Landelijk Architectuur Congres - The dark side of event sourcing: managing data conversion

Landelijk Architectuur Congres - The dark side of event sourcing: managing data conversion

Evolving software systems includes data schema changes, and because of those schema changes data has to be converted. Data conversion in event sourced systems introduces new challenges, because of the relative novelty of the event sourcing architectural pattern, because of the lack of standardized tools for data conversion, and because of the large amount of data that is stored in typical event stores. We addresses the challenge of schema evolution and the resulting data conversion for event sourced systems.

03dc1d993fa7d5de422c1f35d53f80e6?s=128

Michiel Overeem

November 15, 2018
Tweet

Transcript

  1. The Dark Side of Event Sourcing: Managing Data Conversion Michiel

    Overeem, Marten Spoor, Slinger Jansen M. Overeem, M. Spoor, and S. Jansen, “The Dark Side of Event Sourcing: Managing Data Conversion,” in IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), 2017, pp. 193–204.
  2. Event sourcing 101 accountId balance owner 1234567 0 Michiel Current

    state Event sourcing Event BankAccountCreated (accountId: 1234567, balance: 0, owner: Michiel) M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  3. Event sourcing 101 accountId balance owner 1234567 100 Michiel Current

    state Event sourcing Event BankAccountCreated (accountId: 1234567, balance: 0, owner: Michiel) DepositPerformed (accountId : 1234567, amount: 100, balance: 100) M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  4. Event sourcing 101 Event BankAccountCreated (accountId: 1234567, balance: 0, owner:

    Michiel) DepositPerformed (accountId : 1234567, amount: 100, balance: 100) WithdrawalPerformed (accountId: 1234567, amount: 50, balance: 50) accountId balance owner 1234567 50 Michiel Current state Event sourcing M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  5. Event sourcing 101 Event BankAccountCreated (accountId: 1234567, balance: 0, owner:

    Michiel) DepositPerformed (accountId : 1234567, amount: 100, balance: 100) WithdrawalPerformed (accountId: 1234567, amount: 50, balance: 50) OwnerChanged (accountId: 1234567, newOwner: Marten) accountId balance owner 1234567 50 Marten Current state Event sourcing M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  6. Sure, but this is normal for transactions …

  7. Event sourcing 101 Event ShoppingCartCreated (cartid: 1234567, user: Michiel) cartid

    articles user 1234567 0 Michiel Current state Event sourcing M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005. cartid article
  8. Event sourcing 101 Event ShoppingCartCreated (cartid: 1234567, user: Michiel) ArticleAddedToCart(cartid:

    1234567, article: Lumia 950) cartid articles user 1234567 1 Michiel Current state Event sourcing cartid article 1234567 Lumia 950 M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  9. Event sourcing 101 cartid articles user 1234567 0 Michiel Current

    state Event sourcing cartid article Event ShoppingCartCreated (cartid: 1234567, user: Michiel) ArticleAddedToCart(cartid: 1234567, article: Lumia 950) ArticleRemovedFromCart(cartid: 1234567, article: Lumia 950) M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  10. Event sourcing 101 cartid articles user 1234567 1 Michiel Current

    state Event sourcing cartid article 1234567 iPhone X Event ShoppingCartCreated (cartid: 1234567, user: Michiel) ArticleAddedToCart(cartid: 1234567, article: Lumia 950) ArticleRemovedFromCart(cartid: 1234567, article: Lumia 950) ArticleAddedToCart(cartid: 1234567, article: iPhone X) M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  11. Event sourcing 101 cartid articles user 1234567 1 Michiel Current

    state Event sourcing cartid article 1234567 iPhone X Event ShoppingCartCreated (cartid: 1234567, user: Michiel) ArticleAddedToCart(cartid: 1234567, article: Lumia 950) ArticleRemovedFromCart(cartid: 1234567, article: Lumia 950) ArticleAddedToCart(cartid: 1234567, article: iPhone X) M. Fowler, “Event sourcing,” http://martinfowler.com/eaaDev/EventSourcing.html, 2005.
  12. Command Query Responsibility Segregation (CQRS) 101 The command side is

    only responsible for data modifications. It does not return data. The query side only reads and returns data, it does not modify it. Events make sure that data modifications are propogated to the query-side. G. Young, “CQRS and Event Sourcing,” http://codebetter.com/gregyoung/2010/02/13/cqrs-and-event-sourcing, 2010.
  13. Command Query Responsibility Segregation (CQRS) 101 These events could be

    communicated through an servicebus. But they could also be stored as an append-only log. G. Young, “CQRS and Event Sourcing,” http://codebetter.com/gregyoung/2010/02/13/cqrs-and-event-sourcing, 2010.
  14. Why event sourcing In the era of cloud platforms and

    microservices, events are the way of communication. Storing those events improves the 1. anticipation on new business requirements, and 2. continuation of the operation of the platform.
  15. Shining light on the dark side Practitioners often just follow

    ▪CQRS and Event Sourcing are trending, and sometimes even seen as silver bullets. ▪Many practitioners start out without reviewing the consequences. ▪The community often gives simple answers without taking the context into account. RQ: How can an event sourced system be upgraded efficiently when the (implicit) event schema changes?
  16. Challenges for upgrades of event sourced systems • More data

    than traditional current view. • No standardized language (like SQL) that helps in expressing transformations. And in a cloud platform: • Zero-downtime is needed for data transformations
  17. Research approach ▪ We have created an inventory of the

    operations that can be used to transform the event store, ▪ We mapped the operations onto techniques that can execute those, ▪ The techniques are linked to strategies, that in turn can be used to deploy the data transformations. The framework is validated with three renowned experts. Part of it is implemented as an exploration. Combined with Deployed with Executed by Executed by Data upgrade Application upgrade Lazy transformation Upcasting In place transfor- mation Multiple versions Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Expand- Contract Blue- Green Deployed with
  18. Basic Event Operations Complex Event Operations Basic Stream Operations Complex

    Stream Operations Basic Store Operations Complex Store Operations Store Backaccount Stream #1234567 BankAccountCreated DepositPerformed WithdrawalPerformed Operations
  19. The framework Combined with Deployed with Executed by Executed by

    Data upgrade Application upgrade Lazy transformation Upcasting In place transfor- mation Multiple versions Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Expand- Contract Blue- Green Deployed with At the top an inventory of operations.
  20. Multiple versions Techniques Multiple versions of an event type are

    supported throughout the application. D. Betts, J. Dominguez, G. Melnik, F. Simonazzi, and M. Subramanian, Exploring CQRS and Event Sourcing: A journey into high scalability, availability, and maintainability with Windows Azure. Microsoft patterns & practices, 2013.
  21. Multiple versions Techniques Multiple versions of an event type are

    supported throughout the application. Axon Framework, “Reference Guide Axon Framework reference guide - Event Upcasting.” 2016. Upcasting Introduce a central component that transforms an event before offering it to the application.
  22. Multiple versions Techniques Multiple versions of an event type are

    supported throughout the application. P. J. Sadalage and M. Fowler, NoSQL distilled: a brief guide to the emerging world of polyglot persistence. Addison-Wesley, 2012. Upcasting Introduce a central component that transforms an event before offering it to the application. Lazy transformation Store the result of the transformation permanently in the event store.
  23. Multiple versions Techniques Multiple versions of an event type are

    supported throughout the application. S. Scherzinger, M. Klettke, and U. Störl, “Cleager: Eager Schema Evolution in NoSQL Document Stores,” Datenbanksysteme f{ü}r Business, Technol. und Web (BTW), 16. Fachtagung des GI-Fachbereichs “Datenbanken und Informationssysteme” (DBIS), Upcasting Introduce a central component that transforms an event before offering it to the application. Lazy transformation Store the result of the transformation permanently in the event store. In place transformation A batch job that eagerly reads the data, transforms it, and writes the updated data back to the database.
  24. Multiple versions Techniques Multiple versions of an event type are

    supported throughout the application. M. Callaghan, “Facebook - Online Schema Change for MySQL,” 2010. https://www.facebook.com/notes/mysql-at-facebook/online-schema- change-for-mysql/430801045932/. Upcasting Introduce a central component that transforms an event before offering it to the application. Lazy transformation Store the result of the transformation permanently in the event store. In place transformation A batch job that eagerly reads the data, transforms it, and writes the updated data back to the database. Copy and transformation Copies and transforms every event to a new store.
  25. Multiple versions Techniques Multiple versions of an event type are

    supported throughout the application. M. Callaghan, “Facebook - Online Schema Change for MySQL,” 2010. https://www.facebook.com/notes/mysql-at-facebook/online-schema- change-for-mysql/430801045932/. Upcasting Introduce a central component that transforms an event before offering it to the application. Lazy transformation Store the result of the transformation permanently in the event store. In place transformation A batch job that eagerly reads the data, transforms it, and writes the updated data back to the database. Copy and transformation Copies and transforms every event to a new store.
  26. The framework Combined with Deployed with Executed by Executed by

    Data upgrade Application upgrade Lazy transformation Upcasting In place transfor- mation Multiple versions Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Expand- Contract Blue- Green Deployed with Techniques that execute the identified operations: ▪ at run-time or at deploy-time, ▪ through schema evolution or schema versioning.
  27. Expand-Contract Strategies Three phase change: first expand, then update all

    concumers, then contract. D. Sato, “ParallelChange,” 2014. http://martinfowler.com/bliki/ParallelChange.html.
  28. Expand-Contract Strategies Three phase change: first expand, then update all

    concumers, then contract. J. Humble and D. Farley, Continuous delivery: reliable software releases through build, test, and deployment automation. Addison-Wesley Professional, 2010. Blue-Green Use two slots for deployment and toggle between them.
  29. Expand-Contract Strategies Three phase change: first expand, then update all

    concumers, then contract. T. Dumitras, P. Narasimhan, and E. Tilevich, “To Upgrade or Not to Upgrade Impact of Online Upgrades across Multiple Administrative Domains,” ACM SIGPLAN Not., vol. 45, no. 10, pp. 865–876, 2010. Blue-Green Use two slots for deployment and toggle between them. Rolling upgrade Upgrade machine for machine.
  30. Expand-Contract Strategies Three phase change: first expand, then update all

    concumers, then contract. E. A. Brewer, “Lessons from Giant-Scale Services,” {IEEE} Internet Comput., vol. 5, no. 4, pp. 46–55, 2001. Blue-Green Use two slots for deployment and toggle between them. Rolling upgrade Upgrade machine for machine. Big Flip Flip the switch after updating half the machines.
  31. Framework ▪ An upfront design and decision support tool, to

    design the upgrade system of your platform Combined with Deployed with Executed by Executed by Data upgrade Application upgrade Lazy transformation Upcasting In place transfor- mation Multiple versions Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Expand- Contract Blue- Green Deployed with
  32. Expert interviews Three dutch experts (all have +6 years experience,

    and are part of the international community) were interviewed. • Naming issues came up • Frequency of operations was discussed • Technical versus functional immutability “You are maybe the only one, who has such an overview and also thought about edge cases, which I hope never to encounter. ” “Event sourcing needs a lot of upfront thought, which is hard to do with agile development. ”
  33. Framework ▪ By implementing two lanes, an automated upgrade system

    can be built. Combined with Deployed with Executed by Executed by Data upgrade Application upgrade Upcasting Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Blue- Green Deployed with
  34. Reach us at michiel.overeem@afas.nl Event sourcing is the pattern for

    SaaS platforms, because it does not lose data that is found to be useful later on. But more research is needed to formulate effective strategies on implementing event sourcing.