A Pragmatic View of Reactive at ScalaDays Amsterdam

Slides from my talk at ScalaDays 2015 in Amsterdam.

Transcript

1. So how do I do a 2PC in Akka then? or Lutz Hühnken (@lutzhuehnken) A Pragmatic View of Reactive
2. So how do I do a 2PC in Akka then? Lutz Hühnken (@lutzhuehnken) A misleading title, really. Answer: You don’t want to (we’ll get back to that later)
3. Valuable Experience vs. Bad Habit From Enterprise to Reactive Transitions … Lutz Hühnken (@lutzhuehnken) Other failed naming attempts..
4. Lutz Hühnken (@lutzhuehnken) A Pragmatic View of Reactive
6. Yes, of course. But who doesn’t claim that for their system?
7. Come on. Now you’re just selling Akka to me..
8. Real, Pragmatic Questions WAR? Servlet Container? Library X (which uses ThreadLocal) ? RDBMS/ JDBC? How to do 2PC?
9. Pragmatic Problem Fields Deployment Concurrency Model I/O Distribution
10. The Pragmatic Reactive Manifesto
11. Threads vs. task level concurrency
12. Pragmatic Reactive Threads … A supposedly great idea • Threads are • lightweight processes • easier programming model, no IPC 12
13. Pragmatic Reactive Lightweight? 13 Slide from John Rose, Java VM Architect, JFokus, Stockholm, February 2015
14. Pragmatic Reactive The problem with Threads 14 They discard the most essential and appealing properties of sequential computation: understandability, predictability, and determinism. Threads, as a model of computation, are wildly nondeterministic, and the job of the programmer becomes one of pruning that nondeterminism.
15. + Let’s talk about Multi-Threading Every time…
16. Pragmatic Reactive Threads • not efficient • memory consumption • cost for context switch • bad match modern NUMA architectures • locks lead to contention
 • not a good programming model • shared mutual state is difficult to reason about 16
17. Pragmatic Reactive What would be better? Goals • task level (sub-thread) concurrency • share nothing approach • # threads ~ # of cores 17
18. Pragmatic Reactive Thread alternatives (successors?) • Green threads / coroutines / fibres • other granularity, but basically same programming model • Event-loop (e.g. vert.x, Reactor) • very loose coupling, slightly limited, 1 x n dispatch • Actors ! • truly share-nothing, flexible, resilience-proven, 
 m x n dispatch 18
19. Pragmatic Reactive Example: Http Request handling Java EE: Threads. Servlet API: Thread per Request 19 Note: This is a snapshot at one point in time, not a sequence of events.
20. Pragmatic Reactive Example: Http Request handling Reactive: Sub-Thread. Play: n threads per m requests 20 Note: This is a snapshot at one point in time, not a sequence of events.
21. Pragmatic Reactive Consequences • We have effectively (even without explicitly using Actors) switched to a task level concurrency model • As a consequence, ThreadLocal becomes an anti-pattern. • Libraries that depend on them need extra work, might better be avoided • What does it mean for (blocking) I/O? 21
22. Pragmatic Reactive Pragmatic reactive learnings cont’d • You’ll be using sub-thread level concurrency. Accept it, embrace it. 22
23. Blocking vs. non-blocking I/O
24. Pragmatic Reactive High concurrency matters 24 But there’s one thing we can all agree on: At high levels of concurrency (thousands of connections) your server needs to go to asynchronous non-blocking. [..] any part of your server code blocks you’re going to need a thread. And at these levels of concurrency, you can’t go creating threads for every connection. From https://strongloop.com/strongblog/node-js-is-faster-than-java/
25. Pragmatic Reactive Blocking I/O Reactive: Sub-Thread. Play: n threads per m requests 25 What does using blocking I/O mean for this?
26. Pragmatic Reactive Non-blocking 26 For task level (sub-thread level) concurrency • each thread is responsible for n tasks • and that n might be pretty big You don’t want to block such a thread with blocking I/O
27. Pragmatic Reactive But what if I need this..? 27 try { stmt = con.createStatement(); ResultSet rs = stmt.executeQuery(query); while (rs.next()) { String coffeeName = rs.getString("COF_NAME"); int supplierID = rs.getInt("SUP_ID"); float price = rs.getFloat("PRICE"); int sales = rs.getInt("SALES"); int total = rs.getInt("TOTAL"); System.out.println(coffeeName + "\t" + supplierID + "\t" + price + "\t" + sales +
28. Pragmatic Reactive Isolate! 28 vert.x has „worker verticles“ Play/Akka: Configure Dispatchers Slick 3 takes care of this for you!
29. Pragmatic Reactive Pragmatic reactive learnings cont’d • You’ll be using sub-thread level concurrency. Accept it, embrace it. • Use asynchronous I/O. If you really can’t, isolate. 29
30. „Distributed Transactions“ vs. Distributed Systems
31. Pragmatic Reactive But what if I need this..? 31 @Transactional public static class GreetingService { @Inject private JmsTemplate jmsTemplate; @PersistenceContext private EntityManager entityManager; public void createGreeting(String name) { Greeting greeting = new Greeting(name); this.entityManager.persist(greeting); this.jmsTemplate.convertAndSend("greetings", greeting); …
32. Pragmatic Reactive Avoid, separate, recycle.. 32
33. Pragmatic Reactive Avoid… 33 @Transactional public static class GreetingService { @Inject private JmsTemplate jmsTemplate; @PersistenceContext private EntityManager entityManager; public void createGreeting(String name) { Greeting greeting = new Greeting(name); this.entityManager.persist(greeting); this.jmsTemplate.convertAndSend("greetings", greeting); … The example: In fact not really all-or-nothing, but reconciliation.
34. Pragmatic Reactive Separate (the steps..) 34 Claim: Any 2PC can be expressed in terms of asynchronous messaging.
35. Pragmatic Reactive Life beyond Distributed Transactions 35 In general, application developers simply do not implement large scalable applications assuming distributed transactions. When they attempt to use distributed transactions, the projects founder because the performance costs and fragility make them impractical. [..]
36. 36 Want Almost-Infinite Scaling
 • More of everything… Year by year, bigger and bigger • If it fits on your machines, multiply by 10, if that fits, multiply by 1000… • Strive to scale almost linearly (N log N for some big log). Assumptions
 (Don’t Have to Prove These… Just Plain Believe Them) Grown-Ups Don’t Use Distributed Transactions •The apps using distributed transactions become too fragile… • Let’s just consider local transactions. ! Multiple disjoint scopes of serializability Want Scale-Agnostic Apps
 • Two layers to the application: 
 scale-agnostic and scale-aware • Consider scale-agnostic API Scale Agnostic Code Scale-Aware-Code Application Upper Layer Lower Layer Scale Agnostic API
37. Pragmatic Reactive 2 PC => messaging 37 Item-B Cancellation Tentative Op Item-A Restrictions / Requirements •at-least-once delivery •idempotent messages •tentative operations
38. Pragmatic Reactive Pragmatic 38 Real world solution: Saga Pattern Source: http://kellabyte.com/2012/05/30/clarifying-the-saga-pattern/
39. Pragmatic Reactive Pragmatic 39 Example (by Caitie McCaffrey) Source: https://speakerdeck.com/caitiem20/applying-the-saga-pattern
40. Pragmatic Reactive Distributed Transactions 40 Distributed Transactions („2PC“) are a source of unnecessary failure and of contention. It can usually be avoided. Generally, local transactions and at-least-once delivery can be used instead. The Saga Pattern provides a pragmatic solution for „all-or- nothing“ in a distributed system.
41. Pragmatic Reactive Food for thought 41 The data storage landscape is changing, moving towards event sourcing and immutability. This is a great match for reactive systems. The „all-or-nothing“ problems are closely related to wanting a global truth at a point in time. But what is now… the illusion of present… result of series of events..
42. Pragmatic Reactive Pragmatic reactive learnings cont’d • You’ll be using sub-thread level concurrency. Accept it, embrace it. • Use asynchronous I/O. If you really can’t, isolate. • Do not use distributed transactions. If you really must, isolate. 42
43. App Servers vs. Standalone
44. Pragmatic Reactive 44
45. Pragmatic Reactive 45
46. Pragmatic Reactive Java EE Application Servers 46 Servlet API was developed for thread-per- request, synchronous I/O. Application servers are not of much use anyway, nobody uses them as containers for multiple applications. So effectively they’re just a library dependency. The ops convenience can be provided by other tools.
47. Pragmatic Reactive Pragmatic reactive learnings cont’d • You’ll be using sub-thread level concurrency. Accept it, embrace it. • Use asynchronous I/O. If you really can’t, isolate. • Do not use distributed transactions. If you really must, isolate. • Don’t use an application server / servlet container. 47
48. Summary
49. Pragmatic Reactive Conclusion 49 If • Threads are the smallest unit of concurrency in your code, or • You use blocking I/O (without clear separation), or • You use 2-phase-commit across systems, or • You use a Java EE Application Server / Servlet Container Then your application is not reactive.
50. Pragmatic Reactive The Pragmatic Reactive Checklist 50 • Task-level (sub-thread level) concurrency • Non-blocking I/O • Distributed • Containerless
51. Reactive Manifesto revisited
52. We really only talked about the elastic part
53. will lead to will lead to
54. Thank you Lutz Hühnken (@lutzhuehnken)