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MongoDB mongos instances route queries and write operations
to shards in a sharded cluster. mongos provides the
only interface to a sharded cluster from the perspective of
applications. Applications never connect or communicate directly with
the shards.
The mongos tracks what data is on which shard by caching
the metadata from the config servers. The mongos uses the
metadata to route operations from applications and clients to the
mongod instances. A mongos has no persistent
state and consumes minimal system resources.
The most common practice is to run mongos instances on the
same systems as your application servers, but you can maintain
mongos instances on the shards or on other dedicated
resources. See also Number of mongos and Distribution.
Routing And Results Process
A mongos instance routes a query to a cluster by:
Determining the list of shards that must receive the query.
Establishing a cursor on all targeted shards.
The mongos then merges the data from each of the
targeted shards and returns the result document. Certain
query modifiers, such as sorting,
are performed on each shard before mongos
retrieves the results.
Aggregation operations running on multiple
shards may route results back to the mongos to merge results if they don't need to run on the database's primary shard.
There are two cases in which a pipeline is ineligible to run on
mongos.
The first case occurs when the merge part of the split pipeline
contains a stage which must run on a primary shard. For instance,
if $lookup requires access to an unsharded collection in the same
database as the sharded collection on which the aggregation is running,
the merge is obliged to run on the primary shard.
The second case occurs when the merge part of the split pipeline
contains a stage which may write temporary data to disk, such as
$group, and the client has specified allowDiskUse:true. In this
case, assuming that there are no other stages in the merge pipeline
which require the primary shard, the merge runs on a
randomly-selected shard in the set of shards targeted by the aggregation.
For more information on how the work of aggregation is split among
components of a sharded cluster query, use explain:true as a
parameter to the aggregate() call. The
return includes three JSON objects:
mergeTypeshows where the stage of the merge happens ("primaryShard", "anyShard", "specificShard", or "mongos"). WhenmergeTypeisspecificShard, the aggregate output includes amergeShardproperty that contains the shard ID of the merging shard.splitPipelineshows which operations in your pipeline have run on individual shards.shardsshows the work each shard has done.
In some cases, when the shard key or a prefix of the shard key
is a part of the query, the mongos performs a
targeted operation, routing queries to
a subset of shards in the cluster.
mongos performs a broadcast
operation for queries that do not include the
shard key, routing queries to all shards in the cluster. Some
queries that do include the shard key may still result in a broadcast
operation depending on the distribution of data in the cluster and the
selectivity of the query.
See Targeted Operations vs. Broadcast Operations for more on targeted and broadcast operations.
mongos can support hedged reads to
minimize latencies. See hedged reads for
more information.
How mongos Handles Query Modifiers
Sorting
If the result of the query is not sorted, the mongos
instance opens a result cursor that "round robins" results from all
cursors on the shards.
Limits
If the query limits the size of the result set using the
limit() cursor method, the mongos
instance passes that limit to the shards and then re-applies the limit
to the result before returning the result to the client.
Skips
If the query specifies a number of records to skip using the
skip() cursor method, the mongos cannot
pass the skip to the shards, but rather retrieves unskipped results
from the shards and skips the appropriate number of documents when assembling
the complete result.
When used in conjunction with a limit(), the
mongos passes the limit plus the value of the
skip() to the shards to improve the efficiency of these
operations.
Read Preference and Shards
For sharded clusters, mongos applies the read
preference when reading from the shards. The
member selected is governed by both the read preference and
replication.localPingThresholdMs settings, and is
re-evaluated for each operation.
For details on read preference and sharded clusters, see Read Preference and Shards.
Hedged Reads
mongos instances can hedge
reads that use non-primary read preferences. With hedged reads, the mongos
instances route read operations to two replica set members per each
queried shard and return results from the first respondent per shard.
The additional read sent to hedge the read operation uses the
maxTimeMS value of maxTimeMSForHedgedReads.
Hedged reads are supported for the following operations:
Hedged Reads and Read Preference
Hedged reads are specified per operation as part of the read
preference. Non-primary read preferences support hedged reads. See Hedged Read
Preference Option.
To specify hedged read for a non-
primaryread preference, refer to the driver read preference API documentation.Read preference
nearestenables the hedged read option by default.
For details on read preference and sharded clusters as well as member selection, see Read Preference and Shards.
Enable/Disable Support for Hedged Reads
By default, mongos instances support using hedged
reads. To turn off a mongos instance's support for
hedged reads, see the readHedgingMode parameter. If the
hedged read support is off, mongos does not use
hedged reads regardless of the hedge option specified for the
read preference.
Hedged Reads Diagnostics
The command serverStatus and its corresponding
mongosh method db.serverStatus() return
hedgingMetrics.
Confirm Connection to mongos Instances
To detect if the MongoDB instance that your client is connected
to is mongos, use the hello command. When a
client connects to a mongos, hello returns
a document with a msg field that holds the string
isdbgrid. For example:
{ "isWritablePrimary" : true, "msg" : "isdbgrid", "maxBsonObjectSize" : 16777216, "ok" : 1, ... }
If the application is instead connected to a mongod, the
returned document does not include the isdbgrid string.
Targeted Operations vs. Broadcast Operations
Generally, the fastest queries in a sharded environment are those that
mongos route to a single shard, using the shard key and the
cluster meta data from the config server.
These targeted operations use the
shard key value to locate the shard or subset of shards that satisfy the
query document.
For queries that don't include the shard key, mongos must query all
shards, wait for their responses and then return the result to the
application. These "scatter/gather" queries can be long running operations.
Broadcast Operations
mongos instances broadcast queries to all shards for the
collection unless the mongos can
determine which shard or subset of shards stores this data.
After the mongos receives responses from all shards, it merges
the data and returns the result document. The performance of a broadcast
operation depends on the overall load of the cluster, as well as variables
like network latency, individual shard load, and number of documents returned
per shard. Whenever possible, favor operations that result in targeted
operation over those that result in a broadcast
operation.
Multi-update operations are always broadcast operations.
The updateMany() and
deleteMany() methods are broadcast
operations, unless the query document specifies the shard key in full.
Targeted Operations
mongos can route queries that include the shard key or the prefix
of a compound shard key a specific shard or set of
shards. mongos uses the shard key value to locate the
chunk whose range includes the shard key value and directs the
query at the shard containing that chunk.
For example, if the shard key is:
{ a: 1, b: 1, c: 1 }
The mongos program can route queries that include the full
shard key or either of the following shard key prefixes at a
specific shard or set of shards:
{ a: 1 } { a: 1, b: 1 }
All insertOne() operations target to one shard. Each
document in the insertMany() array targets to a
single shard, but there is no guarantee all documents in the array insert into
a single shard.
All updateOne(),
replaceOne() and deleteOne()
operations must include the shard key or _id in the query
document. MongoDB returns an error if these methods are used without
the shard key or _id.
Depending on the distribution of data in the cluster and the selectivity of
the query, mongos may still perform a broadcast
operation to fulfill these queries.
Index Use
When a shard receives a query, it uses the most efficient index available to fulfill that query. The index used may be either the shard key index or another eligible index present on the shard.
Sharded Cluster Security
Use Internal/Membership Authentication to enforce intra-cluster
security and prevent unauthorized cluster components from accessing the
cluster. You must start each mongod or mongos in the
cluster with the appropriate security settings in order to enforce internal
authentication.
Starting in MongoDB 5.3, SCRAM-SHA-1 cannot be used for intra-cluster authentication. Only SCRAM-SHA-256 is supported.
In previous MongoDB versions, SCRAM-SHA-1 and SCRAM-SHA-256 can both be used for intra-cluster authentication, even if SCRAM is not explicitly enabled.
See Deploy Sharded Cluster with Keyfile Authentication for a tutorial on deploying a secured sharded cluster.
Cluster Users
Sharded clusters support Role-Based Access Control (RBAC) for restricting
unauthorized access to cluster data and operations. You must start each
mongod in the cluster, including the config servers, with the --auth option in order to enforce RBAC.
Alternatively, enforcing Internal/Membership Authentication for
inter-cluster security also enables user access controls via RBAC.
With RBAC enforced, clients must specify a --username,
--password, and
--authenticationDatabase when
connecting to the mongos in order to access cluster resources.
Each cluster has its own cluster users. These users cannot be used to access individual shards.
See Enable Access Control for a tutorial on enabling adding users to an RBAC-enabled MongoDB deployment.
Metadata Operations
mongos uses "majority" write concern
for the following operations that affect the sharded cluster
metadata:
Command | Method | Note |
|---|---|---|
Changed in MongoDB 3.6 | ||
Additional Information
fCV Compatibility
The mongos binary cannot connect to mongod
instances whose feature compatibility version (fCV) is greater
than that of the mongos. For example, you cannot connect
a MongoDB 4.0 version mongos to a 4.2
sharded cluster with fCV set to 4.2. You
can, however, connect a MongoDB 4.0 version
mongos to a 4.2 sharded cluster with fCV set to 4.0.
Full Time Diagnostic Data Capture Requirements
mongod includes a Full Time Diagnostic Data Capture mechanism to assist MongoDB engineers with troubleshooting
deployments. If this thread fails, it terminates the originating process.
To avoid the most common failures, confirm that the user running the
process has permissions to create the FTDC diagnostic.data
directory. For mongod the directory is within
storage.dbPath. For mongos it is parallel to systemLog.path.
Connection Pools
Starting in MongoDB 4.2, MongoDB adds the parameter
ShardingTaskExecutorPoolReplicaSetMatching. This
parameter determines the minimum size of the
mongod / mongos instance's
connection pool to each member of the sharded cluster. This value
can vary during runtime.
mongod and mongos maintain connection
pools to each replica set secondary for every replica set in the
sharded cluster. By default, these pools have a number of connections
that is at least the number of connections to the primary.
To modify, see ShardingTaskExecutorPoolReplicaSetMatching.
Using Aggregation Pipelines with Clusters
For more information on how sharding works with aggregations, read the sharding chapter in the Practical MongoDB Aggregations e-book.