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![db.runCommand({ listshards:1 })
{ "shards" :
[{"_id”: "shard0000”,"host”: ”<hostname>:27018” } ],
"ok" : 1
}
Verify that the shard was added](https://image.slidesharecdn.com/mongodbhenrikingomongodb-141111143655-conversion-gate02/85/MongoDB-Henrik-Ingo-MongoDB-17-320.jpg)
![{
_id: ObjectId(),
user: 123,
time: Date(),
subject: “...”,
recipients: [],
body: “...”,
attachments: []
}
Example: Email Storage
Most common scenario, can be applied to 90% cases
Each document can be up to 16MB
Each user may have GBs of storage
Most common query: get user emails sorted by time
Indexes on {_id}, {user, time}, {recipients}](https://image.slidesharecdn.com/mongodbhenrikingomongodb-141111143655-conversion-gate02/85/MongoDB-Henrik-Ingo-MongoDB-42-320.jpg)
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Шардинг в MongoDB, Henrik Ingo (MongoDB)
This document provides an overview of MongoDB sharding, including how it partitions and distributes data across shards, maintains balanced clusters, and routes queries. The key aspects covered are MongoDB's approach to automatic sharding with minimal configuration needed, the sharding architecture involving config servers, mongos routers and shards, and considerations for choosing an appropriate shard key like cardinality and query patterns.
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Шардинг в MongoDB, Henrik Ingo (MongoDB)
- 1. Solutions Architect, MongoDB Henrik Ingo @h_ingo Introduction to Sharding
- 2. Agenda •Scaling Data •MongoDB'sApproach •Architecture •Configuration •Mechanics
- 3. MongoDB's Approach toSharding
- 4. Partitioning • Userdefines shard key • Shard key defines range of data • Key space is like points on a line • Range is a segment of that line
- 5. Initially 1 chunk Default max chunk size: 64mb MongoDB automatically splits & migrates chunks when max reached Data Distribution
- 6. Queries routed tospecific shards MongoDB balances cluster MongoDB migrates data to new nodes Routing and Balancing
- 7. MongoDB Auto-Sharding •Minimal effort required – Same interface as single mongod • Two steps – Enable Sharding for a database – Shard collection within database
- 8.
- 9. What is aShard? • Shard is a node of the cluster • Shard can be a single mongod or a replica set
- 10.
- 11.
- 12.
- 13. mongod --configsvr Startsa configuration server on the default port (27019) Starting the Configuration Server
- 14. mongos --configdb <hostname>:27019 For 3 configuration servers: mongos --configdb <host1>:<port1>,<host2>:<port2>,<host3>:<port3> This is always how to start a new mongos, even if the cluster is already running Start the mongos Router
- 15. mongod --shardsvr Startsa mongodwith the default shard port (27018) Shard is not yet connected to the rest of the cluster Shard may have already been running in production Start the shard database
- 16. On mongos: –sh.addShard(‘<host>:27018’) Adding a replica set: – sh.addShard(‘<rsname>/<seedlist>’) Add the Shard
- 17. db.runCommand({ listshards:1 }) { "shards" : [{"_id”: "shard0000”,"host”: ”<hostname>:27018” } ], "ok" : 1 } Verify that the shard was added
- 18. Enabling Sharding •Enable sharding on a database sh.enableSharding(“<dbname>”) • Shard a collection with the given key sh.shardCollection(“<dbname>.people”,{“country”:1}) • Use a compound shard key to prevent duplicates sh.shardCollection(“<dbname>.cars”,{“year”:1, ”uniqueid”:1})
- 19. Tag Aware Sharding • Tag aware sharding allows you to control the distribution of your data • Tag a range of shard keys – sh.addTagRange(<collection>,<min>,<max>,<tag>) • Tag a shard – sh.addShardTag(<shard>,<tag>)
- 20.
- 21. Cluster Request Routing • Targeted Queries • Scatter Gather Queries • Scatter Gather Queries with Sort
- 22. Cluster Request Routing:Targeted Query
- 23.
- 24. Request routed toappropriate shard
- 25.
- 26. Mongos returns resultsto client
- 27. Cluster Request Routing:Non-Targeted Query
- 28.
- 29. Request sent toall shards
- 30. Shards return resultsto mongos
- 31. Mongos returns resultsto client
- 32. Cluster Request Routing:Non-Targeted Query with Sort
- 33. Non-Targeted request withsort received
- 34. Request sent toall shards
- 35. Query and sortperformed locally
- 36. Shards return resultsto mongos
- 37. Mongos merges sortedresults
- 38. Mongos returns resultsto client
- 39.
- 40. Shard Key •Shard key is immutable • Shard key values are immutable • Shard key must be indexed • Shard key limited to 512 bytes in size • Shard key used to route queries – Choose a field commonly used in queries • Only shard key can be unique across shards – `_id` field is only unique within individual shard
- 41. Shard Key Considerations • Cardinality • Write Distribution • Query Isolation • Reliability • Index Locality
- 42. { _id: ObjectId(), user: 123, time: Date(), subject: “...”, recipients: [], body: “...”, attachments: [] } Example: Email Storage Most common scenario, can be applied to 90% cases Each document can be up to 16MB Each user may have GBs of storage Most common query: get user emails sorted by time Indexes on {_id}, {user, time}, {recipients}
- 43. Example: Email Storage Cardinality Write Scaling Query Isolation Reliability Index Locality
- 44. Example: Email Storage Cardinality Write Scaling Query Isolation Reliability Index Locality _id Doc level One shard Scatter/gat her All users affected Good
- 45. Example: Email Storage Cardinality Write Scaling Query Isolation Reliability Index Locality _id Doc level One shard Scatter/gat her All users affected Good hash(_id) Hash level All Shards Scatter/gat her All users affected Poor
- 46. Example: Email Storage Cardinality Write Scaling Query Isolation Reliability Index Locality _id Doc level One shard Scatter/gat her All users affected Good hash(_id) Hash level All Shards Scatter/gat her All users affected Poor user Many docs All Shards Targeted Some users affected Good
- 47. Example: Email Storage Cardinality Write Scaling Query Isolation Reliability Index Locality _id Doc level One shard Scatter/gat her All users affected Good hash(_id) Hash level All Shards Scatter/gat her All users affected Poor user Many docs All Shards Targeted Some users affected Good user, time Doc level All Shards Targeted Some users affected Good
- 48.
- 49. Solutions Architect, MongoDB Henrik Ingo @h_ingo Thank you!