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MongoDB Manual

Change Streams

On this page

  • Availability
  • Connect
  • Watch a Collection, Database, or Deployment
  • Change Stream Performance Considerations
  • Open A Change Stream
  • Modify Change Stream Output
  • Lookup Full Document for Update Operations
  • Resume a Change Stream
  • Use Cases
  • Access Control
  • Event Notification
  • Collation
  • Change Streams and Orphan Documents
  • Change Streams with Document Pre- and Post-Images

Change streams allow applications to access real-time data changes without the prior complexity and risk of manually tailing the oplog. Applications can use change streams to subscribe to all data changes on a single collection, a database, or an entire deployment, and immediately react to them. Because change streams use the aggregation framework, applications can also filter for specific changes or transform the notifications at will.

Starting in MongoDB 5.1, change streams are optimized, providing more efficient resource utilization and faster execution of some aggregation pipeline stages.

Availability

Change streams are available for replica sets and sharded clusters:

Stable API Support

Change streams are included in Stable API V1. However, the showExpandedEvents option is not included in Stable API V1.

Connect

Connections for a change stream can either use DNS seed lists with the +srv connection option or by listing the servers individually in the connection string.

If the driver loses the connection to a change stream or the connection goes down, it attempts to reestablish a connection to the change stream through another node in the cluster that has a matching read preference. If the driver cannot find a node with the correct read preference, it throws an exception.

For more information, see Connection String URI Format.

Watch a Collection, Database, or Deployment

You can open change streams against:

Target
Description
A collection

You can open a change stream cursor for a single collection (except system collections, or any collections in the admin, local, and config databases).

The examples on this page use the MongoDB drivers to open and work with a change stream cursor for a single collection. See also the mongosh method db.collection.watch().

A database

You can open a change stream cursor for a single database (excluding admin, local, and config database) to watch for changes to all its non-system collections.

For the MongoDB driver method, refer to your driver documentation. See also the mongosh method db.watch().

A deployment

You can open a change stream cursor for a deployment (either a replica set or a sharded cluster) to watch for changes to all non-system collections across all databases except for admin, local, and config.

For the MongoDB driver method, refer to your driver documentation. See also the mongosh method Mongo.watch().

Note

Change Stream Examples

The examples on this page use the MongoDB drivers to illustrate how to open a change stream cursor for a collection and work with the change stream cursor.

Change Stream Performance Considerations

If the amount of active change streams opened against a database exceeds the connection pool size, you may experience notification latency. Each change stream uses a connection and a getMore operation on the change stream for the period of time that it waits for the next event. To avoid any latency issues, you should ensure that the pool size is greater than the number of opened change streams. For details see the maxPoolSize setting.

Sharded Cluster Considerations

When a change stream is opened on a sharded cluster:

  • The mongos creates individual change streams on each shard. This behavior occurs regardless of whether the change stream targets a particular shard key range.

  • When the mongos receives change stream results, it sorts and filters those results. If needed, the mongos also performs a fullDocument lookup.

For best performance, limit the use of $lookup queries in change streams.

Open A Change Stream

To open a change stream:

  • For a replica set, you can issue the open change stream operation from any of the data-bearing members.

  • For a sharded cluster, you must issue the open change stream operation from the mongos.

The following example opens a change stream for a collection and iterates over the cursor to retrieve the change stream documents. [1]

➤ Use the Select your language drop-down menu in the upper-right to set the language of the examples on this page.

The C examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

mongoc_collection_t *collection;
bson_t *pipeline = bson_new ();
bson_t opts = BSON_INITIALIZER;
mongoc_change_stream_t *stream;
const bson_t *change;
const bson_t *resume_token;
bson_error_t error;
collection = mongoc_database_get_collection (db, "inventory");
stream = mongoc_collection_watch (collection, pipeline, NULL /* opts */);
mongoc_change_stream_next (stream, &change);
if (mongoc_change_stream_error_document (stream, &error, NULL)) {
   MONGOC_ERROR ("%s\n", error.message);
}
mongoc_change_stream_destroy (stream);

The C# examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

var cursor = inventory.Watch();
while (cursor.MoveNext() && cursor.Current.Count() == 0) { } // keep calling MoveNext until we've read the first batch
var next = cursor.Current.First();
cursor.Dispose();

The Go examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

cs, err := coll.Watch(ctx, mongo.Pipeline{})
assert.NoError(t, err)
defer cs.Close(ctx)
ok := cs.Next(ctx)
next := cs.Current

The Java examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

MongoCursor<ChangeStreamDocument<Document>> cursor = inventory.watch().iterator();
ChangeStreamDocument<Document> next = cursor.next();

The examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

cursor = db.inventory.watch()
document = await cursor.next()

The Node.js examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

The following example uses stream to process the change events.

const collection = db.collection('inventory');
const changeStream = collection.watch();
changeStream.on('change', next => {
  // process next document
});

Alternatively, you can also use iterator to process the change events:

const collection = db.collection('inventory');
const changeStream = collection.watch();
const next = await changeStream.next();

ChangeStream extends EventEmitter.

The examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

$changeStream = $db->inventory->watch();
$changeStream->rewind();
$firstChange = $changeStream->current();
$changeStream->next();
$secondChange = $changeStream->current();

The Python examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

cursor = db.inventory.watch()
next(cursor)

The examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

cursor = inventory.watch.to_enum
next_change = cursor.next

The Swift (Async) examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

let inventory = db.collection("inventory")
// Option 1: retrieve next document via next()
let next = inventory.watch().flatMap { cursor in
    cursor.next()
}
// Option 2: register a callback to execute for each document
let result = inventory.watch().flatMap { cursor in
    cursor.forEach { event in
        // process event
        print(event)
    }
}

The Swift (Sync) examples below assume that you have connected to a MongoDB replica set and have accessed a database that contains an inventory collection.

let inventory = db.collection("inventory")
let changeStream = try inventory.watch()
let next = changeStream.next()

To retrieve the data change event from the cursor, iterate the change stream cursor. For information on the change stream event, see Change Events.

The change stream cursor remains open until one of the following occurs:

  • The cursor is explicitly closed.

  • An invalidate event occurs; for example, a collection drop or rename.

  • The connection to the MongoDB deployment closes or times out. See Cursor Behaviors for more information.

  • If the deployment is a sharded cluster, a shard removal may cause an open change stream cursor to close, and the closed change stream cursor may not be fully resumable.

Note

The lifecycle of an unclosed cursor is language-dependent.

[1] You can specify a startAtOperationTime to open the cursor at a particular point in time. If the specified starting point is in the past, it must be in the time range of the oplog.

Modify Change Stream Output

➤ Use the Select your language drop-down menu in the upper-right to set the language of the examples on this page.

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

pipeline = BCON_NEW ("pipeline",
                     "[",
                     "{",
                     "$match",
                     "{",
                     "fullDocument.username",
                     BCON_UTF8 ("alice"),
                     "}",
                     "}",
                     "{",
                     "$addFields",
                     "{",
                     "newField",
                     BCON_UTF8 ("this is an added field!"),
                     "}",
                     "}",
                     "]");
stream = mongoc_collection_watch (collection, pipeline, &opts);
mongoc_change_stream_next (stream, &change);
if (mongoc_change_stream_error_document (stream, &error, NULL)) {
   MONGOC_ERROR ("%s\n", error.message);
}
mongoc_change_stream_destroy (stream);

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

var pipeline = new EmptyPipelineDefinition<ChangeStreamDocument<BsonDocument>>()
    .Match(change =>
        change.FullDocument["username"] == "alice" ||
        change.OperationType == ChangeStreamOperationType.Delete)
    .AppendStage<ChangeStreamDocument<BsonDocument>, ChangeStreamDocument<BsonDocument>, BsonDocument>(
        "{ $addFields : { newField : 'this is an added field!' } }");
var collection = database.GetCollection<BsonDocument>("inventory");
using (var cursor = collection.Watch(pipeline))
{
    while (cursor.MoveNext() && cursor.Current.Count() == 0) { } // keep calling MoveNext until we've read the first batch
    var next = cursor.Current.First();
}

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

pipeline := mongo.Pipeline{bson.D{{"$match", bson.D{{"$or",
	bson.A{
		bson.D{{"fullDocument.username", "alice"}},
		bson.D{{"operationType", "delete"}}}}},
}}}
cs, err := coll.Watch(ctx, pipeline)
assert.NoError(t, err)
defer cs.Close(ctx)
ok := cs.Next(ctx)
next := cs.Current

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

MongoClient mongoClient = MongoClients.create("mongodb://<username>:<password>@<host>:<port>");
// Select the MongoDB database and collection to open the change stream against
MongoDatabase db = mongoClient.getDatabase("myTargetDatabase");
MongoCollection<Document> collection = db.getCollection("myTargetCollection");
// Create $match pipeline stage.
List<Bson> pipeline = singletonList(Aggregates.match(Filters.or(
   Document.parse("{'fullDocument.username': 'alice'}"),
   Filters.in("operationType", asList("delete")))));
// Create the change stream cursor, passing the pipeline to the
// collection.watch() method
MongoCursor<Document> cursor = collection.watch(pipeline).iterator();

The pipeline list includes a single $match stage that filters any operations where the username is alice, or operations where the operationType is delete.

Passing the pipeline to the watch() method directs the change stream to return notifications after passing them through the specified pipeline.

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

pipeline = [
    {"$match": {"fullDocument.username": "alice"}},
    {"$addFields": {"newField": "this is an added field!"}},
]
cursor = db.inventory.watch(pipeline=pipeline)
document = await cursor.next()

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

The following example uses stream to process the change events.

const pipeline = [
  { $match: { 'fullDocument.username': 'alice' } },
  { $addFields: { newField: 'this is an added field!' } }
];
const collection = db.collection('inventory');
const changeStream = collection.watch(pipeline);
changeStream.on('change', next => {
  // process next document
});

Alternatively, you can also use iterator to process the change events:

const changeStreamIterator = collection.watch(pipeline);
const next = await changeStreamIterator.next();

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

$pipeline = [
    ['$match' => ['fullDocument.username' => 'alice']],
    ['$addFields' => ['newField' => 'this is an added field!']],
];
$changeStream = $db->inventory->watch($pipeline);
$changeStream->rewind();
$firstChange = $changeStream->current();
$changeStream->next();
$secondChange = $changeStream->current();

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

pipeline = [
    {"$match": {"fullDocument.username": "alice"}},
    {"$addFields": {"newField": "this is an added field!"}},
]
cursor = db.inventory.watch(pipeline=pipeline)
next(cursor)

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

let pipeline: [BSONDocument] = [
    ["$match": ["fullDocument.username": "alice"]],
    ["$addFields": ["newField": "this is an added field!"]]
]
let inventory = db.collection("inventory")
// Option 1: use next() to iterate
let next = inventory.watch(pipeline, withEventType: BSONDocument.self).flatMap { changeStream in
    changeStream.next()
}
// Option 2: register a callback to execute for each document
let result = inventory.watch(pipeline, withEventType: BSONDocument.self).flatMap { changeStream in
    changeStream.forEach { event in
        // process event
        print(event)
    }
}

You can control change stream output by providing an array of one or more of the following pipeline stages when configuring the change stream:

let pipeline: [BSONDocument] = [
    ["$match": ["fullDocument.username": "alice"]],
    ["$addFields": ["newField": "this is an added field!"]]
]
let inventory = db.collection("inventory")
let changeStream = try inventory.watch(pipeline, withEventType: BSONDocument.self)
let next = changeStream.next()

Tip

The _id field of the change stream event document act as the resume token. Do not use the pipeline to modify or remove the change stream event's _id field.

Starting in MongoDB 4.2, change streams will throw an exception if the change stream aggregation pipeline modifies an event's _id field.

See Change Events for more information on the change stream response document format.

Lookup Full Document for Update Operations

By default, change streams only return the delta of fields during the update operation. However, you can configure the change stream to return the most current majority-committed version of the updated document.

➤ Use the Select your language drop-down menu in the upper-right to set the language of the examples on this page.

To return the most current majority-committed version of the updated document, pass the "fullDocument" option with the "updateLookup" value to the mongoc_collection_watch method.

In the example below, all update operations notifications include a fullDocument field that represents the current version of the document affected by the update operation.

BSON_APPEND_UTF8 (&opts, "fullDocument", "updateLookup");
stream = mongoc_collection_watch (collection, pipeline, &opts);
mongoc_change_stream_next (stream, &change);
if (mongoc_change_stream_error_document (stream, &error, NULL)) {
   MONGOC_ERROR ("%s\n", error.message);
}
mongoc_change_stream_destroy (stream);

To return the most current majority-committed version of the updated document, pass "FullDocument = ChangeStreamFullDocumentOption.UpdateLookup" to the db.collection.watch() method.

In the example below, all update operations notifications include a FullDocument field that represents the current version of the document affected by the update operation.

var options = new ChangeStreamOptions { FullDocument = ChangeStreamFullDocumentOption.UpdateLookup };
var cursor = inventory.Watch(options);
while (cursor.MoveNext() && cursor.Current.Count() == 0) { } // keep calling MoveNext until we've read the first batch
var next = cursor.Current.First();
cursor.Dispose();

To return the most current majority-committed version of the updated document, SetFullDocument(options.UpdateLookup) change stream option.

cs, err := coll.Watch(ctx, mongo.Pipeline{}, options.ChangeStream().SetFullDocument(options.UpdateLookup))
assert.NoError(t, err)
defer cs.Close(ctx)
ok := cs.Next(ctx)
next := cs.Current

To return the most current majority-committed version of the updated document, pass FullDocument.UPDATE_LOOKUP to the db.collection.watch.fullDocument() method.

In the example below, all update operations notifications include a FullDocument field that represents the current version of the document affected by the update operation.

cursor = inventory.watch().fullDocument(FullDocument.UPDATE_LOOKUP).iterator();
next = cursor.next();

To return the most current majority-committed version of the updated document, pass full_document='updateLookup' to the db.collection.watch() method.

In the example below, all update operations notifications include a `full_document field that represents the current version of the document affected by the update operation.

cursor = db.inventory.watch(full_document="updateLookup")
document = await cursor.next()

To return the most current majority-committed version of the updated document, pass { fullDocument: 'updateLookup' } to the db.collection.watch() method.

In the example below, all update operations notifications include a fullDocument field that represents the current version of the document affected by the update operation.

The following example uses stream to process the change events.

const collection = db.collection('inventory');
const changeStream = collection.watch([], { fullDocument: 'updateLookup' });
changeStream.on('change', next => {
  // process next document
});

Alternatively, you can also use iterator to process the change events:

const changeStreamIterator = collection.watch([], { fullDocument: 'updateLookup' });
const next = await changeStreamIterator.next();

To return the most current majority-committed version of the updated document, pass "fullDocument' => \MongoDB\Operation\ChangeStreamCommand::FULL_DOCUMENT_UPDATE_LOOKUP" to the db.watch() method.

In the example below, all update operations notifications include a fullDocument field that represents the current version of the document affected by the update operation.

$changeStream = $db->inventory->watch([], ['fullDocument' => \MongoDB\Operation\Watch::FULL_DOCUMENT_UPDATE_LOOKUP]);
$changeStream->rewind();
$firstChange = $changeStream->current();
$changeStream->next();
$secondChange = $changeStream->current();

To return the most current majority-committed version of the updated document, pass full_document='updateLookup' to the db.collection.watch() method.

In the example below, all update operations notifications include a full_document field that represents the current version of the document affected by the update operation.

cursor = db.inventory.watch(full_document="updateLookup")
next(cursor)

To return the most current majority-committed version of the updated document, pass full_document: 'updateLookup' to the db.watch() method.

In the example below, all update operations notifications include a full_document field that represents the current version of the document affected by the update operation.

cursor = inventory.watch([], full_document: 'updateLookup').to_enum
next_change = cursor.next

To return the most current majority-committed version of the updated document, pass options: ChangeStreamOptions(fullDocument: .updateLookup) to the watch() method.

let inventory = db.collection("inventory")
// Option 1: use next() to iterate
let next = inventory.watch(options: ChangeStreamOptions(fullDocument: .updateLookup))
    .flatMap { changeStream in
        changeStream.next()
    }
// Option 2: register a callback to execute for each document
let result = inventory.watch(options: ChangeStreamOptions(fullDocument: .updateLookup))
    .flatMap { changeStream in
        changeStream.forEach { event in
            // process event
            print(event)
        }
    }

To return the most current majority-committed version of the updated document, pass options: ChangeStreamOptions(fullDocument: .updateLookup) to the watch() method.

let inventory = db.collection("inventory")
let changeStream = try inventory.watch(options: ChangeStreamOptions(fullDocument: .updateLookup))
let next = changeStream.next()

Note

If there are one or more majority-committed operations that modified the updated document after the update operation but before the lookup, the full document returned may differ significantly from the document at the time of the update operation.

However, the deltas included in the change stream document always correctly describe the watched collection changes that applied to that change stream event.

See Change Events for more information on the change stream response document format.

Resume a Change Stream

Change streams are resumable by specifying a resume token to either resumeAfter or startAfter when opening the cursor.

resumeAfter for Change Streams

You can resume a change stream after a specific event by passing a resume token to resumeAfter when opening the cursor.

See Resume Tokens for more information on the resume token.

Important

  • The oplog must have enough history to locate the operation associated with the token or the timestamp, if the timestamp is in the past.

  • You cannot use resumeAfter to resume a change stream after an invalidate event (for example, a collection drop or rename) closes the stream. Instead, you can use startAfter to start a new change stream after an invalidate event.

In the example below, the resumeAfter option is appended to the stream options to recreate the stream after it has been destroyed. Passing the _id to the change stream attempts to resume notifications starting after the operation specified.

stream = mongoc_collection_watch (collection, pipeline, NULL);
if (mongoc_change_stream_next (stream, &change)) {
   resume_token = mongoc_change_stream_get_resume_token (stream);
   BSON_APPEND_DOCUMENT (&opts, "resumeAfter", resume_token);
   mongoc_change_stream_destroy (stream);
   stream = mongoc_collection_watch (collection, pipeline, &opts);
   mongoc_change_stream_next (stream, &change);
   mongoc_change_stream_destroy (stream);
} else {
   if (mongoc_change_stream_error_document (stream, &error, NULL)) {
      MONGOC_ERROR ("%s\n", error.message);
   }
   mongoc_change_stream_destroy (stream);
}

In the example below, the resumeToken is retrieved from the last change stream document and passed to the Watch() method as an option. Passing the resumeToken to the Watch() method directs the change stream to attempt to resume notifications starting after the operation specified in the resume token.

  var resumeToken = previousCursor.GetResumeToken();
  var options = new ChangeStreamOptions { ResumeAfter = resumeToken };
  var cursor = inventory.Watch(options);
  cursor.MoveNext();
  var next = cursor.Current.First();
  cursor.Dispose();

You can use ChangeStreamOptions.SetResumeAfter to specify the resume token for the change stream. If the resumeAfter option is set, the change stream resumes notifications after the operation specified in the resume token. The SetResumeAfter takes a value that must resolve to a resume token, e.g. resumeToken in the example below.

resumeToken := original.ResumeToken()
cs, err := coll.Watch(ctx, mongo.Pipeline{}, options.ChangeStream().SetResumeAfter(resumeToken))
assert.NoError(t, err)
defer cs.Close(ctx)
ok = cs.Next(ctx)
result := cs.Current

You can use the resumeAfter() method to resume notifications after the operation specified in the resume token. The resumeAfter() method takes a value that must resolve to a resume token, e.g. resumeToken in the example below.

BsonDocument resumeToken = next.getResumeToken();
cursor = inventory.watch().resumeAfter(resumeToken).iterator();
next = cursor.next();

You can use the resume_after modifier to resume notifications after the operation specified in the resume token. The resume_after modifier takes a value that must resolve to a resume token, e.g. resume_token in the example below.

resume_token = cursor.resume_token
cursor = db.inventory.watch(resume_after=resume_token)
document = await cursor.next()

You can use the resumeAfter option to resume notifications after the operation specified in the resume token. The resumeAfter option takes a value that must resolve to a resume token, e.g. resumeToken in the example below.

const collection = db.collection('inventory');
const changeStream = collection.watch();
let newChangeStream;
changeStream.once('change', next => {
  const resumeToken = changeStream.resumeToken;
  changeStream.close();
  newChangeStream = collection.watch([], { resumeAfter: resumeToken });
  newChangeStream.on('change', next => {
    processChange(next);
  });
});

You can use the resumeAfter option to resume notifications after the operation specified in the resume token. The resumeAfter option takes a value that must resolve to a resume token, e.g. $resumeToken in the example below.

$resumeToken = $changeStream->getResumeToken();
if ($resumeToken === null) {
    throw new \Exception('Resume token was not found');
}
$changeStream = $db->inventory->watch([], ['resumeAfter' => $resumeToken]);
$changeStream->rewind();
$firstChange = $changeStream->current();

You can use the resume_after modifier to resume notifications after the operation specified in the resume token. The resume_after modifier takes a value that must resolve to a resume token, e.g. resume_token in the example below.

resume_token = cursor.resume_token
cursor = db.inventory.watch(resume_after=resume_token)
next(cursor)

You can use the resume_after modifier to resume notifications after the operation specified in the resume token. The resume_after modifier takes a value that must resolve to a resume token, e.g. resume_token in the example below.

  change_stream = inventory.watch
  cursor = change_stream.to_enum
  next_change = cursor.next
  resume_token = change_stream.resume_token
  new_cursor = inventory.watch([], resume_after: resume_token).to_enum
  resumed_change = new_cursor.next

You can use the resumeAfter option to resume notifications after the operation specified in the resume token. The resumeAfter option takes a value that must resolve to a resume token, e.g. resumeToken in the example below.

let inventory = db.collection("inventory")
inventory.watch(options: ChangeStreamOptions(fullDocument: .updateLookup))
    .flatMap { changeStream in
        changeStream.next().map { _ in
            changeStream.resumeToken
        }.always { _ in
            _ = changeStream.kill()
        }
    }.flatMap { resumeToken in
        inventory.watch(options: ChangeStreamOptions(resumeAfter: resumeToken)).flatMap { newStream in
            newStream.forEach { event in
                // process event
                print(event)
            }
        }
    }

You can use the resumeAfter option to resume notifications after the operation specified in the resume token. The resumeAfter option takes a value that must resolve to a resume token, e.g. resumeToken in the example below.

let inventory = db.collection("inventory")
let changeStream = try inventory.watch(options: ChangeStreamOptions(fullDocument: .updateLookup))
let next = changeStream.next()
let resumeToken = changeStream.resumeToken
let resumedChangeStream = try inventory.watch(options: ChangeStreamOptions(resumeAfter: resumeToken))
let nextAfterResume = resumedChangeStream.next()

startAfter for Change Streams

You can start a new change stream after a specific event by passing a resume token to startAfter when opening the cursor. Unlike resumeAfter, startAfter can resume notifications after an invalidate event by creating a new change stream.

See Resume Tokens for more information on the resume token.

Important

  • The oplog must have enough history to locate the operation associated with the token or the timestamp, if the timestamp is in the past.

Resume Tokens

The resume token is available from multiple sources:

Source
Description
Each change event notification includes a resume token on the _id field.

The $changeStream aggregation stage includes a resume token on the cursor.postBatchResumeToken field.

This field only appears when using the aggregate command.

The getMore command includes a resume token on the cursor.postBatchResumeToken field.

Starting in MongoDB 4.2, change streams will throw an exception if the change stream aggregation pipeline modifies an event's _id field.

Tip

MongoDB provides a "snippet", an extension to mongosh, that decodes hex-encoded resume tokens.

You can install and run the resumetoken snippet from mongosh:

snippet install resumetoken
decodeResumeToken('<RESUME TOKEN>')

You can also run resumetoken from the command line (without using mongosh) if npm is installed on your system:

npx mongodb-resumetoken-decoder <RESUME TOKEN>

See the following for more details on:

Resume Tokens from Change Events

Change event notifications include a resume token on the _id field:

{
   "_id": {
      "_data": "82635019A0000000012B042C0100296E5A1004AB1154ACACD849A48C61756D70D3B21F463C6F7065726174696F6E54797065003C696E736572740046646F63756D656E744B65790046645F69640064635019A078BE67426D7CF4D2000004"
    },
    "operationType": "insert",
    "clusterTime": Timestamp({ "t": 1666193824, "i": 1 }),
    "collectionUUID": new UUID("ab1154ac-acd8-49a4-8c61-756d70d3b21f"),
    "wallTime": ISODate("2022-10-19T15:37:04.604Z"),
    "fullDocument": {
       "_id": ObjectId("635019a078be67426d7cf4d2"'),
       "name": "Giovanni Verga"
    },
    "ns": {
       "db": "test",
       "coll": "names"
    },
    "documentKey": {
       "_id": ObjectId("635019a078be67426d7cf4d2")
    }
}

Resume Tokens from aggregate

When using the aggregate command, the $changeStream aggregation stage includes a resume token on the cursor.postBatchResumeToken field:

{
   "cursor": {
      "firstBatch": [],
      "postBatchResumeToken": {
         "_data": "8263515EAC000000022B0429296E1404"
      },
      "id": Long("4309380460777152828"),
      "ns": "test.names"
   },
   "ok": 1,
   "$clusterTime": {
      "clusterTime": Timestamp({ "t": 1666277036, "i": 1 }),
      "signature": {
         "hash": Binary(Buffer.from("0000000000000000000000000000000000000000", "hex"), 0),
         "keyId": Long("0")
      }
   },
   "operationTime": Timestamp({ "t": 1666277036, "i": 1 })
}

Resume Tokens from getMore

The getMore command also includes a resume token on the cursor.postBatchResumeToken field:

{
   "cursor": {
      "nextBatch": [],
      "postBatchResumeToken": {
         "_data": "8263515979000000022B0429296E1404"
      },
      "id": Long("7049907285270685005"),
      "ns": "test.names"
   },
   "ok": 1,
   "$clusterTime": {
      "clusterTime": Timestamp( { "t": 1666275705, "i": 1 } ),
      "signature": {
         "hash": Binary(Buffer.from("0000000000000000000000000000000000000000", "hex"), 0),
         "keyId": Long("0")
      }
   },
   "operationTime": Timestamp({ "t": 1666275705, "i": 1 })
}

Use Cases

Change streams can benefit architectures with reliant business systems, informing downstream systems once data changes are durable. For example, change streams can save time for developers when implementing Extract, Transform, and Load (ETL) services, cross-platform synchronization, collaboration functionality, and notification services.

Access Control

For deployments enforcing Authentication and authorization:

  • To open a change stream against specific collection, applications must have privileges that grant changeStream and find actions on the corresponding collection.

    { resource: { db: <dbname>, collection: <collection> }, actions: [ "find", "changeStream" ] }

  • To open a change stream on a single database, applications must have privileges that grant changeStream and find actions on all non-system collections in the database.

    { resource: { db: <dbname>, collection: "" }, actions: [ "find", "changeStream" ] }

  • To open a change stream on an entire deployment, applications must have privileges that grant changeStream and find actions on all non-system collections for all databases in the deployment.

    { resource: { db: "", collection: "" }, actions: [ "find", "changeStream" ] }

Event Notification

Change streams only notify on data changes that have persisted to a majority of data-bearing members in the replica set. This ensures that notifications are triggered only by majority-committed changes that are durable in failure scenarios.

For example, consider a 3-member replica set with a change stream cursor opened against the primary. If a client issues an insert operation, the change stream only notifies the application of the data change once that insert has persisted to a majority of data-bearing members.

If an operation is associated with a transaction, the change event document includes the txnNumber and the lsid.

Collation

Change streams use simple binary comparisons unless an explicit collation is provided.

Change Streams and Orphan Documents

Starting in MongoDB 5.3, during range migration, change stream events are not generated for updates to orphaned documents.

Change Streams with Document Pre- and Post-Images

Starting in MongoDB 6.0, you can use change stream events to output the version of a document before and after changes (the document pre- and post-images):

  • The pre-image is the document before it was replaced, updated, or deleted. There is no pre-image for an inserted document.

  • The post-image is the document after it was inserted, replaced, or updated. There is no post-image for a deleted document.

  • Enable changeStreamPreAndPostImages for a collection using db.createCollection(), create, or collMod.

Pre- and post-images are not available for a change stream event if the images were:

  • Not enabled on the collection at the time of a document update or delete operation.

  • Removed after the pre- and post-image retention time set in expireAfterSeconds.

    • The following example sets expireAfterSeconds to 100 seconds on an entire cluster:

      use admin
      db.runCommand( {
         setClusterParameter:
            { changeStreamOptions: {
               preAndPostImages: { expireAfterSeconds: 100 }
            } }
      } )

    • The following example returns the current changeStreamOptions settings, including expireAfterSeconds:

      db.adminCommand( { getClusterParameter: "changeStreamOptions" } )

    • Setting expireAfterSeconds to off uses the default retention policy: pre- and post-images are retained until the corresponding change stream events are removed from the oplog.

    • If a change stream event is removed from the oplog, then the corresponding pre- and post-images are also deleted regardless of the expireAfterSeconds pre- and post-image retention time.

Additional considerations:

  • Enabling pre- and post-images consumes storage space and adds processing time. Only enable pre- and post-images if you need them.

  • Limit the change stream event size to less than 16 megabytes. To limit the event size, you can:

    • Limit the document size to 8 megabytes. You can request pre- and post-images simultaneously in the change stream output if other change stream event fields like updateDescription are not large.

    • Request only post-images in the change stream output for documents up to 16 megabytes if other change stream event fields like updateDescription are not large.

    • Request only pre-images in the change stream output for documents up to 16 megabytes if:

      • document updates affect only a small fraction of the document structure or content, and

      • do not cause a replace change event. A replace event always includes the post-image.

  • To request a pre-image, you set fullDocumentBeforeChange to required or whenAvailable in db.collection.watch(). To request a post-image, you set fullDocument using the same method.

  • Pre-images are written to the config.system.preimages collection.

    • The config.system.preimages collection may become large. To limit the collection size, you can set expireAfterSeconds time for the pre-images as shown earlier.

    • Pre-images are removed asynchronously by a background process.

Important

Backward-Incompatible Feature

Starting in MongoDB 6.0, if you are using document pre- and post-images for change streams, you must disable changeStreamPreAndPostImages for each collection using the collMod command before you can downgrade to an earlier MongoDB version.

Tip

See also:

For complete examples with the change stream output, see Change Streams with Document Pre- and Post-Images.

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