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sh.updateZoneKeyRange()

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  • Definition
  • Compatibility
  • Behavior
  • Examples
sh.updateZoneKeyRange(namespace, minimum, maximum, zone)

Associates a range of shard key values with a zone.

You can run updateZoneKeyRange database command and its helpers sh.updateZoneKeyRange() and sh.addTagRange() on an unsharded collection or a non-existing collection.

Important

mongosh Method

This page documents a mongosh method. This is not the documentation for database commands or language-specific drivers, such as Node.js.

For the database command, see the updateZoneKeyRange command.

For MongoDB API drivers, refer to the language-specific MongoDB driver documentation.

sh.updateZoneKeyRange() takes the following arguments:

Parameter
Type
Description

namespace

string

The namespace of the sharded collection associate with the zone.

The collection must be sharded for the operation to succeed.

minimum

document

The inclusive lower bound of the range of shard key values.

Specify each field of the shard key in the form of <fieldname> : <value>. The value must be of the same BSON type or types as the shard key.

To use hashed sharding, the field value needs to be of type NumberLong.

maximum

document

The exclusive upper bound of the range of shard key values.

Specify each field of the shard key in the form of <fieldname> : <value>. The value must be of the same BSON type or types as the shard key.

To use hashed sharding, the field value needs to be of type NumberLong.

zone

string

The name of the zone to associate with the range of shard key values bounded by minimum and maximum.

Only issue sh.updateZoneKeyRange() when connected to a mongos instance.

This method is available in deployments hosted in the following environments:

  • MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud

Important

This command is not supported in M0, M2, and M5 clusters. For more information, see Unsupported Commands.

You cannot create a range of shard key values whose lower and upper boundaries overlap with an existing range for the sharded collection. For example, given an existing range of 1 to 10, you cannot create a new range of 5 to 20, as the new range would overlap with the existing range.

A zone can have multiple ranges of data associated with it, but a range can at most be associated with a single zone.

See the zone manual page for more information on zones in sharded clusters.

If you are considering performing zone sharding on an empty or non-existent collection, use sh.updateZoneKeyRange() to create the zones and zone ranges before sharding the collection (since 4.0.2). Starting in version 4.0.3, creating zones and zone ranges on empty or non-existing collections allows MongoDB to optimize the initial chunk creation and distribution process when sharding the collection. This optimized process supports faster setup of zoned sharding with less balancer overhead than creating zones after sharding. The balancer performs all chunk management after the optimized initial chunk creation and distribution.

For an example of defining zones and zone ranges for initial chunk distribution, see Pre-Define Zones and Zone Ranges for an Empty or Non-Existing Collection.

MongoDB supports sharding collections on compound hashed indexes. MongoDB can perform optimized initial chunk creation and distribution when sharding the empty or non-existing collection on a compound hashed shard key.

If the hashed field is the prefix of the shard key (i.e. the first field in the shard key), all of the following must be true for MongoDB to perform initial chunk creation and distribution:

If the hashed field is not the prefix of the shard key (i.e. the shard key has one or more non-hashed leading fields), all of the following must be true for MongoDB to perform initial chunk creation and distribution:

  • The collection has one zone range for each combination of distinct prefix field values (i.e. all fields preceding the hashed field).

  • For the lower-bound of each zone range, specify MinKey for the hashed field and all subsequent fields.

  • For each zone range, at least one upper-bound prefix field must differ from its lower-bound counterpart.

  • sh.shardCollection() specifies the presplitHashedZones: true option.

For a more complete example of defining zones and zone ranges for initial chunk distribution on a compound hashed shard key, see Pre-Define Zones and Zone Ranges for an Empty or Non-Existing Collection.

Tip

See also:

After associating a range to a zone, the balancer must first run in order to migrate any chunks whose ranges are covered by the zone to shards inside of that zone. Until balancing completes, some chunks may reside on the wrong shard given the configured zones for the sharded cluster. See Balancer for more information.

See the sharded cluster balancer manual page for more information on how migrations work in a sharded cluster.

Zone ranges are always inclusive of the lower boundary and exclusive of the upper boundary.

Dropping a collection deletes its associated zone/tag ranges.

In earlier versions, MongoDB does not remove the tag associations for a dropped collection, and if you later create a new collection with the same name, the old tag associations will apply to the new collection.

For sharded clusters running with authentication, you must authenticate as either:

  • a user whose privileges include the specified actions on various collections in the config database:

    • find on the config.shards collection

    • find and update on the config.tags collection;

    or, alternatively,

  • a user whose privileges include enableSharding on the cluster resource.

The clusterAdmin or clusterManager built-in roles have the appropriate permissions for issuing sh.updateZoneKeyRange(). See the documentation page for Role-Based Access Control for more information.

Given a sharded collection exampledb.collection with a shard key of { a : 1 }, the following operation creates a range with a lower bound of 1 and an upper bound of 10 on the alpha zone:

sh.updateZoneKeyRange(
"exampledb.collection",
{ a : 1 },
{ a : 10 },
"alpha"
)

The following operation removes the previously created range by passing null to the zone field.

sh.updateZoneKeyRange(
"exampledb.collection",
{ a : 1 },
{ a : 10 },
null
)

The min and max must match exactly the bounds of the target range. The following operation attempts to remove the previously created range, but specifies { a : 0 } as the min bound:

sh.updateZoneKeyRange(
"exampledb.collection",
{ a : 0 },
{ a : 10 },
null
)

While the range of { a : 0 } and { a : 10 } encompasses the existing range, it is not an exact match and therefore updateZoneKeyRange does not remove anything.

Given a sharded collection exampledb.collection with a shard key of { a : 1, b : 1 }, the following operation creates a range covering the lower bound of { a: 1, b : 1 } and an upper bound of { a : 10, b : 10} and associates it with the alpha zone:

sh.updateZoneKeyRange(
"exampledb.collection",
{ a : 1, b : 1 },
{ a : 10, b : 10 },
"alpha"
)

If you create zones and zone ranges on empty or non-existing collections, MongoDB may optimize the initial chunk creation and distribution process when sharding the collection. This optimized process supports faster setup of zoned sharding with less balancer overhead than creating zones after sharding. The balancer performs all chunk management after the optimized initial chunk creation and distribution. For more information, see Initial Chunk Distribution with Compound Hashed Shard Keys for more information.

The sections below contain examples for three different shard key types.

Consider the following examples, which explore pre-defining zones or zone ranges for three different shard key types:

Note

This example only applies to single-field or compound shard keys without a hashed field.

For example, { "zip" : 1 } or { "zip" : 1, "account" : 1}

1

Use sh.addShardToZone() to create the zones:

sh.addShardToZone("shardA", "DC1")
sh.addShardToZone("shardB", "DC2")
2

Use sh.updateZoneKeyRange() to create the ranges for the empty contacts collection in the exampledb database:

sh.updateZoneKeyRange(
"exampledb.contacts",
{ zip: 10001 },
{ zip: 10090 },
"DC1"
);
sh.updateZoneKeyRange(
"exampledb.contacts",
{ zip: 90001 },
{ zip: 96054 },
"DC2"
);
3

Note

If the collection does not exist, the sharding operation creates the collection.

If the collection is empty and no index exists to support the shard key, the sharding operation creates the index.

Use sh.shardCollection() to shard the collection contacts:

sh.shardCollection("exampledb.contacts", { zip: 1 } );
4

To see the created chunks and distribution, run the sh.status() operation:

sh.status()

The method returns:

--- Sharding Status ---
sharding version: {
"_id" : 1,
"minCompatibleVersion" : 5,
"currentVersion" : 6,
"clusterId" : ObjectId("5b80c06d35a961fd0ae1986d")
}
shards:
{ "_id" : "shardA", "host" : "shardA/mongodb0.example.net:27018,mongodb1.example.net:27018,mongodb2.example.net:27018", "state" : 1, "tags" : [ "DC1" ] }
{ "_id" : "shardB", "host" : "shardB/mongodb3.example.net:27018,mongodb4.example.net:27018,mongodb5.example.net:27018", "state" : 1, "tags" : [ "DC2" ] }
active mongoses:
"4.2.0" : 2
autosplit:
Currently enabled: yes
balancer:
Currently enabled: yes
Currently running: no
Failed balancer rounds in last 5 attempts: 0
Migration Results for the last 24 hours:
No recent migrations
databases:
{ "_id" : "config", "primary" : "config", "partitioned" : true }
{ "_id" : "exampledb", "primary" : "shardA", "partitioned" : true, "version" : { "uuid" : UUID("6c351bcf-acd2-4fd9-82d8-9f6bd7321558"), "lastMod" : 1 } }
exampledb.contacts
shard key: { "zip" : 1 }
unique: false
balancing: true
chunks:
shardA 3
shardB 2
{ "zip" : { "$minKey" : 1 } } -->> { "zip" : 10001 } on : shardA Timestamp(1, 0)
{ "zip" : 10001 } -->> { "zip" : 10090 } on : shardA Timestamp(1, 1)
{ "zip" : 10090 } -->> { "zip" : 90001 } on : shardB Timestamp(1, 2)
{ "zip" : 90001 } -->> { "zip" : 96054 } on : shardB Timestamp(1, 3)
{ "zip" : 96054 } -->> { "zip" : { "$maxKey" : 1 } } on : shardA Timestamp(1, 4)
tag: DC1 { "zip" : 10001 } -->> { "zip" : 10090 }
tag: DC2 { "zip" : 90001 } -->> { "zip" : 96054 }

For the collection, sharding operation created 5 chunks (two chunks that correspond to the zone ranges and the other three to cover all other values) across shardA and shardB.

Note

This example only applies to compound hashed shard keys where the hashed field is the prefix of the shard key (i.e. the first field in the shard key is hashed).

For example, { "_id" : "hashed", "facility" : 1 }

MongoDB supports sharding collections on compound hashed indexes. When sharding on a compound hashed shard key, MongoDB can perform optimized initial chunk creation and distribution on the empty or non-existing collection only if the defined zone ranges meet additional requirements.

Consider an empty collection examples.metrics which will store analytics from one of two manufacturing facilities. The planned shard key is { "_id" : "hashed", "facility" : 1}, where the hashed field is the shard key prefix.

1

The planned shard key is { "_id" : "hashed", "facility" : 1 }. Since the hashed field is the prefix (i.e. the first field in the shard key), create a single zone using sh.addShardToZone():

sh.addShardToZone("shardA", "FacilityAlpha")
sh.addShardToZone("shardB", "FacilityAlpha")
2

Initial chunk distribution on a compound hashed shard key with a hashed prefix requires a single zone range with MinKey for all lower-bound fields and MaxKey for all upper-bound fields.

Use sh.updateZoneKeyRange() to create a single range:

sh.updateZoneKeyRange(
"examples.metrics",
{ "_id" : MinKey, "facility" : MinKey },
{ "_id" : MaxKey, "facility" : MaxKey },
"FacilityAlpha"
);
3

Note

If the collection does not exist, the sharding operation creates the collection.

If the collection is empty and no index exists to support the shard key, the sharding operation creates the index.

Use sh.shardCollection() with presplitHashedZones: true to shard the collection and perform initial chunk creation and distribution:

sh.shardCollection(
"examples.metrics",
{ "_id" : "hashed", "facility" : 1 },
false,
{ presplitHashedZones: true }
)
4

To see the created chunks and distribution, run the sh.status() operation:

sh.status()

The output resembles the following (content omitted for readability):

--- Sharding Status ---
databases:
{ "_id" : "config", "primary" : "config", "partitioned" : true }
{ "_id" : "examples", "primary" : "shardA", "partitioned" : true, "version" : { "uuid" : UUID("245f8abf-a363-48b0-8208-2a5b577bbb4e"), "lastMod" : 1 } }
examples.metrics
shard key: { "_id" : "hashed", "facility" : 1 }
unique: false
balancing: true
chunks:
shardA 2
shardB 2
{ "_id" : { "$minKey" : 1 }, "facility" : { "$minKey" : 1 } } -->> { "_id" : NumberLong("-4611686018427387902"), "facility" : { "$minKey" : 1 } } on : shardA Timestamp(1, 0)
{ "_id" : NumberLong("-4611686018427387902"), "facility" : { "$minKey" : 1 } } -->> { "_id" : NumberLong(0), "facility" : { "$minKey" : 1 } } on : shardA Timestamp(1, 1)
{ "_id" : NumberLong(0), "facility" : { "$minKey" : 1 } } -->> { "_id" : NumberLong("4611686018427387902"), "facility" : { "$minKey" : 1 } } on : shardB Timestamp(1, 2)
{ "_id" : NumberLong("4611686018427387902"), "facility" : { "$minKey" : 1 } } -->> { "_id" : { "$maxKey" : 1 }, "facility" : { "$maxKey" : 1 } } on : shardB Timestamp(1, 3)
tag: FacilityAlpha { "_id" : { "$minKey" : 1 }, "facility" : { "$minKey" : 1 } } -->> { "_id" : { "$maxKey" : 1 }, "facility" : { "$maxKey" : 1 } }

The sharding operation produced 4 chunks in total. Two chunks correspond to the absolute lower and upper bounds. One zone was created on shardA and shardB corresponding to FacilityAlpha. The zone was subdivided into 2 chunks using the hashed field.

Note

This example only applies to compound hashed shard keys where the hashed field is not the prefix of the shard key (i.e. the first field in the shard key is not hashed).

For example, { "facility" : 1, "_id" : "hashed" }

MongoDB supports sharding collections on compound hashed indexes. When sharding on a compound hashed shard key, MongoDB can perform optimized initial chunk creation and distribution on the empty or non-existing collection only if the defined zone ranges meet additional requirements.

Consider an empty collection examples.metrics which will store analytics from one of two manufacturing facilities. The planned shard key is { "facility" : 1, "_id" : "hashed" }, where the hashed field is not the shard key prefix.

  • The facility field stores the name of the facility: "FacilityAlpha" or "FacilityBaker". The collection requires zone ranges on facility to help isolate data for each facility to specific shards.

  • The _id field compensates for the low-cardinality of the facility field. Hashing compensates for the monotonically-increasing nature of the _id field.

1

Use the sh.addShardToZone() command to create the zones.

sh.addShardToZone("shardA", "FacilityAlpha")
sh.addShardToZone("shardB", "FacilityBaker")
2

The planned shard key is {"facility" : 1, "_id" : "hashed"}. The facility field has two possible values: FacilityAlpha and FacilityBaker.

Initial chunk distribution on a compound hashed shard key where the hashed field is not the prefix requires one zone range for each combination of distinct prefix field values (i.e. all fields preceding the hashed field). Since facility has two distinct prefix values, the collection requires exactly two zone ranges that cover those values.

  • The lower bound range specifies MinKey for all non-prefix fields.

  • The upper-bound range has at least one prefix field that differs from its lower-bound counterpart.

Use sh.updateZoneKeyRange() to create the range for "facility": "FacilityAlpha":

sh.updateZoneKeyRange(
"examples.metrics",
{ "facility": "FacilityAlpha", "_id" : MinKey },
{ "facility": "FacilityBaker", "_id" : MinKey },
"FacilityAlpha"
);
  • Since zone range upper bounds are exclusive, this range only covers documents with the distinct shard key prefix value "facilty" : "FacilityAlpha" and all possible values of _id.

Use sh.updateZoneKeyRange() to create the range for "facility": "FacilityBaker":

sh.updateZoneKeyRange(
"examples.metrics",
{ "facility": "FacilityBaker", "_id" : MinKey },
{ "facility": MaxKey, "_id" : MinKey },
"FacilityBaker"
);
  • While the upper bound of this range can technically capture other values of facility, the initial chunk distribution logic relies on the assumption that no other distinct values for facility exist. Since the collection only contains documents where facility is FacilityAlpha or FacilityBaker, this range only covers documents with the distinct shard key prefix value "facility" : "FacilityBaker" and all possible values of _id.

3

Note

If the collection does not exist, the sharding operation creates the collection.

If the collection is empty and no index exists to support the shard key, the sharding operation creates the index.

Use sh.shardCollection() with presplitHashedZones: true to shard the collection and perform initial chunk creation and distribution:

sh.shardCollection(
"examples.metrics",
{ "facility" : 1, "_id" : "hashed"},
false,
{ presplitHashedZones: true }
)
4

To see the created chunks and distribution, run the sh.status() operation:

sh.status()

The output resembles the following (content omitted for readability):

--- Sharding Status ---
databases:
{ "_id" : "config", "primary" : "config", "partitioned" : true }
{ "_id" : "examples", "primary" : "shardA", "partitioned" : true, "version" : { "uuid" : UUID("6c351bcf-acd2-4fd9-82d8-9f6bd7321558"), "lastMod" : 1 } }
examples.metrics
shard key: { "facility" : 1, "_id" : "hashed" }
unique: false
balancing: true
chunks:
shardA 3
shardB 3
{ "facility" : { "$minKey" : 1 }, "_id" : { "$minKey" : 1 } } -->> { "facility" : "FacilityAlpha", "_id" : { "$minKey" : 1 } } on : shard1 Timestamp(1, 0)
{ "facility" : "FacilityAlpha", "_id" : { "$minKey" : 1 } } -->> { "facility" : "FacilityAlpha", "_id" : NumberLong(0) } on : shard1 Timestamp(1, 1)
{ "facility" : "FacilityAlpha", "_id" : NumberLong(0) } -->> { "facility" : "FacilityBaker", "_id" : { "$minKey" : 1 } } on : shard1 Timestamp(1, 2)
{ "facility" : "FacilityBaker", "_id" : { "$minKey" : 1 } } -->> { "facility" : "FacilityBaker", "_id" : NumberLong(0) } on : shard2 Timestamp(1, 3)
{ "facility" : "FacilityBaker", "_id" : NumberLong(0) } -->> { "facility" : { "$maxKey" : 1 }, "_id" : { "$minKey" : 1 } } on : shard2 Timestamp(1, 4)
{ "facility" : { "$maxKey" : 1 }, "_id" : { "$minKey" : 1 } } -->> { "facility" : { "$maxKey" : 1 }, "_id" : { "$maxKey" : 1 } } on : shard2 Timestamp(1, 5)
tag: FacilityAlpha { "facility" : "FacilityAlpha", "_id" : { "$minKey" : 1 } } -->> { "facility" : "FacilityBaker", "_id" : { "$minKey" : 1 } }
tag: FacilityBaker { "facility" : "FacilityBaker", "_id" : { "$minKey" : 1 } } -->> { "facility" : { "$maxKey" : 1 }, "_id" : { "$minKey" : 1 } }

The sharding operation produced 6 chunks in total. Two chunks correspond to the absolute lower and upper bounds. Two zones were created, one on shardA and one on shardB, corresponding to FacilityAlpha and FacilityBaker. Each of these zones has been further subdivided into 2 chunks using the hashed field.

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