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• Terse
• Object keyword - Singleton
• Companion Objects
• Type inference
• Option[T] – Some[T], None](https://image.slidesharecdn.com/indicthreads-pune12-typesafestacksoftwaredevelopmentonthejvm-121217123149-phpapp01/85/Indic-threads-pune12-typesafe-stack-software-development-on-the-jvm-16-320.jpg)
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Indic threads pune12-typesafe stack software development on the jvm
The document covers the evolution of software and hardware architecture from the single-core era to multi-core systems, emphasizing the challenges of parallel programming and concurrency. It discusses the properties of modern applications, the advantages of Scala as a hybrid functional and object-oriented language, and introduces Akka for concurrent and scalable systems. Various Scala features, such as immutability, actor models, and integration with Play framework for web applications, are also highlighted.
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Indic threads pune12-typesafe stack software development on the jvm
- 1. Typesafe Stack Software DevelopmentOn The JVM Sushanta Pradhan Talentica Software (I) Pvt. Ltd.
- 2. History of HardwareArchitecture • Single core era • moore's law achieved by increasing clock cycles • Multi core era • moore's law achieved by increasing # of cores
- 3.
- 4. PPP – GrandChallenge • Parallel programming as easy as sequential programming • Moores’s law of performance – speed up 2 times year on year • Eliminate concurrency bugs
- 5. History of softwareapplications • pre .com era • standalone desktop apps • .com era • web sites - static web pages, automated business processes • data controlled by software vendor • deployed on data centers
- 6. contd .. • web2.0/semantic web era • web/networked applications • Smart apps • data not controlled by vendor but by the users • deployed on cloud
- 7. Properties of modernday App • Scalability • Distributed • Parallel & Concurrent • Dynamic • Agile & Swift
- 8. Parallelism & Concurrency • Parallel Programming • parallel execution of programs • can't be performed without parallel hardware • programs get faster
- 9. Parallelism & Concurrency • Concurrent Programming • simultaneous execution of programs • can be performed without parallel hardware • programs get more responsive Both are too hard !!
- 10. Why Hard? • non-determinism due to shared mutable state by concurrent threads • encapsulate state in actors or transactors but fundamental problems still remains non-determinism = parallel processing + mutable state
- 11. Remedy? PREVENTION IS BETTER THAN CURE !! • Avoid mutable state and get deterministic processing • Which means program functionally
- 12. Space vs Time Space(functional/parallel) Time(imperative/concurrent)
- 13. Scala • Hybrid – functional & object oriented (pure) • strong static typing • Agile - concise & expressive • Parallel & Sequential • intermixes well with Java
- 14. Scala contd .. Parallellism • parallel collections • distributed collections Concurrency • Actors • STM Akka • Futures
- 15. Scala contd .. • Concise Java • Immutability Val & Var • Tuples & Multiple Assignments • Sensible Defaults • Operator Overloading
- 16. Scala classes .. • Terse • Object keyword - Singleton • Companion Objects • Type inference • Option[T] – Some[T], None
- 17.
- 18. Scala – FunctionalAspects • Functions too are objects • Higher Order Functions • Partially applied Functions • Closures
- 19. Scala Inehritance • Traits • Mixins • Type inference - implicit keyword
- 20. Scala collections • Mutable & immutable • filter() • Map() • foldLeft() • foldRight()
- 21. Scala – PatternMatching • Advanced switch case • Literals and constants • WildCards • Tuples & Lists • Guards • Regular Expressions
- 22. Scala - Concurrency • actor() • Actor Class • receive() & recieveWithin() • react() & reachWithin() • loop() & loopwhile()
- 23. Akka - Middleware • Concurrent, Scalable & fault-tolerant • based on actor model • highly performant • event driven • location transparency
- 24. Actor system • ensemble of actors sharing common configuration • hierarchical structure • heavyweight • has its own pool of resources threads
- 25. Supervision • dependency relationship between actors • supervisor - subordinate model • supervisor monitors and reacts to any errors reported by subordinates • configurable supervision strategy • lifecycle monitoring
- 26. Supervision hierarchy ”root guardian” ”guardian” shutdown “system guardian” order
- 27. Remoting • ActorPath • purely local - "akka://my-sys/user/service-a/worker1" • local or remote - "akka://my-sys@host.example.com:5678 /user/service-b" • Seamlessly send messages to actors on remote nodes
- 28. Routing • route messages to actors(routees) • ideal for load balancing • Examples • RoundRobinRouter • RandomRouter • SmallestMailboxRouter • BroadcastRouter
- 29. Dispatchers • make akka actors tick • manages the resources(threads) used by actors • configure mailboxes of actors • Examples • fork-join-executor • thread-pool-executor
- 30. Play • ruby on rails like agility • convention over configuration • seamless integration with akka for scalability • edit and test
- 31. Play contd .. • an easy, out-of-the-box setup for unit and functional testing • asynchronous HTTP request handling • WebSocket support • cache support (e.g. memcached) • integrated JSON and XML handling
- 32. Progressive Stream Processing • Iteratees • Enumerators • Enumeratees
- 33.