db.collection.aggregate()
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Definition
db.collection.aggregate(pipeline, options)Important
mongosh Method
This page documents a
mongoshmethod. This is not the documentation for database commands or language-specific drivers, such as Node.js.For the database command, see the
aggregatecommand.For MongoDB API drivers, refer to the language-specific MongoDB driver documentation.
For the legacy
mongoshell documentation, refer to the documentation for the corresponding MongoDB Server release:Calculates aggregate values for the data in a collection or a view.
Parameter Type Description pipelinearray A sequence of data aggregation operations or stages. See the aggregation pipeline operators for details.
The method can still accept the pipeline stages as separate arguments instead of as elements in an array; however, if you do not specify thepipelineas an array, you cannot specify theoptionsparameter.optionsdocument Optional. Additional options that aggregate()passes to theaggregatecommand. Available only if you specify thepipelineas an array.The
optionsdocument can contain the following fields and values:Changed in version 5.0.
Field Type Description explainboolean Optional. Specifies to return the information on the processing of the pipeline. See Return Information on Aggregation Pipeline Operation for an example.
Not available in multi-document transactions.allowDiskUseboolean Optional. Enables writing to temporary files. When set to true, aggregation operations can write data to the_tmpsubdirectory in thedbPathdirectory. See Interaction withallowDiskUseByDefaultfor an example.
Starting in MongoDB 4.2, the profiler log messages and diagnostic log messages includes ausedDiskindicator if any aggregation stage wrote data to temporary files due to memory restrictions.cursordocument Optional. Specifies the initial batch size for the cursor. The value of the cursorfield is a document with the fieldbatchSize. See Specify an Initial Batch Size for syntax and example.maxTimeMSnon-negative integer Optional. Specifies a time limit in milliseconds for processing operations on a cursor. If you do not specify a value for maxTimeMS, operations will not time out. A value of 0explicitly specifies the default unbounded behavior.
MongoDB terminates operations that exceed their allotted time limit using the same mechanism asdb.killOp(). MongoDB only terminates an operation at one of its designated interrupt points.bypassDocumentValidationboolean Optional. Applicable only if you specify the $outor$mergeaggregation stages.
Enablesdb.collection.aggregate()to bypass document validation during the operation. This lets you insert documents that do not meet the validation requirements.readConcerndocument Optional. Specifies the read concern.
Starting in MongoDB 3.6, the readConcern option has the following syntax:readConcern: { level: <value> }
Possible read concern levels are:"local". This is the default read concern level for read operations against the primary and secondaries."available". Available for read operations against the primary and secondaries."available"behaves the same as"local"against the primary and non-sharded secondaries. The query returns the instance's most recent data."majority". Available for replica sets that use WiredTiger storage engine."linearizable". Available for read operations on theprimaryonly.
Starting in MongoDB 4.2, the$outstage cannot be used in conjunction with read concern"linearizable". That is, if you specify"linearizable"read concern fordb.collection.aggregate(), you cannot include the$outstage in the pipeline.
The$mergestage cannot be used in conjunction with read concern"linearizable". That is, if you specify"linearizable"read concern fordb.collection.aggregate(), you cannot include the$mergestage in the pipeline.collation document Optional.
Specifies the collation to use for the operation.
Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.
The collation option has the following syntax:collation: { locale: <string>, caseLevel: <boolean>, caseFirst: <string>, strength: <int>, numericOrdering: <boolean>, alternate: <string>, maxVariable: <string>, backwards: <boolean> }When specifying collation, the
localefield is mandatory; all other collation fields are optional. For descriptions of the fields, see Collation Document.If the collation is unspecified but the collection has a default collation (see
db.createCollection()), the operation uses the collation specified for the collection.If no collation is specified for the collection or for the operations, MongoDB uses the simple binary comparison used in prior versions for string comparisons.
You cannot specify multiple collations for an operation. For example, you cannot specify different collations per field, or if performing a find with a sort, you cannot use one collation for the find and another for the sort.
hintstring or document Optional. The index to use for the aggregation. The index is on the initial collection/view against which the aggregation is run.
Specify the index either by the index name or by the index specification document.Note
commentstring Optional. Users can specify an arbitrary string to help trace the operation through the database profiler, currentOp, and logs. writeConcerndocument Optional. A document that expresses the write concern to use with the $outor$mergestage.
Omit to use the default write concern with the$outor$mergestage.letdocument Optional.
Specifies a document with a list of variables. This allows you to improve command readability by separating the variables from the query text.
The document syntax is:{ <variable_name_1>: <expression_1>, ..., <variable_name_n>: <expression_n> }The variable is set to the value returned by the expression, and cannot be changed afterwards.
To access the value of a variable in the command, use the double dollar sign prefix (
$$) together with your variable name in the form$$<variable_name>. For example:$$targetTotal.Note
For a complete example using
letand variables, see Use Variables inlet.New in version 5.0.
Returns: This method returns: - A cursor for the documents produced by the final stage of the aggregation pipeline.
- If the pipeline includes the
explainoption, the query returns a document that provides details on the processing of the aggregation operation. - If the pipeline includes the
$outor$mergeoperators, the query returns an empty cursor.
Behavior
Error Handling
If an error occurs, the aggregate() helper throws an exception.
Cursor Behavior
In mongosh, if the cursor returned from the db.collection.aggregate() is not assigned to a variable using the var keyword, then mongosh automatically iterates the cursor up to 20 times. See Iterate a Cursor in mongosh for handling cursors in mongosh.
Cursors returned from aggregation only supports cursor methods that operate on evaluated cursors (i.e. cursors whose first batch has been retrieved), such as the following methods:
Tip
See also:
For more information, see Aggregation Pipeline, Aggregation Reference, Aggregation Pipeline Limits, and aggregate.
Sessions
For cursors created inside a session, you cannot call getMore outside the session.
Similarly, for cursors created outside of a session, you cannot call getMore inside a session.
Session Idle Timeout
MongoDB drivers and mongosh associate all operations with a server session, with the exception of unacknowledged write operations. For operations not explicitly associated with a session (i.e. using Mongo.startSession()), MongoDB drivers and mongosh create an implicit session and associate it with the operation.
If a session is idle for longer than 30 minutes, the MongoDB server marks that session as expired and may close it at any time. When the MongoDB server closes the session, it also kills any in-progress operations and open cursors associated with the session. This includes cursors configured with noCursorTimeout() or a maxTimeMS() greater than 30 minutes.
For operations that return a cursor, if the cursor may be idle for longer than 30 minutes, issue the operation within an explicit session using Mongo.startSession() and periodically refresh the session using the refreshSessions command. See Session Idle Timeout for more information.
Transactions
db.collection.aggregate() can be used inside multi-document transactions.
However, the following stages are not allowed within transactions:
You also cannot specify the explain option.
-
For cursors created outside of a transaction, you cannot call
getMoreinside the transaction. -
For cursors created in a transaction, you cannot call
getMoreoutside the transaction.
Important
In most cases, multi-document transaction incurs a greater performance cost over single document writes, and the availability of multi-document transactions should not be a replacement for effective schema design. For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases. That is, for many scenarios, modeling your data appropriately will minimize the need for multi-document transactions.
For additional transactions usage considerations (such as runtime limit and oplog size limit), see also Production Considerations.
Client Disconnection
For db.collection.aggregate() operation that do not include the $out or $merge stages:
Starting in MongoDB 4.2, if the client that issued db.collection.aggregate() disconnects before the operation completes, MongoDB marks db.collection.aggregate() for termination using killOp.
Examples
The following examples use the collection orders that contains the following documents:
{ _id: 1, cust_id: "abc1", ord_date: ISODate("2012-11-02T17:04:11.102Z"), status: "A", amount: 50 }
{ _id: 2, cust_id: "xyz1", ord_date: ISODate("2013-10-01T17:04:11.102Z"), status: "A", amount: 100 }
{ _id: 3, cust_id: "xyz1", ord_date: ISODate("2013-10-12T17:04:11.102Z"), status: "D", amount: 25 }
{ _id: 4, cust_id: "xyz1", ord_date: ISODate("2013-10-11T17:04:11.102Z"), status: "D", amount: 125 }
{ _id: 5, cust_id: "abc1", ord_date: ISODate("2013-11-12T17:04:11.102Z"), status: "A", amount: 25 }
Group by and Calculate a Sum
The following aggregation operation selects documents with status equal to "A", groups the matching documents by the cust_id field and calculates the total for each cust_id field from the sum of the amount field, and sorts the results by the total field in descending order:
db.orders.aggregate([ { $match: { status: "A" } }, { $group: { _id: "$cust_id", total: { $sum: "$amount" } } }, { $sort: { total: -1 } } ])
The operation returns a cursor with the following documents:
{ "_id" : "xyz1", "total" : 100 }
{ "_id" : "abc1", "total" : 75 }
mongosh iterates the returned cursor automatically to print the results. See Iterate a Cursor in mongosh for handling cursors manually in mongosh.
Return Information on Aggregation Pipeline Operation
The following example uses db.collection.explain() to view detailed information regarding the execution plan of the aggregation pipeline.
db.orders.explain().aggregate([ { $match: { status: "A" } }, { $group: { _id: "$cust_id", total: { $sum: "$amount" } } }, { $sort: { total: -1 } } ])
The operation returns a document that details the processing of the aggregation pipeline. For example, the document may show, among other details, which index, if any, the operation used. [1] If the orders collection is a sharded collection, the document would also show the division of labor between the shards and the merge operation, and for targeted queries, the targeted shards.
Note
The intended readers of the explain output document are humans, and not machines, and the output format is subject to change between releases.
You can view more verbose explain output by passing the executionStats or allPlansExecution explain modes to the db.collection.explain() method.
| [1] | Index Filters can affect the choice of index used. See Index Filters for details. |
Interaction with allowDiskUseByDefault
Starting in MongoDB 6.0, pipeline stages that require more than 100 megabytes of memory to execute write temporary files to disk by default. In earlier verisons of MongoDB, you must pass { allowDiskUse: true } to individual find and aggregate commands to enable this behavior.
Individual find and aggregate commands may override the allowDiskUseByDefault parameter by either:
-
Using
{ allowDiskUse: true }to allow writing temporary files out to disk whenallowDiskUseByDefaultis set tofalse -
Using
{ allowDiskUse: false }to prohibit writing temporary files out to disk whenallowDiskUseByDefaultis set totrue
Starting in MongoDB 4.2, the profiler log messages and diagnostic log messages includes a usedDisk indicator if any aggregation stage wrote data to temporary files due to memory restrictions.
Tip
See also:
Specify an Initial Batch Size
To specify an initial batch size for the cursor, use the following syntax for the cursor option:
cursor: { batchSize: <int> }
For example, the following aggregation operation specifies the initial batch size of 0 for the cursor:
db.orders.aggregate( [ { $match: { status: "A" } }, { $group: { _id: "$cust_id", total: { $sum: "$amount" } } }, { $sort: { total: -1 } }, { $limit: 2 } ], { cursor: { batchSize: 0 } } )
A batchSize of 0 means an empty first batch and is useful for quickly returning a cursor or failure message without doing significant server-side work. Specify subsequent batch sizes for future getMore operations with batchSize().
mongosh iterates the returned cursor automatically to print the results. See Iterate a Cursor in mongosh for handling cursors manually in mongosh.
Specify a Collation
Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.
A collection myColl has the following documents:
{ _id: 1, category: "café", status: "A" }
{ _id: 2, category: "cafe", status: "a" }
{ _id: 3, category: "cafE", status: "a" }
The following aggregation operation includes the collation option:
db.myColl.aggregate( [ { $match: { status: "A" } }, { $group: { _id: "$category", count: { $sum: 1 } } } ], { collation: { locale: "fr", strength: 1 } } );
Note
If performing an aggregation that involves multiple views, such as with $lookup or $graphLookup, the views must have the same collation.
For descriptions on the collation fields, see Collation Document.
Hint an Index
Create a collection foodColl with the following documents:
db.foodColl.insertMany( [ { _id: 1, category: "cake", type: "chocolate", qty: 10 }, { _id: 2, category: "cake", type: "ice cream", qty: 25 }, { _id: 3, category: "pie", type: "boston cream", qty: 20 }, { _id: 4, category: "pie", type: "blueberry", qty: 15 } ] )
Create the following indexes:
db.foodColl.createIndex( { qty: 1, type: 1 } ); db.foodColl.createIndex( { qty: 1, category: 1 } );
The following aggregation operation includes the hint option to force the usage of the specified index:
db.foodColl.aggregate( [ { $sort: { qty: 1 }}, { $match: { category: "cake", qty: 10 } }, { $sort: { type: -1 } } ], { hint: { qty: 1, category: 1 } } )
Override readConcern
Use the readConcern option to specify the read concern for the operation.
You cannot use the $out or the $merge stage in conjunction with read concern "linearizable". That is, if you specify "linearizable" read concern for db.collection.aggregate(), you cannot include either stages in the pipeline.
The following operation on a replica set specifies a Read Concern of "majority" to read the most recent copy of the data confirmed as having been written to a majority of the nodes.
Note
-
To ensure that a single thread can read its own writes, use
"majority"read concern and"majority"write concern against the primary of the replica set. -
Starting in MongoDB 4.2, you can specify read concern level
"majority"for an aggregation that includes an$outstage. -
Regardless of the read concern level, the most recent data on a node may not reflect the most recent version of the data in the system.
db.restaurants.aggregate( [ { $match: { rating: { $lt: 5 } } } ], { readConcern: { level: "majority" } } )
Specify a Comment
A collection named movies contains documents formatted as such:
{
"_id" : ObjectId("599b3b54b8ffff5d1cd323d8"),
"title" : "Jaws",
"year" : 1975,
"imdb" : "tt0073195"
}
The following aggregation operation finds movies created in 1995 and includes the comment option to provide tracking information in the logs, the db.system.profile collection, and db.currentOp.
db.movies.aggregate( [ { $match: { year : 1995 } } ], { comment : "match_all_movies_from_1995" } ).pretty()
On a system with profiling enabled, you can then query the system.profile collection to see all recent similar aggregations, as shown below:
db.system.profile.find( { "command.aggregate": "movies", "command.comment" : "match_all_movies_from_1995" } ).sort( { ts : -1 } ).pretty()
This will return a set of profiler results in the following format:
{
"op" : "command",
"ns" : "video.movies",
"command" : {
"aggregate" : "movies",
"pipeline" : [
{
"$match" : {
"year" : 1995
}
}
],
"comment" : "match_all_movies_from_1995",
"cursor" : {
},
"$db" : "video"
},
...
}
An application can encode any arbitrary information in the comment in order to more easily trace or identify specific operations through the system. For instance, an application might attach a string comment incorporating its process ID, thread ID, client hostname, and the user who issued the command.
Use Variables in let
New in version 5.0.
To define variables that you can access elsewhere in the command, use the let option.
Note
Create a collection cakeSales containing sales for cake flavors:
db.cakeSales.insertMany( [ { _id: 1, flavor: "chocolate", salesTotal: 1580 }, { _id: 2, flavor: "strawberry", salesTotal: 4350 }, { _id: 3, flavor: "cherry", salesTotal: 2150 } ] )
The following example:
-
retrieves the cake that has a
salesTotalgreater than 3000, which is the cake with an_idof 2 -
defines a
targetTotalvariable inlet, which is referenced in$gtas$$targetTotal
db.cakeSales.aggregate( [ { $match: { $expr: { $gt: [ "$salesTotal", "$$targetTotal" ] } } } ], { let: { targetTotal: 3000 } } )