Cqrs but different
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When many developers think of Command-Query Responsibility Segregation (CQRS), they envision separate datastores for reads and writes, linked together by some kind of event-based synchronization mechanism. The reality is that for many domains this is overkill, while for others it still doesn’t solve fundamental concurrency issues.
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Cqrs but different
- 1. CQRS but different Udi Dahan @udidahan in Particular
- 4. Why people think they need it Scalability Simpler code Everybody’s talking about it
- 5. Slave N Scalability – DB Master/Slave Master Client Library Slave 2 Slave 1 async master to slave replication
- 6. Scalability – Partitioning Dividing data across multiple DB instances Requires some level of application knowledge
- 7. Scalability – Sharding Like partitioning, but not on a natural key
- 8. The logical deployment architecture Client DB Server
- 9. … or even Client DB Simpler code?
- 14. Domain-Driven Design Value Objects Anti-corruption layers components Subdomains & Bounded Contexts
- 15. Starting up in the UI
- 16. … and going all the way down UI BL DAL DB API
- 17. … and finally beyond layers Lightweight ServiceBus (pub/sub) BC1 BC2 BC3 NoSqlSql Shards
- 18. SOA EDA MVC Pipes & Filters REST DDD Layers CQRS What to use when?
- 20. Where things can go wrong High contention domains
- 21. … on the most popular items
- 22. Regular logic starts to choke begin transaction var quantity = select Q from Inventory where Id = @ProdId if (quantity >= quantityRequested) update Inventory set Q = quantity – quantityRequested where Id = @ProdId commit transaction
- 23. … and the connection pool to dry up
- 24. Resulting in terrible wait times for everybody
- 25. Regular CQRS might fall behind too
- 26. What’s great about Event Sourcing non-blocking, append-only data model
- 27. Business needs to get flexible
- 28. Append-only data models with simple querying too ProductID Delta TimeStamp 5 -1 08:35:22 6-3-2015 5 -1 08:35:27 6-3-2015 5 -3 08:42:12 6-3-2015 5 +250 08:43:06 6-3-2015 5 -2 10:36:22 6-3-2015 5 -5 17:25:54 6-3-2015 5 -3 18:02:37 6-3-2015 select sum(Delta) where …
- 29. Add snapshotting for compaction ProductID Delta TimeStamp 5 +235 18:03:06 6-3-2015 begin transaction select @q = sum(Delta), TimeStamp <= 5.min.ago from Inventory where Id = @ProdId delete from Inventory where Id = @ProdId and TimeStamp <= 5.min.ago insert into Inventory @ProdId, @q, now() commit transaction
- 30. The logical deployment architecture Client DB Server Simple – isn’t it?
- 32. Want to learn more?
- 33. Thank you Udi Dahan @udidahan in Particular
Notes de l'éditeur
- © 2003 Microsoft Corporation. All rights reserved. This presentation is for informational purposes only. Microsoft makes no warranties, express or implied, in this summary.
- Supported by MySQL, Postgres
- Yes, yes, all the security guys are having a fit right now, but you will have firewalls and intrusion detection systems and the network level between them.
- But we’ll get back to this on the topic of architecture.
- For the love of all that is good and holy – stop worrying about layers.
- Value objects – money, measurements (length, temperature), CC expiry date
- Each software project is like a different custom meal you’re preparing.
- Multiple users operating on the same data at the same time
- Multiple users operating on the same data at the same time
- How do we keep the quantity consistent when multiple users are doing this in parallel? We need to lock the record even at the time of the query.
- Multiple users operating on the same data at the same time
- But if the business still tries to enforce high consistency – it won’t work.
- The way Amazon emails you back afterwards saying – sorry, your order will be delayed. So – do we really need to check inventory at the instant that somebody orders? But once this happens, you can greatly simplify your architecture back down.
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