作者：Grey
原文地址：Java8以后各版本新增特性
Java 8
JUC包中的CompletableFuture
JUC包中的WorkStealingPool
Reactor of Java
Reactor of Java 這一章來自於《Spring in Action, 5th》 的筆記，因為這本書講Reactor of Java講的太好了，所以作為筆記摘抄了下來。
Reactor of Java
In an imperative programming model, the code would look something like this:
String name = "Craig";
String capitalName = name.toUpperCase();
String greeting = "Hello, " + capitalName + "!";
System.out.println(greeting);
In the imperative model, each line of code performs a step, one right after the other, and definitely in the same thread. Each step blocks the executing thread from moving to the next step until complete. In contrast, functional, reactive code could achieve the same thing like this:
Mono.just("Craig")
.map(n -> n.toUpperCase())
.map(n -> "Hello, " + n + " !")
.subscribe(System.out::println);
The Mono in the example is one of Reactor’s two core types. Flux is the other. Both are implementations of Reactive Streams’ Publisher.
A Flux represents** a pipeline of zero, one, or many (potentially infinite) data items**.
A Mono is a specialized reactive type that’s optimized for when the dataset is known to have no more than one data item.
CREATING FROM OBJECTS
Flux<String> fruitFlux = Flux
.just("Apple", "Orange", "Grape", "Banana", "Strawberry");
fruitFlux.subscribe(f -> System.out.println("Hello " + f));
// for test
StepVerifier.create(fruitFlux)
.expectNext("Apple")
.expectNext("Orange")
.expectNext("Grape")
.expectNext("Banana")
.expectNext("Strawberry")
.verifyComplete();
CREATING FROM COLLECTIONS
Stream<String> fruitStream = Stream.of("Apple", "Orange", "Grape", "Banana", "Strawberry");
Flux<String> fruitFlux2 = Flux.fromStream(fruitStream);
fruitFlux2.subscribe(s -> System.out.println(s));
List<String> fruitList = new ArrayList<>();
fruitList.add("Apple");
fruitList.add("Orange");
fruitList.add("Grape");
fruitList.add("Banana");
fruitList.add("Strawberry");
Flux<String> fruitFlux3 = Flux.fromIterable(fruitList);
fruitFlux3.subscribe(s -> System.out.println(s));
String[] fruits = new String[] {"Apple", "Orange", "Grape", "Banana", "Strawberry" };
Flux<String> fruitFlux = Flux.fromArray(fruits);
fruitFlux.subscribe(s -> System.out.println(s));
StepVerifier.create(fruitFlux)
.expectNext("Apple")
.expectNext("Orange")
.expectNext("Grape")
.expectNext("Banana")
.expectNext("Strawberry")
.verifyComplete();
GENERATING FLUX DATA
Flux<Integer> intervalFlux =
Flux.range(1, 5);
intervalFlux.subscribe(integer -> System.out.println(integer));
StepVerifier.create(intervalFlux)
.expectNext(1)
.expectNext(2)
.expectNext(3)
.expectNext(4)
.expectNext(5)
.verifyComplete();
Flux<Long> intervalFlux =
Flux.interval(Duration.ofSeconds(1))
.take(5);
intervalFlux.subscribe(i -> System.out.println(i));
StepVerifier.create(intervalFlux)
.expectNext(0L)
.expectNext(1L)
.expectNext(2L)
.expectNext(3L)
.expectNext(4L)
.verifyComplete();
MERGING REACTIVE TYPES
Flux<String> characterFlux = Flux
.just("Garfield", "Kojak", "Barbossa")
.delayElements(Duration.ofMillis(500));
Flux<String> foodFlux = Flux
.just("Lasagna", "Lollipops", "Apples")
.delaySubscription(Duration.ofMillis(250))
.delayElements(Duration.ofMillis(500));
Flux<String> mergedFlux = characterFlux.mergeWith(foodFlux);
mergedFlux.subscribe(s -> System.out.println(s));
StepVerifier.create(mergedFlux)
.expectNext("Garfield")
.expectNext("Lasagna")
.expectNext("Kojak")
.expectNext("Lollipops")
.expectNext("Barbossa")
.expectNext("Apples")
.verifyComplete();
Flux<String> characterFlux = Flux
.just("Garfield", "Kojak", "Barbossa");
Flux<String> foodFlux = Flux
.just("Lasagna", "Lollipops", "Apples");
Flux<Tuple2<String, String>> zippedFlux =
Flux.zip(characterFlux, foodFlux);
zippedFlux.subscribe(x -> System.out.println(x));
StepVerifier.create(zippedFlux)
.expectNextMatches(p ->
p.getT1().equals("Garfield") &&
p.getT2().equals("Lasagna"))
.expectNextMatches(p ->
p.getT1().equals("Kojak") &&
p.getT2().equals("Lollipops"))
.expectNextMatches(p ->
p.getT1().equals("Barbossa") &&
p.getT2().equals("Apples"))
.verifyComplete();
Flux<String> characterFlux = Flux
.just("Garfield", "Kojak", "Barbossa");
Flux<String> foodFlux = Flux
.just("Lasagna", "Lollipops", "Apples");
Flux<String> zippedFlux =
Flux.zip(characterFlux, foodFlux, (c, f) -> c + " eats " + f);
zippedFlux.subscribe(x -> System.out.println(x));
StepVerifier.create(zippedFlux)
.expectNext("Garfield eats Lasagna")
.expectNext("Kojak eats Lollipops")
.expectNext("Barbossa eats Apples")
.verifyComplete();
SELECTING THE FIRST REACTIVE TYPE TO PUBLISH
Flux<String> slowFlux = Flux.just("tortoise", "snail", "sloth")
.delaySubscription(Duration.ofMillis(100));
Flux<String> fastFlux = Flux.just("hare", "cheetah", "squirrel");
Flux<String> firstFlux = Flux.first(slowFlux, fastFlux);
StepVerifier.create(firstFlux)
.expectNext("hare")
.expectNext("cheetah")
.expectNext("squirrel")
.verifyComplete();
FILTERING DATA FROM REACTIVE TYPES
Flux<String> skipFlux = Flux.just(
"one", "two", "skip a few", "ninety nine", "one hundred")
.skip(3);
StepVerifier.create(skipFlux)
.expectNext("ninety nine", "one hundred")
.verifyComplete();
Flux<String> skipFlux = Flux.just(
"one", "two", "skip a few", "ninety nine", "one hundred")
.delayElements(Duration.ofSeconds(1))
.skip(Duration.ofSeconds(4));
StepVerifier.create(skipFlux)
.expectNext("ninety nine", "one hundred")
.verifyComplete();
Flux<String> nationalParkFlux = Flux.just(
"Yellowstone", "Yosemite", "Grand Canyon",
"Zion", "Grand Teton")
.take(3);
StepVerifier.create(nationalParkFlux)
.expectNext("Yellowstone", "Yosemite", "Grand Canyon")
.verifyComplete();
Flux<String> nationalParkFlux = Flux.just(
"Yellowstone", "Yosemite", "Grand Canyon",
"Zion", "Grand Teton")
.delayElements(Duration.ofSeconds(1))
.take(Duration.ofMillis(3500));
StepVerifier.create(nationalParkFlux)
.expectNext("Yellowstone", "Yosemite", "Grand Canyon")
.verifyComplete();
Flux<String> nationalParkFlux = Flux.just(
"Yellowstone", "Yosemite", "Grand Canyon",
"Zion", "Grand Teton")
.filter(np -> !np.contains(" "));
StepVerifier.create(nationalParkFlux)
.expectNext("Yellowstone", "Yosemite", "Zion")
.verifyComplete();
Flux<String> animalFlux = Flux.just(
"dog", "cat", "bird", "dog", "bird", "anteater")
.distinct();
StepVerifier.create(animalFlux)
.expectNext("dog", "cat", "bird", "anteater")
.verifyComplete();
MAPPING REACTIVE DATA
Flux<Player> playerFlux = Flux
.just("Michael Jordan", "Scottie Pippen", "Steve Kerr")
.map(n -> {
String[] split = n.split("\\s");
return new Player(split[0], split[1]);
});
StepVerifier.create(playerFlux)
.expectNext(new Player("Michael", "Jordan"))
.expectNext(new Player("Scottie", "Pippen"))
.expectNext(new Player("Steve", "Kerr"))
.verifyComplete();
Flux<Player> playerFlux = Flux
.just("Michael Jordan", "Scottie Pippen", "Steve Kerr")
.flatMap(n -> Mono.just(n)
.map(p -> {
String[] split = p.split("\\s");
return new Player(split[0], split[1]);
})
.subscribeOn(Schedulers.parallel())
);
List<Player> playerList = Arrays.asList(
new Player("Michael", "Jordan"),
new Player("Scottie", "Pippen"),
new Player("Steve", "Kerr"));
StepVerifier.create(playerFlux)
.expectNextMatches(p -> playerList.contains(p))
.expectNextMatches(p -> playerList.contains(p))
.expectNextMatches(p -> playerList.contains(p))
.verifyComplete();
BUFFERING DATA ON A REACTIVE STREAM
Flux<String> fruitFlux = Flux.just(
"apple", "orange", "banana", "kiwi", "strawberry");
Flux<List<String>> bufferedFlux = fruitFlux.buffer(3);
StepVerifier
.create(bufferedFlux)
.expectNext(Arrays.asList("apple", "orange", "banana"))
.expectNext(Arrays.asList("kiwi", "strawberry"))
.verifyComplete();
Buffering values from a reactive Flux into non-reactive List collections seems counterproductive. But when you combine buffer() with flatMap(), it enables each of the List collections to be processed in parallel:
Flux.just(
"apple", "orange", "banana", "kiwi", "strawberry")
.buffer(3)
.flatMap(x ->
Flux.fromIterable(x)
.map(y -> y.toUpperCase())
.subscribeOn(Schedulers.parallel())
.log()
).subscribe();
Flux<String> fruitFlux = Flux.just(
"apple", "orange", "banana", "kiwi", "strawberry");
Mono<List<String>> fruitListMono = fruitFlux.collectList();
StepVerifier
.create(fruitListMono)
.expectNext(Arrays.asList(
"apple", "orange", "banana", "kiwi", "strawberry"))
.verifyComplete();
Flux<String> animalFlux = Flux.just(
"aardvark", "elephant", "koala", "eagle", "kangaroo");
Mono<Map<Character, String>> animalMapMono =
animalFlux.collectMap(a -> a.charAt(0));
StepVerifier
.create(animalMapMono)
.expectNextMatches(map -> {
return
map.size() == 3 &&
map.get('a').equals("aardvark") &&
map.get('e').equals("eagle") &&
map.get('k').equals("kangaroo");
})
.verifyComplete();
Performing logic operations on reactive types
Flux<String> animalFlux = Flux.just(
"aardvark", "elephant", "koala", "eagle", "kangaroo");
Mono<Boolean> hasAMono = animalFlux.all(a -> a.contains("a"));
StepVerifier.create(hasAMono)
.expectNext(true)
.verifyComplete();
Mono<Boolean> hasKMono = animalFlux.all(a -> a.contains("k"));
StepVerifier.create(hasKMono)
.expectNext(false)
.verifyComplete();
Flux<String> animalFlux = Flux.just(
"aardvark", "elephant", "koala", "eagle", "kangaroo");
Mono<Boolean> hasAMono = animalFlux.any(a -> a.contains("a"));
StepVerifier.create(hasAMono)
.expectNext(true)
.verifyComplete();
Mono<Boolean> hasZMono = animalFlux.any(a -> a.contains("z"));
StepVerifier.create(hasZMono)
.expectNext(false)
.verifyComplete();
Spring MVC change to Spring WebFlux
@GetMapping("/recent")
public Iterable<Taco> recentTacos() {
PageRequest page = PageRequest.of(
0, 12, Sort.by("createdAt").descending());
return tacoRepo.findAll(page).getContent();
}
@GetMapping("/recent")
public Flux<Taco> recentTacos() {
return Flux.fromIterable(tacoRepo.findAll()).take(12);
}
@PostMapping(consumes="application/json")
@ResponseStatus(HttpStatus.CREATED)
public Taco postTaco(@RequestBody Taco taco) {
return tacoRepo.save(taco);
}
@PostMapping(consumes="application/json")
@ResponseStatus(HttpStatus.CREATED)
public Mono<Taco> postTaco(@RequestBody Mono<Taco> tacoMono) {
return tacoRepo.saveAll(tacoMono).next();
}
public interface TacoRepository
extends ReactiveCrudRepository<Taco, Long> {
}
@GetMapping("/{id}")
public Taco tacoById(@PathVariable("id") Long id) {
Optional<Taco> optTaco = tacoRepo.findById(id);
if (optTaco.isPresent()) {
return optTaco.get();
}
return null;
}
@GetMapping("/{id}")
public Mono<Taco> tacoById(@PathVariable("id") Long id) {
return tacoRepo.findById(id);
}
WORKING WITH RXJAVA TYPES
@GetMapping("/recent")
public Observable<Taco> recentTacos() {
return tacoService.getRecentTacos();
}
@GetMapping("/{id}")
public Single<Taco> tacoById(@PathVariable("id") Long id) {
return tacoService.lookupTaco(id);
}
Developing Reactive APIs
@Configuration
public class RouterFunctionConfig {
@Autowired
private TacoRepository tacoRepo;
@Bean
public RouterFunction<?> routerFunction() {
return route(GET("/design/taco"), this::recents)
Testing reactive controllers 279
.andRoute(POST("/design"), this::postTaco);
}
public Mono<ServerResponse> recents(ServerRequest request) {
return ServerResponse.ok()
.body(tacoRepo.findAll().take(12), Taco.class);
}
public Mono<ServerResponse> postTaco(ServerRequest request) {
Mono<Taco> taco = request.bodyToMono(Taco.class);
Mono<Taco> savedTaco = tacoRepo.save(taco);
return ServerResponse
.created(URI.create(
"http://localhost:8080/design/taco/" +
savedTaco.getId()))
.body(savedTaco, Taco.class);
}
}
Test Reactive Rest APIs
// Test Get Method
Taco[] tacos = {
testTaco(1L), testTaco(2L),
testTaco(3L), testTaco(4L),
testTaco(5L), testTaco(6L),
testTaco(7L), testTaco(8L),
testTaco(9L), testTaco(10L),
testTaco(11L), testTaco(12L),
testTaco(13L), testTaco(14L),
testTaco(15L), testTaco(16L)};
Flux<Taco> tacoFlux = Flux.just(tacos);
TacoRepository tacoRepo = Mockito.mock(TacoRepository.class);
when(tacoRepo.findAll()).thenReturn(tacoFlux);
WebTestClient testClient = WebTestClient.bindToController(
new DesignTacoController(tacoRepo))
.build();
testClient.get().uri("/design/recent")
.exchange()
.expectStatus().isOk()
.expectBody()
.jsonPath("$").isArray()
.jsonPath("$").isNotEmpty()
.jsonPath("$[0].id").isEqualTo(tacos[0].getId().toString())
.jsonPath("$[0].name").isEqualTo("Taco 1").jsonPath("$[1].id")
.isEqualTo(tacos[1].getId().toString()).jsonPath("$[1].name")
.isEqualTo("Taco 2").jsonPath("$[11].id")
.isEqualTo(tacos[11].getId().toString())
.jsonPath("$[11].name").isEqualTo("Taco 12").jsonPath("$[12]")
.doesNotExist().jsonPath("$[12]").doesNotExist();
// Test POST Method
TacoRepository tacoRepo = Mockito.mock(
TacoRepository.class);
Mono<Taco> unsavedTacoMono = Mono.just(testTaco(null));
Taco savedTaco = testTaco(null);
savedTaco.setId(1L);
Mono<Taco> savedTacoMono = Mono.just(savedTaco);
when(tacoRepo.save(any())).thenReturn(savedTacoMono);
WebTestClient testClient = WebTestClient.bindToController(
new DesignTacoController(tacoRepo)).build();
testClient.post()
.uri("/design")
.contentType(MediaType.APPLICATION_JSON)
.body(unsavedTacoMono, Taco.class)
.exchange()
.expectStatus().isCreated()
.expectBody(Taco.class)
.isEqualTo(savedTaco);
// Testing with a live server
@RunWith(SpringRunner.class)
@SpringBootTest(webEnvironment=WebEnvironment.RANDOM_PORT)
public class DesignTacoControllerWebTest {
@Autowired
private WebTestClient testClient;
@Test
public void shouldReturnRecentTacos() throws IOException {
testClient.get().uri("/design/recent")
.accept(MediaType.APPLICATION_JSON).exchange()
.expectStatus().isOk()
.expectBody()
.jsonPath("$[?(@.id == 'TACO1')].name")
.isEqualTo("Carnivore")
.jsonPath("$[?(@.id == 'TACO2')].name")
.isEqualTo("Bovine Bounty")
.jsonPath("$[?(@.id == 'TACO3')].name")
.isEqualTo("Veg-Out");
}
}
Consume Reactive APIs
Flux ingredients = WebClient.create()
.get()
.uri("http://localhost:8080/ingredients")
.retrieve()
.bodyToFlux(Ingredient.class);
ingredients.subscribe(i -> { ...})
Flux<Ingredient> ingredients = WebClient.create()
.get()
.uri("http://localhost:8080/ingredients")
.retrieve()
.bodyToFlux(Ingredient.class);
ingredients
.timeout(Duration.ofSeconds(1))
.subscribe(
i -> { ... },
e -> {
// handle timeout error
})
//Handing errors
ingredientMono.subscribe(
ingredient -> {
// handle the ingredient data
...
},
error-> {
// deal with the error
...
});
Mono<Ingredient> ingredientMono = webClient
.get()
.uri("http://localhost:8080/ingredients/{id}", ingredientId)
.retrieve()
.onStatus(HttpStatus::is4xxClientError,
response -> Mono.just(new UnknownIngredientException()))
.bodyToMono(Ingredient.class);
Java 9
VarHandler
無法用單個下划線作為變量名稱
int _ = 3; // java9 or above , error
String a = Objects.requireNonNullElse(m,"Bc"); // 若m不為null，則a = m，若m為null，則a = "Bc"
-cp, -classpath, --class-path(Java9新增)
Multi-Release JAR Files
--release
--class-path instead of -classpath
--version instead of -version
--module-path option has a shortcut -p
更多，見jeps
Java8中，接口可以有靜態方法的默認實現，例：
public interface Test {
public static void print() {
System.out.println("interface print");
}
default void pout() {
System.out.println();
}
}
Java9中，可以支持private的靜態方法實現。
public interface Test {
private static void print() {
System.out.println("interface print");
}
static void pout() {
print();
}
}
Optional.ofNullable(date).orElseGet(() -> newDate()); // date為null，才會執行newDate()方法，否則不執行newDate()方法
Optional.ofNullable(date).orElse(newDate()); // 無論date是否為null，都會執行newDate()方法
Java7中，可以使用try-with-Resources
try(Resouce res = ...) {
work with res
}
res.close()會被自動執行
例：
try (var in = new Scanner(new FileInputStream("C:\\Users\\Young\\Desktop\\新建文件夾\\1.tx.txt"), StandardCharsets.UTF_8);
var out = new PrintWriter("C:\\Users\\Young\\Desktop\\新建文件夾\\out.txt", StandardCharsets.UTF_8)) {
while (in.hasNext()) {
out.println(in.next().toUpperCase());
}
}
in 和 out執行完畢后都會自動關閉資源
在Java9 中，你可以在try中預先聲明資源
例：
public static void printAll(String[] lines, PrintWriter out) {
try (out) { // effectively final variable
for (String line : lines) {
out.println(line);
} // out.close() called here
}
}
StackWalker用法示例
public class App {
/**
* Computes the factorial of a number
*
* @param n a non-negative integer
* @return n! = 1 * 2 * . . . * n
*/
public static int factorial(int n) {
System.out.println("factorial(" + n + "):");
var walker = StackWalker.getInstance();
walker.forEach(System.out::println);
int r;
if (n <= 1) {
r = 1;
} else {
r = n * factorial(n - 1);
}
System.out.println("return " + r);
return r;
}
public static void main(String[] args) {
try (var in = new Scanner(System.in)) {
System.out.print("Enter n: ");
int n = in.nextInt();
factorial(n);
}
}
}
Java 9 expands the use of the diamond syntax to situations where it was previously not accepted. For example , you can now use diamonds with anonymous subclasses.
ArrayList<String> list = new ArrayList<>(){
@Override
public String get(int index) {
return super.get(index).replaceAll(".","*");
}
};
Java 10
無需定義變量類型，通過var關鍵字+初始化的值，可以推測出變量類型
var a = 2; // a表示int
var b = "hello"; // b 表示String
var date = new java.util.Date();
var obj = new Custome(); // 自定義對象
Java 11
String repeated = "Java".repeat(3); // 三個Java字符串連接
JDK提供了jdeprscan 來檢查你的代碼是否使用了deprecated的方法
專題
Lambda Expression
| Method Reference | Equivalent Lambda Expression | Notes |
|---|---|---|
| separator::equals | x -> separator.equals(x) | This is a method expression with an object and an instance method. The lambda parameter is passed as the explicit parameter of the method |
| String::trim | x -> x.trim() | This is a method expression with a class and an instance method. The lambda parameter becomes the explicit parameter of the method |
| String::concat | (x, y) -> x.concat(y) | Again, we have an instance method, but this time, with an explicit parameter. As before, the first lambda parameter becomes the implicit parameter, and the remaining ones are passed to the method |
| Integer::valueOf | x -> Integer::valueOf(x) | This is a method expression with a static method. The lambda parameter is passed to the static method |
| Integer::sum | (x, y) -> Integer::sum(x, y) | This is another static method, but this time with two parameters. Both lambda parameters are passed to the static method. The Integer.sum method was specifically created to be used as a method reference. As a lmbda, you could just write (x, y)->x + y |
| Integer::new | x -> new Integer(x) | This is a constructor reference. The lambda parameters are passed to the constructor |
| Integer[]::new | n -> new Integer[n] | This is an array constructor reference. The lambda paramter is the array length |
| Functional Interface | Parameter Types | Return Types | Abstract Method Name | Description | Other Method |
|---|---|---|---|---|---|
| Runnable | none | void | run | Runs an action without arguments or return value | |
| Supplier
|
none | T | get | Supplies a value of type T | |
| Consumer
|
T | void | accept | Consumes a value of type T | andThen |
| BiConsumer<T,U> | T,U | void | accept | Consumes value of types T and U | andThen |
| Function<T,R> | T | R | apply | A function with argument of type T | compose, andThen, identity |
| BiFunction<T,U,R> | T,U | R | apply | A function with arguments of types T and U | andThen |
| UnaryOperator
|
T | T | apply | A unary operator on the type T | compose, andThen, identity |
| BinaryOperator
|
T,T | T | apply | A binary operator on the type T | andThen, maxBy, minBy |
| Predicate
|
T | boolean | test | A boolean-valued function | and, or, negate, isEqual |
| BiPredicate<T,U> | T,U | boolean | test | A boolean-valued function with two argumnets | and,or,negate |
Functional interfaces for Primitive Types
p, q is int ,long double; P, Q is Int, Long, Double
| Functional Interface | Parameter Types | Return Types | Abstract Method Name |
|---|---|---|---|
| BooleanSupplier | none | boolean | getAsBoolean |
| PSupplier | none | p | getAsP |
| PConsumer | p | void | accept |
| ObjPConsumer
|
T,p | void | accept |
| PFunction
|
p | T | apply |
| PToQFunction | p | q | applyAsQ |
| ToPFunction
|
T | p | applyAsP |
| ToPBiFunction<T,U> | T,U | p | applyAsP |
| PUnaryOperator | p | p | applyAsP |
| PBinaryOperator | p,p | p | applyAsP |
| PPredicate | p | boolean | test |
Service Loaders
Proxies
Logging
Generic Programming
- E for the element type of a collection
- K and V for key and value type of a table
- T(and the neighboring letters U and S, if neccessary) for "any type at all"
Pair<String> a = new Pair<>("A", "B");
Pair<Double> b = new Pair<>(1.1, 1.11);
System.out.println(a.getClass() == b.getClass()); // TRUE
in Java8
public static <T> Pair<T> makePair(Supplier<T> constr) {
return new Pair<>(constr.get(), constr.get());
}
Pair<String> p = Pair.makePair(String:new);
In general, there is no relationship between Pair<S> and Pair<T>, no matter how S and T are related.
BUT
var managerBuiddies = new Pair<Manager>(ceo, cfo);
Pair<? extends Employee> buddies = managerBuddies;
Collections
Concurrency
Stream
Java 8
// 流操作
List<Integer> list = new ArrayList<>();
list.add(1);
list.add(2);
list.parallelStream().filter(i -> i > 1).count();
list.stream().filter(i -> i > 1).count();
Stream<String> words = Stream.of(contents.split(","));
// 創建流
var limits = new BigInteger("1000");
Stream<BigInteger> integerStream = Stream.iterate(BigInteger.ZERO, n -> n.compareTo(limits) < 0, n -> n.add(BigInteger.ONE));
System.out.println(integerStream.count());
如果我們持有的iterable對象不是集合，那么可以通過下面的調用將其轉換成一個流
StreamSupport.stream(iterable.spliterator(),false);
如果我們持有的是Iterator對象，並且希望得到一個由它的結果構成的流，那么可以使用下面的語句
StreamSupport.stream(Spliterators.spliteratorUnknowSize(iterator, Spliterator.ORDERED),false);
至關重要的是，在執行流的操作時，我們並沒有修改流背后的集合。記住，流並沒有收集其數據，數據一直存儲在單獨的集合中
Optional
String result = optionalString.orElse(""); // The wrapped string , or "" if none
String result = optionalString.orElseGet(() -> System.getProperty("myapp.default"));
String result = optionalString.orElseThrow(IllegalStateException::new);
消費Optinal值
optionalValue.ifPresent(v -> result.add(v));
optionalValue.ifPresentOrElse(v -> System.out.println("Found" + v),
()-> logger.warning("no match"));
管道化Optional
Optional<String> transformed = optionalString.filter(s -> s.length() >= 8).map(String::toUpperCase);
in Java9
// 如果optionalString的值存在，那么result為optionalString，如果值不存在，那么就會計算lambda表達式，並使用計算出來的結果
Optional<String> transformed = optionalString.or(() -> alternatives.stream().findFirst());