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Merge Chunks in a Sharded Cluster

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The mergeChunks command allows you to combine continuous chunks on the same shard into a single chunk. This tutorial explains how to merge neighboring chunks in a sharded cluster.

Note

Examples in this procedure use a members collection in the test database, using the username field as the shard key.

In mongosh, identify the chunk ranges with the following operation:

sh.status()

In the output, the chunk ranges appear after the chunk counts for each sharded collection, as in the following example:

--- Sharding Status ---
sharding version: {
"_id" : 1,
"minCompatibleVersion" : 5,
"currentVersion" : 6,
"clusterId" : ObjectId("5ebf0bfd3eeb6037ec7cbba9")
}
shards:
{ "_id" : "shardA", "host" : "shardA/shardA-m1.example.net:27018,shardA-m2.example.net:27018,shardA-m3.example.net:27018", "state" : 1 }
{ "_id" : "shardB", "host" : "shardB/shardB-m1.example.net:27018,shardB-m2.example.net:27018,shardB-m3.example.net:27018", "state" : 1 }
active mongoses:
"4.4.0" : 1
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:
519 : Success
databases:
{ "_id" : "config", "primary" : "config", "partitioned" : true }
config.system.sessions
shard key: { "_id" : 1 }
unique: false
balancing: true
chunks:
shardA 512
shardB 512
too many chunks to print, use verbose if you want to force print
{ "_id" : "test", "primary" : "shardA", "partitioned" : true, "version" : { "uuid" : UUID("22c042fc-7e3d-4c6d-992d-f3d714759781"), "lastMod" : 1 } }
test.members
shard key: { "username" : 1 }
unique: false
balancing: true
chunks:
shardA 7
shardB 7
{ "username" : { "$minKey" : 1 } } -->> { "username" : "user16643" } on : shardB Timestamp(13, 0)
{ "username" : "user16643" } -->> { "username" : "user2329" } on : shardB Timestamp(16, 0)
{ "username" : "user2329" } -->> { "username" : "user29937" } on : shardB Timestamp(17, 0)
{ "username" : "user29937" } -->> { "username" : "user36583" } on : shardB Timestamp(18, 0)
{ "username" : "user36583" } -->> { "username" : "user43229" } on : shardB Timestamp(19, 0)
{ "username" : "user43229" } -->> { "username" : "user49877" } on : shardB Timestamp(20, 0)
{ "username" : "user49877" } -->> { "username" : "user56522" } on : shardB Timestamp(21, 0)
{ "username" : "user56522" } -->> { "username" : "user63169" } on : shardA Timestamp(21, 1)
{ "username" : "user63169" } -->> { "username" : "user69816" } on : shardA Timestamp(10, 1)
{ "username" : "user69816" } -->> { "username" : "user76462" } on : shardA Timestamp(11, 1)
{ "username" : "user76462" } -->> { "username" : "user83108" } on : shardA Timestamp(12, 1)
{ "username" : "user83108" } -->> { "username" : "user89756" } on : shardA Timestamp(14, 1)
{ "username" : "user89756" } -->> { "username" : "user96401" } on : shardA Timestamp(15, 1)
{ "username" : "user96401" } -->> { "username" : { "$maxKey" : 1 } } on : shardA Timestamp(15, 2)

The chunk ranges appear after the chunk counts for each sharded collection. For example, the following are the chunk ranges for the test.members collection:

{ "username" : { "$minKey" : 1 } } -->> { "username" : "user16643" } on : shardB Timestamp(13, 0)
{ "username" : "user16643" } -->> { "username" : "user2329" } on : shardB Timestamp(16, 0)
{ "username" : "user2329" } -->> { "username" : "user29937" } on : shardB Timestamp(17, 0)
{ "username" : "user29937" } -->> { "username" : "user36583" } on : shardB Timestamp(18, 0)
{ "username" : "user36583" } -->> { "username" : "user43229" } on : shardB Timestamp(19, 0)
{ "username" : "user43229" } -->> { "username" : "user49877" } on : shardB Timestamp(20, 0)
{ "username" : "user49877" } -->> { "username" : "user56522" } on : shardB Timestamp(21, 0)
{ "username" : "user56522" } -->> { "username" : "user63169" } on : shardA Timestamp(21, 1)
{ "username" : "user63169" } -->> { "username" : "user69816" } on : shardA Timestamp(10, 1)
{ "username" : "user69816" } -->> { "username" : "user76462" } on : shardA Timestamp(11, 1)
{ "username" : "user76462" } -->> { "username" : "user83108" } on : shardA Timestamp(12, 1)
{ "username" : "user83108" } -->> { "username" : "user89756" } on : shardA Timestamp(14, 1)
{ "username" : "user89756" } -->> { "username" : "user96401" } on : shardA Timestamp(15, 1)
{ "username" : "user96401" } -->> { "username" : { "$maxKey" : 1 } } on : shardA Timestamp(15, 2)

Merge contiguous chunks on the same shard.

For example, consider the following chunk ranges on shardA:

Note

The chunks to be merged are highlighted.

{ "username" : "user56522" } -->> { "username" : "user63169" } on : shardA Timestamp(21, 1)
{ "username" : "user63169" } -->> { "username" : "user69816" } on : shardA Timestamp(10, 1)
{ "username" : "user69816" } -->> { "username" : "user76462" } on : shardA Timestamp(11, 1)
{ "username" : "user76462" } -->> { "username" : "user83108" } on : shardA Timestamp(12, 1)
{ "username" : "user83108" } -->> { "username" : "user89756" } on : shardA Timestamp(14, 1)
{ "username" : "user89756" } -->> { "username" : "user96401" } on : shardA Timestamp(15, 1)
{ "username" : "user96401" } -->> { "username" : { "$maxKey" : 1 } } on : shardA Timestamp(15, 2)

To merge the highlighted contiguous chunks, issue the mergeChunks command against the admin database:

db.adminCommand( {
mergeChunks: "test.members",
bounds: [ { "username" : "user69816" },
{ "username" : "user96401" } ]
} )

On success, mergeChunks produces the following output:

{
"ok" : 1,
"operationTime" : Timestamp(1589580356, 14),
"$clusterTime" : {
"clusterTime" : Timestamp(1589580356, 14),
"signature" : {
"hash" : BinData(0,"up5VKd49G/uPCq1iger2nOtfIHw="),
"keyId" : NumberLong("6827188741371592725")
}
}
}

On any failure condition, mergeChunks returns a document where the value of the ok field is 0.

After merging the identified chunks, confirm the new chunk, as follows:

sh.status()

The output of sh.status() should resemble:

--- Sharding Status ---
sharding version: {
"_id" : 1,
"minCompatibleVersion" : 5,
"currentVersion" : 6,
"clusterId" : ObjectId("5ebef5447fa151d4bd79dd72")
}
shards:
{ "_id" : "shardA", "host" : "shardA/shardA-m1.example.net:27018,shardA-m2.example.net:27018,shardA-m3.example.net:27018", "state" : 1 }
{ "_id" : "shardB", "host" : "shardB/shardB-m1.example.net:27018,shardB-m2.example.net:27018,shardB-m3.example.net:27018", "state" : 1 }
active mongoses:
"4.4.0" : 1
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:
519 : Success
databases:
{ "_id" : "config", "primary" : "config", "partitioned" : true }
config.system.sessions
shard key: { "_id" : 1 }
unique: false
balancing: true
chunks:
shardA 512
shardB 512
too many chunks to print, use verbose if you want to force print
{ "_id" : "test", "primary" : "shardA", "partitioned" : true, "version" : { "uuid" : UUID("22c042fc-7e3d-4c6d-992d-f3d714759781"), "lastMod" : 1 } }
test.members
shard key: { "username" : 1 }
unique: false
balancing: true
chunks:
shardA 5
shardB 6
{ "username" : { "$minKey" : 1 } } -->> { "username" : "user16643" } on : shardA Timestamp(22, 0)
{ "username" : "user16643" } -->> { "username" : "user2329" } on : shardB Timestamp(22, 1)
{ "username" : "user2329" } -->> { "username" : "user29937" } on : shardB Timestamp(17, 0)
{ "username" : "user29937" } -->> { "username" : "user36583" } on : shardB Timestamp(18, 0)
{ "username" : "user36583" } -->> { "username" : "user43229" } on : shardB Timestamp(19, 0)
{ "username" : "user43229" } -->> { "username" : "user49877" } on : shardB Timestamp(20, 0)
{ "username" : "user49877" } -->> { "username" : "user56522" } on : shardB Timestamp(21, 0)
{ "username" : "user56522" } -->> { "username" : "user63169" } on : shardA Timestamp(21, 1)
{ "username" : "user63169" } -->> { "username" : "user69816" } on : shardA Timestamp(10, 1)
{ "username" : "user69816" } -->> { "username" : "user96401" } on : shardA Timestamp(21, 2)
{ "username" : "user96401" } -->> { "username" : { "$maxKey" : 1 } } on : shardA Timestamp(15, 2)

After the merge, the balancer may migrate chunks across shards to ensure a more even distribution of chunks.

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