1
. Otherwise, the database connection is closed.
Specify the employee
collection for document retrieval. Retrieve all
documents in the collection by using the MongoDB connection. documents
is a structure array.
collection = "employee";
documents = find(conn,collection);
Display the first document in the collection. Each document is a structure with these fields.
Field | Description | Data Type |
---|---|---|
x_id | Unique identifier | Structure |
department | Department name | Character vector |
employee | Employee identifier | Double |
salary | Employee salary | Double |
documents(1)
ans = struct with fields: x_id: [1×1 struct] department: 'Sales' employee: 1 salary: 60000
Close the MongoDB connection.
close(conn)
Connect to MongoDB, retrieve all documents in a MongoDB query on a collection in the database, and import them into MATLAB. Here, each document in the collection represents an employee.
Create a MongoDB connection to the database mongotest
. Here, the database server dbtb01
hosts this database using port number 27017
.
server = "dbtb01"; port = 27017; dbname = "mongotest"; conn = mongo(server,port,dbname)
conn = mongo with properties: Database: 'mongotest' UserName: '' Server: {'dbtb01'} Port: 27017 CollectionNames: {'airlinesmall', 'employee', 'largedata' ... and 3 more} TotalDocuments: 23485919
conn
is the
mongo
object that contains the MongoDB connection. The object properties contain information about the connection and the
database.
The database name is mongotest
.
The user name is blank.
The database server is dbtb01
.
The port number is 27017
.
This database contains six document collections. The first three collection names are
airlinesmall
, employee
, and
largedata
.
This database contains 23,485,919 documents.
Verify the MongoDB connection.
isopen(conn)
ans = logical 1
The database connection is successful because the isopen
function returns 1
. Otherwise, the database connection is closed.
Specify the employee
collection for document retrieval.
Create the MongoDB query as a character vector that contains a JSON-style string.
This query retrieves all employees in the Sales department.
collection = "employee"; mongoquery = '{"department":"Sales"}';
Retrieve all documents in the MongoDB query on the employee
collection by using
the MongoDB connection. documents
is a structure array
that contains a structure for each document returned by the query.
documents = find(conn,collection,'Query',mongoquery);
Close the MongoDB connection.
close(conn)
Connect to MongoDB and retrieve documents in a MongoDB query on a collection in the database. Then, sort the results by a field in the documents. Here, each document in the collection represents an employee.
Create a MongoDB connection to the database mongotest
. Here, the database server dbtb01
hosts this database using port number 27017
.
server = "dbtb01"; port = 27017; dbname = "mongotest"; conn = mongo(server,port,dbname)
conn = mongo with properties: Database: 'mongotest' UserName: '' Server: {'dbtb01'} Port: 27017 CollectionNames: {'airlinesmall', 'employee', 'largedata' ... and 3 more} TotalDocuments: 23485919
conn
is the
mongo
object that contains the MongoDB connection. The object properties contain information about the connection and the
database.
The database name is mongotest
.
The user name is blank.
The database server is dbtb01
.
The port number is 27017
.
This database contains six document collections. The first three collection names are
airlinesmall
, employee
, and
largedata
.
This database contains 23,485,919 documents.
Verify the MongoDB connection.
isopen(conn)
ans = logical 1
The database connection is successful because the isopen
function returns 1
. Otherwise, the database connection is closed.
Specify the employee
collection for document retrieval.
Create the MongoDB query as a character vector that contains a JSON-style string.
This query retrieves all employees in the Sales department.
collection = "employee"; mongoquery = '{"department":"Sales"}';
Create the sort query as a character vector that contains a JSON-style
string. Sort the documents by the salary
field.
sortquery = '{"salary":1.0}';
Retrieve all documents in the MongoDB query on the employee
collection by using
the MongoDB connection, and sort the documents.
documents
is a structure array that contains a
structure for each document returned by the query. The documents are sorted
by salary in increasing order.
documents = find(conn,collection,'Query',mongoquery,'Sort',sortquery);
Display the sorted salaries for the first two employees.
documents(1:2).salary
ans = 60000 ans = 64440
Close the MongoDB connection.
close(conn)
Connect to MongoDB and retrieve all documents in a collection. Specify the fields to retrieve for each document. Import the documents into MATLAB. Here, each document in the collection represents an employee.
Create a MongoDB connection to the database mongotest
. Here, the database server dbtb01
hosts this database using port number 27017
.
server = "dbtb01"; port = 27017; dbname = "mongotest"; conn = mongo(server,port,dbname)
conn = mongo with properties: Database: 'mongotest' UserName: '' Server: {'dbtb01'} Port: 27017 CollectionNames: {'airlinesmall', 'employee', 'largedata' ... and 3 more} TotalDocuments: 23485919
conn
is the
mongo
object that contains the MongoDB connection. The object properties contain information about the connection and the
database.
The database name is mongotest
.
The user name is blank.
The database server is dbtb01
.
The port number is 27017
.
This database contains six document collections. The first three collection names are
airlinesmall
, employee
, and
largedata
.
This database contains 23,485,919 documents.
Verify the MongoDB connection.
isopen(conn)
ans = logical 1
The database connection is successful because the isopen
function returns 1
. Otherwise, the database connection is closed.
Specify the employee
collection for document retrieval.
Specify the fields to retrieve for each document by using a character vector
that contains a JSON-style string. Here, return the
department
and salary
fields.
collection = "employee"; fields = '{"department":1.0,"salary":1.0}';
Retrieve all documents in the collection. Use the name-value pair argument
'Projection'
to retrieve the specified fields for
each document. documents
is a structure array.
documents = find(conn,collection,'Projection',fields);
Display the first document in the results. In addition to the unique
identifier for the document, the document contains only the specified
fields, department
and salary
.
documents(1)
ans = struct with fields: x_id: [1×1 struct] department: 'Sales' salary: 60000
Close the MongoDB connection.
close(conn)
Connect to MongoDB and retrieve a specific number of documents in a collection in the database. Return documents from a specific position in the results using an offset value. Import the documents into MATLAB. Here, each document in the collection represents an employee.
Create a MongoDB connection to the database mongotest
. Here, the database server dbtb01
hosts this database using port number 27017
.
server = "dbtb01"; port = 27017; dbname = "mongotest"; conn = mongo(server,port,dbname)
conn = mongo with properties: Database: 'mongotest' UserName: '' Server: {'dbtb01'} Port: 27017 CollectionNames: {'airlinesmall', 'employee', 'largedata' ... and 3 more} TotalDocuments: 23485919
conn
is the
mongo
object that contains the MongoDB connection. The object properties contain information about the connection and the
database.
The database name is mongotest
.
The user name is blank.
The database server is dbtb01
.
The port number is 27017
.
This database contains six document collections. The first three collection names are
airlinesmall
, employee
, and
largedata
.
This database contains 23,485,919 documents.
Verify the MongoDB connection.
isopen(conn)
ans = logical 1
The database connection is successful because the isopen
function returns 1
. Otherwise, the database connection is closed.
Specify the employee
collection for document
retrieval.
collection = "employee";
Use the name-value pair argument 'Skip'
to skip the
first five documents in the collection. Then, use the name-value pair
argument 'Limit'
to return the next 10 documents in the
collection. documents
is structure array that contains 10
documents.
documents = find(conn,collection,'Skip',5,'Limit',10);
Close the MongoDB connection.
close(conn)
conn
— MongoDB connectionmongo
objectMongoDB connection, specified as a mongo
object.
collection
— Collection nameCollection name, specified as a string scalar.
Example: "taxidata"
Data Types: string
Specify optional
comma-separated pairs of Name,Value
arguments. Name
is
the argument name and Value
is the corresponding value.
Name
must appear inside quotes. You can specify several name and value
pair arguments in any order as Name1,Value1,...,NameN,ValueN
.
'Skip',5,'Limit',10
skips the first five documents in a
collection and returns the next 10 documents.'Query'
— MongoDB query MongoDB query, specified as the comma-separated pair consisting of
'Query'
and a string scalar or character vector.
Specify a JSON-style string to query the database.
Example: 'Query','{"department":"Sales"}'
queries
the database for documents where the department
field
is equal to Sales
.
Example: 'Query','{salary: {$gt: 90000}}'
queries
the database for documents where the value of the
salary
field is greater than
90000
.
Example: 'Query','{"_id":{$oid:"593fec95b78dc311e01e9204"}}'
queries the database for the document that has the identifier
593fec95b78dc311e01e9204
.
Data Types: char
| string
'Projection'
— FieldsFields to retrieve in each document, specified as the comma-separated
pair consisting of 'Projection'
and a string scalar
or character vector. Specify a JSON-style string to describe the
fields.
Example: 'Projection','{"department":1.0,"salary":1.0}'
returns the department
and salary
fields.
Data Types: char
| string
'Sort'
— Sort fieldSort field for documents, specified as the comma-separated pair
consisting of 'Sort'
and a string scalar or character
vector. Specify a JSON-style string to describe the sort field.
Example: 'Sort','{"department":1.0}'
sorts the
returned documents by the department
field.
Data Types: char
| string
'Skip'
— OffsetOffset from the beginning of the returned documents, specified as the
comma-separated pair consisting of 'Skip'
and a
numeric scalar.
Example: 'Skip',5
skips the first five returned
documents.
Data Types: double
'Limit'
— Number of documents to returnNumber of documents to return, specified as the comma-separated pair
consisting of 'Limit'
and a numeric scalar.
Example: 'Limit',10
returns 10
documents.
Data Types: double
documents
— DocumentsDocuments in a MongoDB collection or query on a collection, returned as a structure, structure array, or cell array of structures.
Each JSON-style document is represented as a structure. The
find
function returns a:
Structure for one document
Structure array for multiple documents containing the same fields
Cell array of structures for multiple documents containing different fields
The find
function estimates memory requirements when
retrieving many documents using the Java® heap. To avoid out-of-memory issues, the function automatically
limits the number of returned documents in a single execution.
When an issue occurs, the function throws a warning message, for example,
Warning: Available memory is less than Total memory required.
Limiting the RESULTSET from 15837001 to 59248. Use Skip and Limit to
retrieve resultset in batches
.
To retrieve many documents, retrieve them in batches. For an example, see Import Large Data from MongoDB.
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