reactive programming for java developers – rossen stoyanchev – qcon

For more QCon posts, see my live blog table of contents.

General notes

  • Spring 5 has reactive features.
  • Maybe a third of the audience is doing something with reactive, a little more have read about it (that’s me) and a lot haven’t heard of it. Which is good given the title of this talk!
  • Moore’s law slowing down. No more free lunch from the hardware
  • Now apps more distributed/independent/cloudbased compared to 10 years ago
  • Now we expect latency
  • Thread now has to do more async things. Hit limits of scale. imperative logic more complicated.

Other approach

  • Async/non-blocking
  • Use very few threads. node.js has a single thread. Must be careful because blocking those few threads blocks the whole app
  • Reactive programming – think async. Not everything is a callback

Comparing styles

  • Imperative
    • call a method, get a result, do something with that result
  • Async
    • return a Future instead of a value. Don’t throw a checked exception because my happen in a different thread. They are asynchronous in that you can get a result later. But when you eventually call feature.get(), it throws different checked exceptions.
    • In Java 8, can return a CompletableFuture and call future.whenComplete((user, throwable) -> {})
    • If doing a findAll(), the future/completable future approach doesn’t give you a callback/return anything until all of them are ready. You can’t stream or could run out of memory.
    • Async results as stream – get one notification per data item and another for completion or error
  • Declarative
    • Focus on what, not how
    • Declare what should happen rather than focusing on callbacks
    • Java 8 stream API uses this style. It is meant for collections and pull based/usable once
    • Hot streams – latency sensitive streams, data need to be pushed for you
    • Cold streams – pull based

Reactive libraries

  • Stream like API
  • Can be used for hot/cold streams
  • Project Reactor – Similar to ReactiveX, easy to bridge to Java 8 streams. (ReactiveX is like XUnit – commonality for different languages)

Abstractions

  • Flux – sequence of 0 to n – equivalent of Java 8 stream – can convert to/from Java 8
  • Mono – sequence of 0 or 1 – can convert to/from CompletableFuture

Reactive streams spec

  • Back pressure – producers must not overwhelm consumers. Communicates if downstream isn’t ready for more items. Ex: a slow client like a mobile device isnt able to handle more data and server isn’t blocking
  • Small API – only 4 interfaces
  • Rules
  • Interoperability across reactive components so can compose chain

Java 9

  • Reactive streams included (the four interfaces)
    • Publisher
    • Subscriber
    • Subscription
    • Processor
  • Use a reactive library. Don’t implement the four interfaces yourself
  • subscribe() triggers the flow of data
  • “push” was missing until now. Want in JDK to have foundation
  • Classes
    • java.util.concurrent.Flow – the four interfaces
    • SubmissionPublisher – bridge to reactie streams
    • Tie-ins to CompletableFuture and Stream

Reactor

  • GA release scheduled for July
  • Currently called 2.5. Might changed to 3.0

Reactive Spring MVC

  • Apps annotate controllers even now.
  • Return a Flux type.
  • Spring MVC itself needs to change a lot – called Spring Web Reactive
  • The servlet API assumes blocking. There are async workarounds. Servlet 4.0 might support reactive spring integration, but probably just the basics. Using own bridge to Servlet 3.1 in meantime.
  • Can still use Jetty/Tomcat. They are non-blocking behind the scenes.
  • Don’t need servlet container. Can use Netty.
  • HandlerMapping – change to return a Mono so can be non-blocking
  • Focusing on REST/microservices scenarios

Other reactive efforts

  • MongoDB – reactive driver
  • Couchbase – reactive driver
  • Thymeleaf – split templates into chunks and throttle to respect backpressure

applying java 8 idioms to existing code – trisha gee – qcon

For more QCon posts, see my live blog table of contents. Last year, she talked about creating new apps in Java 8. This year is about migrating to Java 8 for “legacy” code. She showed specific JetBrains IDEA features. I just took notes on the concepts that are IDE agnostic. Presentation will be at bit.ly/refJ8

Usage from audience poll

  • About half compile with Java 7
  • About half compile with Java 8
  • About a quarter (half of Java 8 people)  compile with Java 8, but apps still looks like Java 7

Why use Java 8

  • Performance improvements in common data structure
  • Fork/Join speed improvements
  • Changes to support concurrency
  • Fewer lines of code – less boilerplate
  • New solutions to problems – more elegant/easier to write code
  • Minimize errors – ex: Optional avoids NullPointerException

Before refactoring

  • Make sure have high test coverage
  • Focus on method level changes – tests should still work
  • Have performance tests too to ensure not negatively impacting system
  • Decide on goals – performance? clearer code? easier to write new code? easier to read new code? use lambdas because team used to it? developer morale?
  • Limit the scope – small incremental commits. Don’t make change that will affect whole code base.

Straightforward refactoring of lambda expressions

  • Predicate, Comparator and Runnable are common places where might have used anonymous inner classes and can switch to lambdas
  • IDEs suggest where can replace code with lambdas (SonarLint does as well)
  • Quick win – reduce old boilerplate
  • [She didn’t talk about this, but it will make your code coverage go down. Make sure your management doesn’t worry about that!]
  • Lose explicit type information when use lambda. Might want to extra to method to make it clearer and call the method from the lambda.

Abstract classes – candidates for lambdas

  • See if can use an interface (if single abstract method) so can start using lambdas
  • Tag with @FunctionalInterface to make clearer
  • Then look at implementers (especially anonymous inner classes) and see if can convert to lambda expressions

Conditional logging

  • if (debug) { log.debug() } pattern is a good candidate for logging
  • Often people forget to add that conditional so opportunity to defer evaluation for those too via search/replace. Also, protects against conditional not matching log level. if (debug)  { log.severe() }. Uh oh!
  • Use a default method on the existing logging interface that takes a supplier instead of a String and has the if check

Collections and Streams API

  • Turn for loops into collect() or forEach()
  • Remember you can call list.forEach() directly without going through a stream
  • If do something like get rid of initial list size, test performance before and after to make sure not a needed optimization
  • The automatic streams refactoring might not result in shorter code. Think about whether the surrounding code wants to be refactored as well. A more dramatic refactoring. Go back to later. Also, avoid refactoring if and else code since not  a simple filter.
  • Remember to include method references when converting code too
  • Watch for surrounding code. For example, if sorting a list, move into the the stream. Or if iterating over new list, add as a forEach instead of turning into a list.

Optional

  • Be careful. Refactor locally.
  • Easy to accidentally change something that requires changing a ton of code.

Performance

  • Lambdas expressions don’t necessarily perform better than anonymous inner classes. Similarly for streams.
  • Using lambdas to add conditional logging is a big quick win performance improvement.
  • Streams didn’t need the “initial size of list” optimization
  • Adding parallel() to stream operations sometimes performs better and sometimes worse. Simple operation often performs worse in parallel because of overhead of parallelizing.
  • Introducing Optionals increases cost.

Java 7 refactorings

  • Use static imports
  • Reudndant type in diamond operator for generics

how the OCA Java Programmer certification compares to AP Computer Science A

I gave a presentation to high schoolers about the OCA Java Programmer I certification. I was asked over email how well the AP (Advanced Placement) Computer Science class provides the foundational info for the OCA cert:
My main question is wondering how close within reach the java certification would be and how useful it would be to students.  From what you said, the value of having the cert is very good.  But, I’m still wondering about how much additional work will be required to achieve a good result.  I understand your point about needing study materials etc,-  that’s all a given and something that today’s students are very used to doing (PSAT, SAT, ACT, AP, CLEP, etc.).  But, do you expect that generally an AP Computer Science course would provide the foundational info needed to pass the test, and then the student just needs practice to be proficient and quick?
I took AP Computer Science over 15 years ago. It wasn’t in Java and a lot has changed. So I looked at the College Board’s Computer Science course description to find out. I also learned that AP Computer Science AB no longer exists.
AP Computer Science vs the OCA
The OCA exam is meant to cover the basics. In some ways, the AP exam goes beyond that. For example, the AP exam covers recursion. There are a few things covered on the OCA that don’t appear to be covered on the AP exam:
  • Exceptions – checked exceptions, throw/throws, try/catch block
  • StringBuilder
  • byte, char, float and long
  • Wrapper classes
  • Importing other Java packages
  • Garbage collection
  • Overloaded methods
  • Java 8 date/time
  • Java 8 lambdas/predicates
  • Plus a few things that I’m not clear as to whether they are on the AP
    • Ternary operators
    • Switch statements
    • Break/continue

All of these is easily learned through a study guide so I think a student preparing for the AP exam is in good shape to pick of an OCA certification study guide.

Plus it is likely the student’s class is using a book which was not intended for the narrower scope of the AP exam. Which means the student would have come across some of the above anyway.