2010 mongo berlin-shardinginternals (1)
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This document summarizes MongoDB sharding, which allows scaling horizontally for data size, index size, write load, and consistent read load. It distributes databases, collections, or individual objects across shards in a cluster. Sharding can be configured to partition data by range, user ID, photo ID, or other fields. Operations like insert, update, query, and sorting of data are routed to shards based on the shard key. The architecture involves mongos routers, config servers, and shards made up of replica sets for redundancy. Sharding can be enabled on an existing database and collections can be sharded while the system remains online.
2010 mongo berlin-shardinginternals (1)
- 1. Eliot Horowitz @eliothorowitz MongoBerlin October 4, 2010 Sharding Internals
- 2. MongoDB Sharding Scale horizontally for data size, index size, write and consistent read scaling Distribute databases, collections or a objects in a collection Auto-balancing, migrations, management happen with no down time
- 3. Choose how you partition data Can convert from single master to sharded system with no downtime Same features as non-sharding single master Fully consistent
- 4. Range Based collection is broken into chunks by range chunks default to 200mb or 100,000 objects
- 5. User profiles Partition by user_id Secondary indexes on location, dates, etc... Reads/writes know which shard to hit
- 6. User Activity Stream Shard by user_id Loading a user’s stream hits a single shard Writes are distributed across all shards Can index on activity for deleting
- 7. Photos Can shard by photo_id for best read/write distribution Secondary index on tags, date
- 8. Logging date machine, date logger name Possible Shard Keys
- 9. Architecture client mongos ... mongos mongod mongod mongodddd mongod mongod mongod ... Shards mongod mongod mongod Config Servers
- 10. Config Servers 3 of them changes are made with 2 phase commit if any are down, meta data goes read only system is online as long as 1/3 is up
- 11. Shards Can be master, master/slave or replica sets Replica sets gives sharding + full auto-failover Regular mongod processes
- 12. mongos Sharding Router Acts just like a mongod to clients Can have 1 or as many as you want Can run on appserver so no extra network traffic
- 13. Writes Inserts : require shard key, routed Removes: routed and/or scattered Updates: routed or scattered
- 14. Queries By shard key: routed sorted by shard key: routed in order by non shard key: scatter gather sorted by non shard key: distributed merge sort
- 15. Operations split: breaking a chunk into 2 migrate: move a chunk from 1 shard to another balancing: moving chunks automatically to keep system in balance
- 16. Setting it Up Start servers add shards: db.runCommand( { addshard : "10.1.1.5" } ) turn on partitioning: db.runCommand( { enablesharding : "test" } shard a collection: db.runCommand( { shardcollection : "test.data" , key : { num : 1 } } )
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