1. Functional Leap of
Faith
Tomer Gabel, Wix
JDay Lviv 2014

2. Through the Looking Glass
20 years ago…
• C/C++ rule the
market [1]
• First release of Java
[1] TIOBE Index (historical data)

3. … since then?*
• C and Java are neck-and-neck
• Virtual machines are everywhere
• Garbage collection is everywhere
• OOP is everywhere
* Not exhaustive

4. Virtual Machines
1967 BCPL
1978 UCSD p-System
1994 JVM
2014 Everywhere!

5. Garbage Collection
1960 Formalized[1]
1970s Research
1994 JVM
2014 Everywhere!
[1] Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I

6. Object-Oriented Programming
1967 Simula 67
1980 Smalltalk 80
1983 C++
2014 Everywhere!

7. Advances take
decades to become
mainstream

8. Market Growth[1]
3000
2500
2000
1500
1000
500
0
1975 1980 1985 1990 1995 2000 2005 2010 2015* 2020*
Units (Millions)
[1] eTForecasts Worldwide PC Market Research Report

9. 3000
2500
2000
1500
1000
500
0
1975 1980 1985 1990 1995 2000 2005 2010 2015* 2020*
Units (Millions)
Market Growth
• Structured Programming
• Module Systems
• Dynamic Memory Allocation

10. 3000
2500
2000
1500
1000
500
0
1975 1980 1985 1990 1995 2000 2005 2010 2015* 2020*
Units (Millions)
Market Growth
• Garbage Collection
• OOP
• VMs and JIT

11. 3000
2500
2000
1500
1000
500
0
1975 1980 1985 1990 1995 2000 2005 2010 2015* 2020*
Units (Millions)
Market Growth
You are here!

12. What’s holding us
back?

13. The Market has Shifted
• SaaS is the norm
• Shorter time to
market
• Latency requirements
are stricter
• Availability is
business-critical

14. The Free Lunch is Over[1]
[1] The Free Lunch is Over, Herb Stutter (Dr. Dobb's Journal, 2005)
• CPUs aren’t getting
(much) faster
• Rather, they’re getting
parallel
• Concurrency is the
new kid on the block

15. Datasets are Getting Bigger
• Terabyte-scale data is
common
• Computation demand
– NoSQL
– Big Data
• Specialized hardware
(SAN) is a hindrance

16. We need new
abstractions.

17. Three desirable
attributes:

18. Today’s systems
are highly available & reliable.
Tomorrow’s abstraction must…
encourage correct code.

19. Complexity is the Mind Killer
• Complex system  bigger codebase
• More code  more bugs
• We want less code
• We want correct code

20. Control flow  Data flow
We need to invert our thinking.

21. How  What
We need to invert our thinking.

22. Control flow describes the
how
List<Person> adults(List<Person> in) {
ArrayList<Person> out = new ArrayList<>();
for (Person p : in)
if (p.getAge() >= 18)
out.add(p);
return out;
}

23. Data flow describes the what
List<Person> adults(List<Person> in) {
return in.stream()
.filter(p -> p.age >= 18)
.collect(Collectors.toList());
}

24. “What” is Better
• Focuses on the
problem
• Reduces accidental
complexity
• Decouples intent from
execution

25. Today’s systems
are highly concurrent.
Tomorrow’s abstraction must…
encourage immutability.

26. The Case for Immutability
• Inherently thread-safe
• Referentially
transparent
• Easier to reason
about!

27. Today’s systems
are horizontally scalable.
Tomorrow’s abstraction must…
simplify workload distribution.

28. Distribution 101
1. Take a core
computation
2. Split it out
3. Run on many nodes
4. Profit

29. Why is this hard?
• Behavior-as-data
• Side effects
• High-performance
frameworks
 Lambdas
 Immutability
 Akka, Hadoop,
Storm…

30. The future is
functional.
1. Data flow-oriented
2. Immutable
3. Easy to distribute

31. tomer@tomergabel.com
@tomerg
http://il.linkedin.com/in/tomergabel
THANK YOU FOR YOUR TIME!