如何组合 Observables 以避免给定的嵌套和依赖回调?
How to compose Observables to avoid the given nested and dependent callbacks?
在this blog, he gives this(copy/pasted下面的代码)例子中为回调地狱。但是,没有提到如何使用 Reactive Extensions 来消除这个问题。
所以这里的F3依赖于F1的完成,F4和F5依赖于F2的完成。
- 想知道 Rx 中的功能等价物是什么。
- 如何在Rx中表示F1,F2,F3,F4,F5都应该异步拉取?
注意:我目前正在尝试围绕 Rx 思考,所以在问这个问题之前我没有尝试解决这个例子。
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicReference;
public class CallbackB {
/**
* Demonstration of nested callbacks which then need to composes their responses together.
* <p>
* Various different approaches for composition can be done but eventually they end up relying upon
* synchronization techniques such as the CountDownLatch used here or converge on callback design
* changes similar to <a href="https://github.com/Netflix/RxJava">Rx</a>.
*/
public static void run() throws Exception {
final ExecutorService executor = new ThreadPoolExecutor(4, 4, 1, TimeUnit.MINUTES, new LinkedBlockingQueue<Runnable>());
/* the following are used to synchronize and compose the asynchronous callbacks */
final CountDownLatch latch = new CountDownLatch(3);
final AtomicReference<String> f3Value = new AtomicReference<String>();
final AtomicReference<Integer> f4Value = new AtomicReference<Integer>();
final AtomicReference<Integer> f5Value = new AtomicReference<Integer>();
try {
// get f3 with dependent result from f1
executor.execute(new CallToRemoteServiceA(new Callback<String>() {
@Override
public void call(String f1) {
executor.execute(new CallToRemoteServiceC(new Callback<String>() {
@Override
public void call(String f3) {
// we have f1 and f3 now need to compose with others
System.out.println("intermediate callback: " + f3 + " => " + ("f4 * f5"));
// set to thread-safe variable accessible by external scope
f3Value.set(f3);
latch.countDown();
}
}, f1));
}
}));
// get f4/f5 after dependency f2 completes
executor.execute(new CallToRemoteServiceB(new Callback<Integer>() {
@Override
public void call(Integer f2) {
executor.execute(new CallToRemoteServiceD(new Callback<Integer>() {
@Override
public void call(Integer f4) {
// we have f2 and f4 now need to compose with others
System.out.println("intermediate callback: f3" + " => " + (f4 + " * f5"));
// set to thread-safe variable accessible by external scope
f4Value.set(f4);
latch.countDown();
}
}, f2));
executor.execute(new CallToRemoteServiceE(new Callback<Integer>() {
@Override
public void call(Integer f5) {
// we have f2 and f5 now need to compose with others
System.out.println("intermediate callback: f3" + " => " + ("f4 * " + f5));
// set to thread-safe variable accessible by external scope
f5Value.set(f5);
latch.countDown();
}
}, f2));
}
}));
/* we must wait for all callbacks to complete */
latch.await();
System.out.println(f3Value.get() + " => " + (f4Value.get() * f5Value.get()));
} finally {
executor.shutdownNow();
}
}
public static void main(String[] args) {
try {
run();
} catch (Exception e) {
e.printStackTrace();
}
}
private static final class CallToRemoteServiceA implements Runnable {
private final Callback<String> callback;
private CallToRemoteServiceA(Callback<String> callback) {
this.callback = callback;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(100);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call("responseA");
}
}
private static final class CallToRemoteServiceB implements Runnable {
private final Callback<Integer> callback;
private CallToRemoteServiceB(Callback<Integer> callback) {
this.callback = callback;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(40);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call(100);
}
}
private static final class CallToRemoteServiceC implements Runnable {
private final Callback<String> callback;
private final String dependencyFromA;
private CallToRemoteServiceC(Callback<String> callback, String dependencyFromA) {
this.callback = callback;
this.dependencyFromA = dependencyFromA;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(60);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call("responseB_" + dependencyFromA);
}
}
private static final class CallToRemoteServiceD implements Runnable {
private final Callback<Integer> callback;
private final Integer dependencyFromB;
private CallToRemoteServiceD(Callback<Integer> callback, Integer dependencyFromB) {
this.callback = callback;
this.dependencyFromB = dependencyFromB;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(140);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call(40 + dependencyFromB);
}
}
private static final class CallToRemoteServiceE implements Runnable {
private final Callback<Integer> callback;
private final Integer dependencyFromB;
private CallToRemoteServiceE(Callback<Integer> callback, Integer dependencyFromB) {
this.callback = callback;
this.dependencyFromB = dependencyFromB;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(55);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call(5000 + dependencyFromB);
}
}
private static interface Callback<T> {
public void call(T value);
}
}
根据你的代码。假设使用 Observable
.
完成远程调用
Observable<Integer> callRemoveServiceA() { /* async call */ }
/* .... */
Observable<Integer> callRemoveServiceE(Integer f2) { /* async call */ }
你想要什么:
- 调用
serviceA
然后调用 serviceB
得到 serviceA
的结果
- 调用
serviceC
然后调用 serviceD
和 serviceE
得到 serviceC
的结果
- 利用
serviceE
和serviceD
的结果,构建一个新值
- 用
serviceB
的结果显示新值
使用 RxJava,您将使用以下代码实现此目的:
Observable<Integer> f3 = callRemoveServiceA() // call serviceA
// call serviceB with the result of serviceA
.flatMap((f1) -> callRemoveServiceB(f1));
Observable<Integer> f4Andf5 = callRemoveServiceC() // call serviceC
// call serviceD and serviceE then build a new value
.flatMap((f2) -> callRemoveServiceD(f2).zipWith(callRemoveServiceE(f2), (f4, f5) -> f4 * f5));
// compute the string to display from f3, and the f4, f5 pair
f3.zipWith(f4Andf5, (childF3, childF4Andf5) -> childF3 + " => " + childF4Andf5)
// display the value
.subscribe(System.out::println);
这里重要的部分是使用 flapMap
和 zip
(或 zipWith
)
flapMap
会将一个值转换为另一个 Observable
。这里的 Observable
将是您的新异步调用。 ( http://reactivex.io/documentation/operators/flatmap.html )
zip
将从两个不同的 Observable
组成一个新值。因此,您可以使用两个(或更多)Obsevable
( http://reactivex.io/documentation/operators/zip.html ) 的结果构建一个新值
您可以在此处获取有关 flapMap 的更多信息:When do you use map vs flatMap in RxJava?
我是有关回调和 Java 期货的参考博客 post 的原作者。下面是一个使用 flatMap、zip 和 merge 异步进行服务组合的例子。
它获取一个 User 对象,然后同时获取 Social 和 PersonalizedCatalog 数据,然后从 PersonalizedCatalog 中为每个视频同时获取一个 Bookmark、Rating 和 Metadata,将它们压缩在一起,并将所有响应合并到一个渐进式流输出中作为服务器发送的事件。
return getUser(userId).flatMap(user -> {
Observable<Map<String, Object>> catalog = getPersonalizedCatalog(user)
.flatMap(catalogList -> catalogList.videos().<Map<String, Object>> flatMap(
video -> {
Observable<Bookmark> bookmark = getBookmark(video);
Observable<Rating> rating = getRatings(video);
Observable<VideoMetadata> metadata = getVideoMetadata(video);
return Observable.zip(bookmark, rating, metadata, (b, r, m) -> combineVideoData(video, b, r, m));
}));
Observable<Map<String, Object>> social = getSocial(user).map(s -> {
return s.getDataAsMap();
});
return Observable.merge(catalog, social);
}).flatMap(data -> {
String json = SimpleJson.mapToJson(data);
return response.writeStringAndFlush("data: " + json + "\n");
});
上运行的应用程序上下文中查看此示例
由于我不可能在此处提供所有信息,您还可以在 https://speakerdeck.com/benjchristensen/reactive-streams-with-rx-at-javaone-2014?slide=32.
找到演示文稿形式的解释(带有 link 视频)
在this blog, he gives this(copy/pasted下面的代码)例子中为回调地狱。但是,没有提到如何使用 Reactive Extensions 来消除这个问题。
所以这里的F3依赖于F1的完成,F4和F5依赖于F2的完成。
- 想知道 Rx 中的功能等价物是什么。
- 如何在Rx中表示F1,F2,F3,F4,F5都应该异步拉取?
注意:我目前正在尝试围绕 Rx 思考,所以在问这个问题之前我没有尝试解决这个例子。
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicReference;
public class CallbackB {
/**
* Demonstration of nested callbacks which then need to composes their responses together.
* <p>
* Various different approaches for composition can be done but eventually they end up relying upon
* synchronization techniques such as the CountDownLatch used here or converge on callback design
* changes similar to <a href="https://github.com/Netflix/RxJava">Rx</a>.
*/
public static void run() throws Exception {
final ExecutorService executor = new ThreadPoolExecutor(4, 4, 1, TimeUnit.MINUTES, new LinkedBlockingQueue<Runnable>());
/* the following are used to synchronize and compose the asynchronous callbacks */
final CountDownLatch latch = new CountDownLatch(3);
final AtomicReference<String> f3Value = new AtomicReference<String>();
final AtomicReference<Integer> f4Value = new AtomicReference<Integer>();
final AtomicReference<Integer> f5Value = new AtomicReference<Integer>();
try {
// get f3 with dependent result from f1
executor.execute(new CallToRemoteServiceA(new Callback<String>() {
@Override
public void call(String f1) {
executor.execute(new CallToRemoteServiceC(new Callback<String>() {
@Override
public void call(String f3) {
// we have f1 and f3 now need to compose with others
System.out.println("intermediate callback: " + f3 + " => " + ("f4 * f5"));
// set to thread-safe variable accessible by external scope
f3Value.set(f3);
latch.countDown();
}
}, f1));
}
}));
// get f4/f5 after dependency f2 completes
executor.execute(new CallToRemoteServiceB(new Callback<Integer>() {
@Override
public void call(Integer f2) {
executor.execute(new CallToRemoteServiceD(new Callback<Integer>() {
@Override
public void call(Integer f4) {
// we have f2 and f4 now need to compose with others
System.out.println("intermediate callback: f3" + " => " + (f4 + " * f5"));
// set to thread-safe variable accessible by external scope
f4Value.set(f4);
latch.countDown();
}
}, f2));
executor.execute(new CallToRemoteServiceE(new Callback<Integer>() {
@Override
public void call(Integer f5) {
// we have f2 and f5 now need to compose with others
System.out.println("intermediate callback: f3" + " => " + ("f4 * " + f5));
// set to thread-safe variable accessible by external scope
f5Value.set(f5);
latch.countDown();
}
}, f2));
}
}));
/* we must wait for all callbacks to complete */
latch.await();
System.out.println(f3Value.get() + " => " + (f4Value.get() * f5Value.get()));
} finally {
executor.shutdownNow();
}
}
public static void main(String[] args) {
try {
run();
} catch (Exception e) {
e.printStackTrace();
}
}
private static final class CallToRemoteServiceA implements Runnable {
private final Callback<String> callback;
private CallToRemoteServiceA(Callback<String> callback) {
this.callback = callback;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(100);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call("responseA");
}
}
private static final class CallToRemoteServiceB implements Runnable {
private final Callback<Integer> callback;
private CallToRemoteServiceB(Callback<Integer> callback) {
this.callback = callback;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(40);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call(100);
}
}
private static final class CallToRemoteServiceC implements Runnable {
private final Callback<String> callback;
private final String dependencyFromA;
private CallToRemoteServiceC(Callback<String> callback, String dependencyFromA) {
this.callback = callback;
this.dependencyFromA = dependencyFromA;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(60);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call("responseB_" + dependencyFromA);
}
}
private static final class CallToRemoteServiceD implements Runnable {
private final Callback<Integer> callback;
private final Integer dependencyFromB;
private CallToRemoteServiceD(Callback<Integer> callback, Integer dependencyFromB) {
this.callback = callback;
this.dependencyFromB = dependencyFromB;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(140);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call(40 + dependencyFromB);
}
}
private static final class CallToRemoteServiceE implements Runnable {
private final Callback<Integer> callback;
private final Integer dependencyFromB;
private CallToRemoteServiceE(Callback<Integer> callback, Integer dependencyFromB) {
this.callback = callback;
this.dependencyFromB = dependencyFromB;
}
@Override
public void run() {
// simulate fetching data from remote service
try {
Thread.sleep(55);
} catch (InterruptedException e) {
e.printStackTrace();
}
callback.call(5000 + dependencyFromB);
}
}
private static interface Callback<T> {
public void call(T value);
}
}
根据你的代码。假设使用 Observable
.
Observable<Integer> callRemoveServiceA() { /* async call */ }
/* .... */
Observable<Integer> callRemoveServiceE(Integer f2) { /* async call */ }
你想要什么:
- 调用
serviceA
然后调用serviceB
得到serviceA
的结果
- 调用
serviceC
然后调用serviceD
和serviceE
得到serviceC
的结果
- 利用
serviceE
和serviceD
的结果,构建一个新值 - 用
serviceB
的结果显示新值
使用 RxJava,您将使用以下代码实现此目的:
Observable<Integer> f3 = callRemoveServiceA() // call serviceA
// call serviceB with the result of serviceA
.flatMap((f1) -> callRemoveServiceB(f1));
Observable<Integer> f4Andf5 = callRemoveServiceC() // call serviceC
// call serviceD and serviceE then build a new value
.flatMap((f2) -> callRemoveServiceD(f2).zipWith(callRemoveServiceE(f2), (f4, f5) -> f4 * f5));
// compute the string to display from f3, and the f4, f5 pair
f3.zipWith(f4Andf5, (childF3, childF4Andf5) -> childF3 + " => " + childF4Andf5)
// display the value
.subscribe(System.out::println);
这里重要的部分是使用 flapMap
和 zip
(或 zipWith
)
flapMap
会将一个值转换为另一个Observable
。这里的Observable
将是您的新异步调用。 ( http://reactivex.io/documentation/operators/flatmap.html )zip
将从两个不同的Observable
组成一个新值。因此,您可以使用两个(或更多)Obsevable
( http://reactivex.io/documentation/operators/zip.html ) 的结果构建一个新值
您可以在此处获取有关 flapMap 的更多信息:When do you use map vs flatMap in RxJava?
我是有关回调和 Java 期货的参考博客 post 的原作者。下面是一个使用 flatMap、zip 和 merge 异步进行服务组合的例子。
它获取一个 User 对象,然后同时获取 Social 和 PersonalizedCatalog 数据,然后从 PersonalizedCatalog 中为每个视频同时获取一个 Bookmark、Rating 和 Metadata,将它们压缩在一起,并将所有响应合并到一个渐进式流输出中作为服务器发送的事件。
return getUser(userId).flatMap(user -> {
Observable<Map<String, Object>> catalog = getPersonalizedCatalog(user)
.flatMap(catalogList -> catalogList.videos().<Map<String, Object>> flatMap(
video -> {
Observable<Bookmark> bookmark = getBookmark(video);
Observable<Rating> rating = getRatings(video);
Observable<VideoMetadata> metadata = getVideoMetadata(video);
return Observable.zip(bookmark, rating, metadata, (b, r, m) -> combineVideoData(video, b, r, m));
}));
Observable<Map<String, Object>> social = getSocial(user).map(s -> {
return s.getDataAsMap();
});
return Observable.merge(catalog, social);
}).flatMap(data -> {
String json = SimpleJson.mapToJson(data);
return response.writeStringAndFlush("data: " + json + "\n");
});
上运行的应用程序上下文中查看此示例
由于我不可能在此处提供所有信息,您还可以在 https://speakerdeck.com/benjchristensen/reactive-streams-with-rx-at-javaone-2014?slide=32.
找到演示文稿形式的解释(带有 link 视频)