1. open-source, high-performance,
document-oriented database

2. Why Sharding
• Vertical scaling is limited by physics and
cost
• Hard to scale vertically in the cloud
• Can scale wider than higher

3. What is Sharding
• ad-hoc partitioning
• consistent hashing (Dynamo)
• range based partitioning (BigTable/PNUTS)

4. Overview
• Automatic partitioning and management
• range based
• Can convert from single master to sharded
system with 0 downtime
• Almost no functionality lost over single
master
• Fully consistent

5. Range Based
• collection is broken into chunks by range

6. Auto-sharding
Shards
mongo mongo mongo
..
Config mongo mongo mongo
Servers
mongod
mongod
mongod
mongos mongos ..
client

7. 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

8. Shards
• Can be master, master/slave or replica sets
• Replica sets gives sharding + full auto-
failover
• Regular mongod processes

9. 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

10. Writes
• Inserts : require shard key, routed
• Removes: routed and/or scattered
• Updates: routed or scattered

11. 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

12. Operations
• split: breaking a chunk into 2
• migrate: move a chunk from 1 shard to
another

13. Balancing
• distributes chunks automatically
• can look at: disk ops, cpu, data size

14. Multi DataCenter
• intelligent geo honing
• auto failover

15. Sharding Limitations
• Unique indexes not based on shard key
• current version limited to ~ 20 petabytes

16. After Party!
Download MongoDB
http://www.mongodb.org
and let us know what you think
@eliothorowitz @mongodb