These are Java ways of functional style; pragmatic ways of understanding and introducing Lambda/Functional API. 你可以在以下找到中文說明： http://www.codedata.com.tw/java/jdk8-functional-api/

1. JDK8 Functional API
Justin Lin caterpillar@openhome.cc http://openhome.cc
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2. Agenda
•Lambda in 10 mins
•Lambda & Refactoring
•Stream...
•Reduction
•Parallelism
•A little Monad
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3. Lambda in 10 mins
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4. •Anonymous class
•Lambda expressions with no argument
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5. •Lambda expressions with arguments
•Type inference
JDK8 built-in functional interface
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6. •Target typing
•Method reference
•Default method
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7. Lambda & Refactoring
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8. •The most beneficial way of using lambdas is introducing them into your existing code base.
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9. •Introduce a method.
Finding tracks over one minute
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10. Collecting names from each track
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11. Filtering tracks over a minute and collecting to a List
Mapping tracks to names and collecting to a Set
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12. An Intermediate operation, why don't we chain them together?
Filtering tracks over a minute, mapping tracks to names and collect to a Set
Well, what's stream?
We may just use
map(Track::getName)
instead.
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13. Stream...
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14. •The stream method returns a Stream instance, not a new collection.
•The filter or map method returns a Stream instance, too.
•The collect(toSet()) returns a Set<String> instance as a result.
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15. •The Stream instance draw data from the source, could be a collection, an array, a generator function, or an I/O channel.
–collection.stream()
–Arrays.stream(array)
–Files.lines(Paths.get(fileName))
–…
•An intermediate operation, such as filter, produces a new Stream instance.
•A terminal operation, such as forEach, produces a non-stream result.
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16. •Intermediate operations are lazy…
•You don't have to close streams provided by JDK8 except Files.line, list and walk.
•Compared with the eager way.
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17. •Why does Stream's findFirst return Optional?
•Maybe there's no the first one … Why not null?
•Which method of Stream returns Optional?
–Optional<T> findAny()
–Optional<T> findFirst()
–Optional<T> max(Comparator<? super T> comparator)
–Optional<T> min(Comparator<? super T> comparator)
–Optional<T> reduce(BinaryOperator<T> accumulator)
Null sucks.
Doug Lea
I call it my billion- dollar mistake.
Tony Hoare
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18. •Whether an Optional instance containing a value or not is optional, so make appropriate checks to avoid bugs.
•Creating an Optional instance…
–Optional.empty()
–Optional.of(value)
–Optional.ofNullable(value)
•Getting the value orXXX?
–T orElseGet(Supplier<? extends T> other)
–T orElseThrow(Supplier<? extends X> expsp)
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19. •Checking by yourself?
•Invoking the specified consumer if a value is present.
•Invoking the specified consumer if the value matches the given predicate.
NoSuchElementException if no value.
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20. •Wait! I see wired method signatures in previous examples….Supplier, Consumer, Predicate…What're those types?
•Important functional interfaces used time and time again in JDK8.
Interface
Arguments
Returns
Consumer<T>
T
void
Function<T, R>
T
R
Predicate<T>
T
boolean
Supplier<T>
none
T
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21. •Consumer<T>
accept
T
void
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22. •Function<T, R>
–Sub interface: UnaryOperator<T>
•Predicate<T>
apply
T
R
apply
T
T
test
T
boolean
Predicate
Function
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23. •Supplier<T>
•Fail fast examples if an Optional instance contains no value.
•Avoiding performance overhead.
get
none
T
NoSuchElementException
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24. •To avoid performance overheads, the streams library has primitive versions. They have a clear- cut naming convention.
•Streams for primitives.
–IntStream
–LongStream
–DoubleStream
•Functional interfaces for primitives.
–XxxConsumer
–XxxPredicate
–XxxSuppiler
–XxxToOooFunction
accept
xxx
void
test
xxx
boolean
getAsXxx
none
xxx
applyAsOoo
xxx
ooo
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25. •Functional interfaces for mapping objects and primitives.
–XxxFunction<R>
–ToXxxFunction<T>
•Several functional interfaces starts with Bi- prefix. Take BiConsumer<T, U> for an example.
apply
xxx
R
applyAsXxx
T
xxx
accept
(T, U)
void
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26. Reduction
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27. •How long of all long tracks?
•Reduce? Sometimes it's called as fold(left).
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28. •The max length?
•Reduction operations
–Terminal operations that return one value by reducing the contents of a stream.
–(Reduce, fold or combine, whatever you call it.)
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29. •How to reduce the elements of a stream to a more complex object, such as a collection?
•Using collect methods…
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30. •The Collectors.toXxx method, such as toSet, doesn't return a Set but a Collector.
•The Collectors provides factory methods for creating out-of-box Collector …
•Grouping …
•Grouping and mapping …
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31. •Grouping and reducing …
•Grouping and averaging …
•The stream library picks an appropriate implementation for you.
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32. •You might wish to collect your values into a specific Collection.
•Implementing your own Collector…
–supplier、accumulator、combiner、 finisher
Creating a new mutable result container
Reducing a value into a mutable result container
Accepting two partial results and merging them
Performing an optional final transform on the container
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33. •Implementing your own Collector, a simple example …
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34. Parallelism
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35. •Concurrency
–Two tasks are making progress at overlapping time periods.
•Parallelism
–Two tasks are happening at literally the same time.
Task 1
Task 2
Core 1
Core 2
Task 1 Task 2
Core 1
Core 2
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36. •Changing a single method call…
•Making an operation execute in parallel…
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37. •The Java runtime performs a concurrent reduction if …
–The stream is parallel.
–The Collector has the characteristic Collector.Characteristics.CONCURRENT
–Either the stream is unordered, or the Collector has the characteristic Collector.Characteristics.UNORDERED.
•Built-in concurrent-supported collector
–groupingByConcurrent
–toConcurrentMap
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38. •Ordering…
•The combining function must be associatve when preforming concurrent reduction…
–1 + 3 + 8 + 9 + 2 + 5 + 4 + 6 + 7
–(1 + 3) + 8 + (9 + 2) + 5 + (4 + 6 + 7)
–1 + (3 + 8 )+ 9 + 2 + (5 + 4 + 6 + 7)
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39. •Interference
•Performance
–Data size、source data structure、number of cores、cost per element …
•Simply speaking…
–Executing in parallel without worrying about tools doesn't mean there is a free lunch.
Don't do this!!
ConcurrentModifiedException
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40. A little Monad
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41. •Hey, you forget this … why not refactoring it?
•Yes! Coming now … But …
What's flatMap?
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42. •The idea of flatMap is from Monad …
•Monad? Let's google it ….
•Great! something can be eaten … XD
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43. •A suggestion: getting started from map and flatMap of Optional …
•The map method can change the following …
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44. •If your getXXX methods return Optional, you can change the following …
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45. •Monad in Java 8 ?
–Optional
–Stream
–CompletableFuture
•Several starting points …
–http://openhome.cc/Gossip/Java/FlatMap.html
–http://www.codedata.com.tw/java/jdk8- completablefuture/
–http://www.slideshare.net/mariofusco/monadic-java
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46. Summary
•Functional? You've done that when you are …
–Refactoring your existing code …
–Applying filter, map, reduce …
–Returning Optional instead of null …
–Considering issues of parallelism when using parallel tools, such as parallelStream …
–Or even using those monadic API of Java 8 …
•These are Java ways of functional style; pragmatic ways of understanding and introducing Lambda/Functional API
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47. Exercise:
–Completing Chapter 1
–Using functional API to refactor Customer again
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MonsterSupreme
Lambda 就是 重構(重構(程式碼))
Lambda is a way to refactor refactored code

48. References
•http://shop.oreilly.com/product/0636920030713.do
•http://www.amazon.com/Refactoring-Improving- Design-Existing-Code/dp/0201485672
•http://docs.oracle.com/javase/tutorial/collections/streams/index.html
•http://docs.oracle.com/javase/tutorial/collections/streams/reduction.html
•http://openhome.cc/Gossip/Java/FlatMap.html
•http://www.codedata.com.tw/java/jdk8- completablefuture/
•http://www.slideshare.net/mariofusco/monadic-java
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49. Thanks!!
Justin Lin caterpillar@openhome.cc http://openhome.cc
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