An introduction to Scala, Functional Programming, and concurrency patterns that I gave to a class of students at Houghton College on November 2, 2014

1. Functional Programming &
Concurrency Patterns
Tim Kellogg (@kellogh)
September 2, 2014

2. Agenda
• Introduce 2lemetry & IoT technologies
• Introduce Scala
• Functional Programming
• Concurrency patterns

3. About Me
• 39.9747597,-105.0881511
• Class of 2007

4. Internet of Things
• Moving
• Storing
• Analyzing
• Reacting

5. MQTT
• Message Queue Telemetry Transport
• Pub/Sub binary protocol
• Open standard
• Persistent connections

6. IoT-SQL
SELECT LAST(*)
FROM mqtt(‘co.t/temp/+’) AS temp
JOIN storage(‘metadata’) AS md
ON temp.deviceId = md.id
WHERE temp.outside.value > 90
AND temp.inside.value < 70
GROUP BY 1 HOUR

7. We need…
• To move quickly, be agile, adapt to changes
• Performant code
• To leverage concurrency
• To rent server space in the cloud

8. • Functional + Object Oriented
• Strongly typed
– Safe
– Not like Java types
• JVM

9. • First-class functions
• Traits
• Type inference
• Record types (case classes)
• Pattern Matching (and structural typing)

10. Record Types

11. Pattern Matching

12. First class functions

13. First Class Functions

14. Example:
Count all goals from young players

15. Example: Count Goals

16. Example: Count Goals

17. Example: Count Goals

18. Example: Count Goals

19. Example: Count Goals

20. Example: Count Goals

21. Example: Count Goals

22. Example: Count Goals

23. Example: Count Goals

24. Example: Count Goals

25. Example: Count Goals

26. FP Mainstream References
• SQL
• LINQ (C#)
• jQuery
• Hadoop (map / reduce)
– Spark

27. Monads

29. Common Monads
• List[T]
• Set[T]
• Option[T]  No more nulls
• Future[T]
• Try[T]

30. Monads
• Container
• “bind” operation
– “flatMap” in Scala
– T => M[U]

31. List[T] As A Monad

32. Option[T] As A Monad

33. Option[T] As Monad

34. List[T] As A Monad

35. List[T] As A Monad

36. Concurrency

37. Concurrency Basics
• If it’s immutable, it’s thread-safe
• Locks are hard to reason about
• Badly placed locks defeat concurrency

38. Multi-threading vs Concurrent
• Concurrent
– An architecture
– Not necessarily multi-threaded

39. Immutability: What You Can’t Do
• Change a variable
• Write to a file
• Write to a TCP socket

40. Haskell Is
Useless
Simon Peyton Jones
https://www.youtube.com/
watch?v=iSmkqocn0oQ

41. Side Note: Reference Immutability
• https://homes.cs.washington.edu/~csgordon/
papers/oopsla12.pdf
• M#
• Rust

42. Immutability: What You Can Do
• State Monad
• IO Monad
• Future Monad
• Forget about concurrency details

43. Role of Monads
• Represent state as a value
• Declarative programming
– Describe the problem
– Let the compiler solve it for you

44. Future[T]
• Represents a value
• Handles failure as a value
• Computation might happen on another thread
• Supervisors

45. Future[T]
• map / filter
• flatMap (bind)
• successful (pure)

46. Future[T]

47. Future[T] - Dispatchers
• Thread pooling
• Configuration

48. Actors

49. Actors
• Akka (Scala)
• OTP (Erlang)
• http://arxiv.org/pdf/1008.1459.pdf
• “Sandboxing” mutability & side effects

50. Actor Model of Computation

51. Actor Mailbox

52. Akka

53. Akka Specialization
• Actors  Computation
• Dispatchers  Thread pooling
• Supervisors  Reliability
• Routers  Concurrency