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MongoDB Basic Concepts
This document provides an overview and introduction to key MongoDB concepts including: - Replication which allows for failover, backups, and high availability through asynchronous replication across replica sets. - Sharding which provides horizontal scalability by automatically distributing and balancing data across multiple shards in a cluster. - Consistency and durability models including eventual consistency and different write acknowledgement options for ensuring data is safely written. - Flexibility in data modeling through embedding and linking of related data as well as the use of JSON which maps easily to objects.
MongoDB Basic Concepts
- 1. MongoDB Basic Concepts NorbertoLeite Senior Solutions Architect, 10gen
- 2. Agenda • Overview • Replication •Scalability • Consistency & Durability • Flexibility / Developer Experience 2
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- 6. Norberto Leite Senior SolutionsArchitect @nleite / norberto@10gen.com 6
- 7. Norberto Leite Senior Solutions Architect @nleite/ norberto@10gen.com Barcelona 7
- 8. Norberto Leite Senior Solutions Architect @nleite/ norberto@10gen.com Barcelona Love MongoDB 8
- 9. Norberto Leite Senior Solutions Architect @nleite/ norberto@10gen.com Barcelona Love MongoDB and others ... 9
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- 13. Fundamentals Document Application High Oriented { Performance name: ‘Norberto Leite’, position: ‘SA’, nick: ‘WingMan’, based: [‘Barcelona’, ‘London’] } mongoDB mongoDB mongoDB mongoDB Fully Consistent Horizontal Scalability 13
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- 15. Why do weneed Replication? • Failover • Backups • Secondary Batch Jobs • High Availability 15
- 16. Outages • Planned – Hardware upgrade – OS or file-system tuning – Software upgrade – Relocation of data to new file-system / storage • Un-planed – Human Error – Hardware Failure – Data Center / Region Outage – Application Corruption 16
- 17. Replica Sets • DataProtection – Multiple copies of data – Data spread across data centers, AZ’s etc • High Availability – Automated Failover – Automated Recovery 17
- 18. Asynchronous Replication App Write Primary Read (default) Secondary Read (optional) Secondary Read (optional)
- 19. Failover App Write Primary Read (default) Secondary Read (optional) Secondary Read (optional)
- 20. Automatic Failover Primary Election App Primary Write Primary Read (default) Secondary Read (optional)
- 21. Automatic Recovery App Read Recovery Secondary (optional) Write Primary Read (default) Secondary Read (optional)
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- 23. Sharding • Data LocationTransparent to Code • Data Distribution is Automatic – as well as re-distribution • Aggregation System resources Horizontally • No CODE Changes!!! 23
- 24. sh.shardCollection("test.tweets", {_id: 1}, false) Range Distribution shard01 shard02 shard03 a-i j-m n-z
- 25. Chunk Split shard01 shard02 shard03 a-i ja-jz j-m n-z ka-kj k-m ki-m
- 26. Auto Balancing shard01 shard02 shard03 a-i ja-jz j-m n-z ka-kj ki-m
- 27. Routed db.tweets.find( {_id: Queries ‘norberto’}) shard01 shard02 shard03 a-i ja-jz j-m n-z ka-kj ki-m
- 28. db.tweets.find( {email: ‘norberto@10gen’}) Scatter Gather shard01 shard02 shard03 a-i ja-jz j-m n-z ka-kj ki-m
- 29. Caching 96 GB Mem 3:1 Data/Mem shard01 a-i 300 GB Data j-r n-z 300 GB
- 30. Horizontal Distribution 96 GB Mem 96 GB Mem 96 GB Mem 1:1 Data/Mem 1:1 Data/Mem 1:1 Data/Mem shard01 shard02 shard03 a-i a-i j-r n-z 300 GB Data 100 GB 100 GB 100 GB
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- 32. Consistency • Eventual Consistency – Allow updates when a system as been partitioned – Resolve conflicts later – Ex: Cassandra, CouchDB • Immediate Consistency – Single Master – Avoids conflicts – Example: MongoDB 32
- 33. Durability • For howlong is my data available? • When do I know my data is safe?! • Where is it safe? • MongoDB style: – Fire and Forget – Get Last Error – Journal Sync – Replica Safe 33
- 34. Durability Multiple Data Centers Memory Journal Secondary Nodes RDMS Async w=1 (default) j=true w=majority w=”tag” 34
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- 36. Data Model • WhyJson? – Well understood data format – Maps simply to objects – Linking & Embedding to describe relationships 36
- 37. JSON place1 = {: "578 Broadway 7th Floor", name : "10gen HQ", address city : "New York", zip "business", "tech" ]} : "10011", tags : [ }
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- 39. MongoDB Way embedding linking
- 40. JSON & ScaleOut • Embedding removes the need for: – Distributed Joins – Two Phase Commit • Enables data to be distributed across many nodes without penalty 40