Future用来获取某个并发操作的结果，这个结果可以同步（阻塞）或异步（非阻塞）的方式访问。
执行上下文
Future 需要一个ExecutionContext, 它与java.util.concurrent.Executor 很相像. 如果你在作用域内有一个 ActorSystem , 它可以用system.dispatcher()作 ExecutionContext。你也可以用ExecutionContext 伴生对象提供的工厂方法来将 Executors 和 ExecutorServices 进行包裹, 或者甚至创建自己的实例.
//执行上下文可以自己指定线程池类型 ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool())
Future的创建方法 Futuref1 = Futures.successful("f1", ec); Future f2 = Futures.future(new Callable() { @Override Object call() { return "f2" } }, ec) Future f3 = Futures.successful("f3", ActorSystem.create("test").dispatcher());
//使用actor的ask方法发送消息是也能创建一个Future
Future f4 = akka.pattern.Patterns.ask(actor, "msg", 1000 * 60)
函数式 Future
Akka 的 Future 有一些与Scala集合所使用的非常相似的 monadic 方法. 这使你可以构造出结果可以传递的‘管道’ 或 ‘数据流’.
map（对未来返回的结果进行处理）
让Future以函数式风格工作的第一个方法是 map. 它需要一个函数来对Future的结果进行处理, 返回一个新的结果。map 方法的返回值是包含新结果的另一个 Future:
static void map() throws Exception { ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future f1 = Futures.successful("fof1o", ec); //map的作用是：对Futrue：f1的返回结果进行处理，返回一个新的结果 Future f2 = f1.map(new Mapper () { public Integer apply(String s) { return s.length(); } }); //这里对未来f1返回的字符串计算其长度 //下面是非阻塞式，异步返回 f2.onComplete(new OnComplete() { @Override public void onComplete(Throwable failure, Integer success) { System.out.println("f2返回结果:" + success + ",failure:" + failure); } }); f2.onSuccess(new OnSuccess () { @Override public void onSuccess(Integer result) { System.out.println("f2返回结果:" + result); } }); f2.onFailure(new OnFailure() { @Override public void onFailure(Throwable failure) { System.out.println("f2返回failure:" + failure); } }); }
flatMap（对多个Future返回的结果进行处理）
static void flatMap() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future f1 = Futures.successful("hello", ec); // Future fr = f1.flatMap(new Mapper >() { public Future apply(final String s) { return Futures.future(new Callable () { public Integer call() { return s.length(); } }, ec); } }); // System.out.println(Await.result(fr, Duration.create(5, "s"))); //阻塞式 } //对两个Future的结果处理 static void flatMap_concat2() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); final Future f1 = Futures.successful("hello", ec); final Future f2 = Futures.successful("world", ec); //如果要对多个Future的结果进行处理，需要用flatMap //本例中对f1和f2返回的结果用空格连接成“hello world” Future fr = f1.flatMap(new Mapper >() { public Future apply(final String s) { return f2.map(new Mapper () { @Override public String apply(String v) { return s + " " + v; } }); } }); System.out.println(Await.result(fr, Duration.create(5, "s"))); //阻塞式 } //对三个Future的结果处理 static void flatMap_concat3() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); final Future f1 = Futures.successful("How", ec); final Future f2 = Futures.successful("are", ec); final Future f3 = Futures.successful("you", ec); //如果要对多个Future的结果进行处理，需要用flatMap //本例中对f1、f2、f3返回的结果用空格连接成“How are you” Future fr = f1.flatMap(new Mapper >() { public Future apply(final String s) { return f2.flatMap(new Mapper >() { @Override public Future apply(final String s2) { return f3.map(new Mapper () { @Override public String apply(String s3) { return s + " " + s2 + " " + s3; } }); } }); } }); /*用java写比较繁琐，用scala的话就简单多了 val future1 = for { a: String <- actor ? "How" // returns How b: String <- actor ? "are" // returns "are" c: String <- actor ? "you" // returns "you" } yield a + " " + b + "" + c*/ System.out.println(Await.result(fr, Duration.create(5, "s"))); //阻塞式 } filter（对Future进行条件筛选）
static void filter() throws Exception { ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future f1 = Futures.successful("fof1o", ec); Future f2 = Futures.successful("fo", ec); //map的作用是：对Futrue：f1的返回结果进行处理，返回一个新的结果 Future fs = f1.filter(Filter.filterOf(new Function () { @Override public Boolean apply(String param) { return param.length() == 5; } })); System.out.println(Await.result(fs, Duration.create(5, "s"))); Future ff = f2.filter(Filter.filterOf(new Function () { @Override public Boolean apply(String param) { return param.length() == 5; } })); //不匹配的话会抛scala.MatchError异常 System.out.println(Await.result(ff, Duration.create(5, "s"))); } 组合Futures
如果Future的数目较多，用flatMap组合的话代码就过于复杂。可以使用sequence和traverse。
sequence（将 T[Future[A]] 转换为 Future[T[A]]）
public static void sequence() throws Exception { //将 T[Future[A]] 转换为 Future[T[A]] //简化了用flatMap来组合 final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); final Future f1 = Futures.successful("How", ec); final Future f2 = Futures.successful("are", ec); final Future f3 = Futures.successful("you", ec); List > futureList = new ArrayList >(); futureList.add(f1); futureList.add(f2); futureList.add(f3); //这里将List > 组合成一个Future：Future > Future > future = Futures.sequence(futureList, ec); Future fr = future.map(new Mapper , String>() { @Override public String apply(Iterable parameter) { String result = ""; for (String s : parameter) { result += s + " "; } return result; } }); System.out.println(Await.result(fr, Duration.create(5, "s"))); } public static void traverse() throws Exception { //将 T[A] 转换为 Future[T[A]] final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Iterable list = Arrays.asList("How", "are", "you"); //这里将List 组合成一个Future：Future > ，对list中的每个元素做加工处理 Future > future = Futures.traverse(list, new Function >() { @Override public Future apply(final String param) { return Futures.future(new Callable () { @Override public String call() throws Exception { return param.toUpperCase(); } }, ec); } }, ec); Future fr = future.map(new Mapper , String>() { @Override public String apply(Iterable parameter) { String result = ""; for (String s : parameter) { result += s + " "; } return result; } }); System.out.println(Await.result(fr, Duration.create(5, "s"))); } public static void fold() throws Exception { //fold从一个初始值开始递归地对Future序列进行处理（它将sequence和map操作合并成一步了） final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); final Future f1 = Futures.successful("How", ec); final Future f2 = Futures.successful("are", ec); final Future f3 = Futures.successful("you", ec); List > futureList = new ArrayList >(); futureList.add(f1); futureList.add(f2); futureList.add(f3); //本例从初始值“Init”开始，递归地对futureList的返回值用"_"连接，返回“Init_How_are_you” Future fr = Futures.fold("Init", futureList, new Function2 () { @Override public String apply(String arg1, String arg2) { System.out.println("arg1----" + arg1); //第一次为Init，第二次为Init_How ，第三次为Init_How_are System.out.println("arg2----" + arg2); //第一次为How ，第二次为are 第三次为you return arg1 + "_" + arg2; } }, ec); //如果futureList为空列表，则返回初始值“Init” System.out.println(Await.result(fr, Duration.create(5, "s"))); //结果为Init_How_are_you } reduce（如果不想从给定的初始值开始递归，而想从future序列的第一个开始，则用reduce（它将sequence和map合并成一步了）） public static void reduce() throws Exception { //如果不想从给定的初始值开始递归，而想从future序列的第一个开始，则用reduce（它将sequence和map合并成一步了） final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); final Future f1 = Futures.successful("How", ec); final Future f2 = Futures.successful("are", ec); final Future f3 = Futures.successful("you", ec); List > futureList = new ArrayList >(); futureList.add(f1); futureList.add(f2); futureList.add(f3); //本例从初始值“How”开始，递归地对futureList的返回值用"_"连接，返回“How_are_you” Future fr = Futures.reduce(futureList, new Function2 () { @Override public String apply(String arg1, String arg2) { System.out.println("arg1----" + arg1); //第一次为How ，第二次为How_are System.out.println("arg2----" + arg2); //第一次为are ，第二次为you return arg1 + "_" + arg2; } }, ec); //如果futureList为空列表，则返回初始值“Init” System.out.println(Await.result(fr, Duration.create(5, "s"))); //结果为Init_How_are_you } andThen（由于回调的执行是无序的，而且可能是并发执行的, 当你需要一组有序操作的时候需要一些技巧。）
public static void andThen() throws Exception { //如果要对Future的结果分多次依次处理，需要使用andThen final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future future = Futures.successful("hello", ec).andThen(new OnComplete () { @Override public void onComplete(Throwable failure, String success) { System.out.println("先收到：" + success); } }).andThen(new OnComplete () { @Override public void onComplete(Throwable failure, String success) { System.out.println("又收到：" + success); } }).andThen(new OnSuccess >() { @Override public void onSuccess(Either result) { System.out.println("收到onSuccess：" + result); } }); } public static void fallbackTo() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future f1 = Futures.failed(new RuntimeException("ex1"), ec); Future f2 = Futures.failed(new RuntimeException("ex2"), ec); Future f3 = Futures.successful("ok", ec); //fallbackTo 将两个 Futures 合并成一个新的 Future, 如果第一个Future失败了，它将持有第二个 Future 的成功值 Future fr = f1.fallbackTo(f2).fallbackTo(f3); System.out.println(Await.result(fr, Duration.create(5, "s"))); } zip（操作将两个 Futures 组合压缩成一个新的Future，返回的新的Future持hold一个tuple实例，它包含二者成功的结果）
public static void zip() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future f1 = Futures.future(new Callable () { @Override public String call() throws Exception { System.out.println("f1---" + Thread.currentThread().getName()); Thread.sleep(1000 * 10); return "hello"; } }, ec); Future f2 = Futures.future(new Callable () { @Override public String call() throws Exception { System.out.println("f2---" + Thread.currentThread().getName()); Thread.sleep(1000 * 5); return "world"; } }, ec); //zip操作将两个 Futures 组合压缩成一个新的Future，返回的新的Future持hold一个tuple实例，它包含二者成功的结果 Future fr = f1.zip(f2).map(new Mapper , String>() { @Override public String apply(Tuple2 ziped) { System.out.println("zip---" + Thread.currentThread().getName()); return ziped._1() + " " + ziped._2(); //f1和f2的返回结果包含在zipped对象中 } }); System.out.println("主线程----" + Thread.currentThread().getName()); System.out.println(Await.result(fr, Duration.create(15, "s"))); } public static void zip2() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); Future f1 = Futures.successful("hello", ec); Future f2 = Futures.future(new Callable () { @Override public String call() throws Exception { System.out.println("f2---" + Thread.currentThread().getName()); Thread.sleep(1000 * 10); return (1 / 0) + ""; } }, ec); //zip操作将两个 Futures 组合压缩成一个新的Future，返回的新的Future持hold一个tuple实例，它包含二者成功的结果 Future fr = f1.zip(f2).map(new Mapper , String>() { @Override public String apply(Tuple2 ziped) { System.out.println("zip----" + Thread.currentThread().getName()); return ziped._1() + " " + ziped._2(); //f1和f2的返回结果包含在zipped对象中 } }); System.out.println("主线程----" + Thread.currentThread().getName()); System.out.println(Await.result(fr, Duration.create(15, "s"))); } recover（对Future的异常进行处理，相当于try..catch中对捕获异常后的处理）
public static void recover() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); //recover对Future的异常进行处理，相当于try..catch中对捕获异常后的处理 Future future = Futures.future(new Callable () { public Integer call() { return 1 / 0; } }, ec).recover(new Recover () { public Integer recover(Throwable problem) throws Throwable { System.out.println("捕获到异常：" + problem);// if (problem instanceof RuntimeException) { // return 0;// } else { // throw problem;// } return -2; //这里捕获到异常后直接返回新值了，并没有再抛出异常，所以后面的recover不会再收到异常 } }).recover(new Recover () { public Integer recover(Throwable problem) throws Throwable { System.out.println("捕获到异常：" + problem); if (problem instanceof ArithmeticException) { //捕获异常并处理，捕获到后，后面得到的result将会是-1 return -1; } else { throw problem; } } }); int result = Await.result(future, Duration.create(1, TimeUnit.SECONDS)); System.out.println("result----" + result); } recoverWith（和recover很类似，只是捕获到异常后返回Future，使其能够异步并发处理）
public static void recoverWith() throws Exception { final ExecutionContextExecutorService ec = ExecutionContexts.fromExecutorService(Executors.newCachedThreadPool()); //recoverWith和recover很类似，只是捕获到异常后返回Future，使其能够异步并发处理 Future future = Futures.future(new Callable () { public Integer call() { return 1 / 0; } }, ec).recoverWith(new Recover >() { @Override public Future recover(Throwable failure) throws Throwable { if (failure instanceof ArithmeticException) { return Futures.future(new Callable () { @Override public Integer call() throws Exception { return 0; } }, ec); } else throw failure; } }); int result = Await.result(future, Duration.create(1, TimeUnit.SECONDS)); System.out.println("result----" + result); }