序
本文主要研究一下reactive streams的processors
processors分类
processors既是Publisher也是Subscriber。在project reactor中processor有诸多实现,他们的分类大致如下:
- direct(
DirectProcessor以及UnicastProcessor
) - synchronous(
EmitterProcessor及ReplayProcessor
) - asynchronous(
TopicProcessor及WorkQueueProcessor
)
direct
DirectProcessor
它不支持backpressure特性,如果publisher发布了N个数据,如果其中一个subscriber请求数<N,则抛出IllegalStateException.
@Test
public void testDirectProcessor(){
DirectProcessor<Integer> directProcessor = DirectProcessor.create();
Flux<Integer> flux = directProcessor
.filter(e -> e % 2 == 0)
.map(e -> e +1);
flux.subscribe(new Subscriber<Integer>() {
private Subscription s;
@Override
public void onSubscribe(Subscription s) {
this.s = s;
// s.request(2);
}
@Override
public void onNext(Integer integer) {
LOGGER.info("subscribe:{}",integer);
}
@Override
public void onError(Throwable t) {
LOGGER.error(t.getMessage(),t);
}
@Override
public void onComplete() {
}
});
IntStream.range(1,20)
.forEach(e -> {
directProcessor.onNext(e);
});
directProcessor.onComplete();
directProcessor.blockLast();
}
输出如下
16:00:11.201 [main] DEBUG reactor.util.Loggers$LoggerFactory - Using Slf4j logging framework
16:00:11.216 [main] ERROR com.example.demo.ProcessorTest - Can't deliver value due to lack of requests
reactor.core.Exceptions$OverflowException: Can't deliver value due to lack of requests
at reactor.core.Exceptions.failWithOverflow(Exceptions.java:215)
at reactor.core.publisher.DirectProcessor$DirectInner.onNext(DirectProcessor.java:304)
at reactor.core.publisher.DirectProcessor.onNext(DirectProcessor.java:106)
at com.example.demo.ProcessorTest.lambda$testDirectProcessor$5(ProcessorTest.java:82)
at java.util.stream.Streams$RangeIntSpliterator.forEachRemaining(Streams.java:110)
at java.util.stream.IntPipeline$Head.forEach(IntPipeline.java:557)
at com.example.demo.ProcessorTest.testDirectProcessor(ProcessorTest.java:81)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
at org.junit.runner.JUnitCore.run(JUnitCore.java:137)
at com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:69)
at com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:234)
at com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:74)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
UnicastProcessor
- 支持backpressure特性,但是代价是至多只能有一个subscriber。默认是无界的,如果发布数据之后,subscriber还没来得及request,则它会把数据缓存下来。
- 如果设置了一个有界的queue,当buffer满而且subscriber没有发送足够多的request的时候,processor会拒绝推送数据。在这种场景下,processor内置了一个callback,每当一个element被rejected的时候会触发.
@Test
public void testUnicastProcessor() throws InterruptedException {
UnicastProcessor<Integer> unicastProcessor = UnicastProcessor.create(Queues.<Integer>get(8).get());
Flux<Integer> flux = unicastProcessor
.map(e -> e)
.doOnError(e -> {
LOGGER.error(e.getMessage(),e);
});
IntStream.rangeClosed(1,12)
.forEach(e -> {
LOGGER.info("emit:{}",e);
unicastProcessor.onNext(e);
try {
TimeUnit.SECONDS.sleep(1);
} catch (InterruptedException e1) {
e1.printStackTrace();
}
});
LOGGER.info("begin to sleep 7 seconds");
TimeUnit.SECONDS.sleep(7);
//UnicastProcessor allows only a single Subscriber
flux.subscribe(e -> {
LOGGER.info("flux subscriber:{}",e);
});
unicastProcessor.onComplete();
TimeUnit.SECONDS.sleep(10);
// unicastProcessor.blockLast(); //blockLast也是一个subscriber
}
输出实例
16:31:04.970 [main] DEBUG reactor.util.Loggers$LoggerFactory - Using Slf4j logging framework
16:31:04.977 [main] INFO com.example.demo.ProcessorTest - emit:1
16:31:05.990 [main] INFO com.example.demo.ProcessorTest - emit:2
16:31:06.991 [main] INFO com.example.demo.ProcessorTest - emit:3
16:31:07.994 [main] INFO com.example.demo.ProcessorTest - emit:4
16:31:08.998 [main] INFO com.example.demo.ProcessorTest - emit:5
16:31:10.002 [main] INFO com.example.demo.ProcessorTest - emit:6
16:31:11.007 [main] INFO com.example.demo.ProcessorTest - emit:7
16:31:12.010 [main] INFO com.example.demo.ProcessorTest - emit:8
16:31:13.014 [main] INFO com.example.demo.ProcessorTest - emit:9
16:31:14.029 [main] INFO com.example.demo.ProcessorTest - emit:10
16:31:14.030 [main] DEBUG reactor.core.publisher.Operators - onNextDropped: 10
16:31:15.034 [main] INFO com.example.demo.ProcessorTest - emit:11
16:31:15.034 [main] DEBUG reactor.core.publisher.Operators - onNextDropped: 11
16:31:16.038 [main] INFO com.example.demo.ProcessorTest - emit:12
16:31:16.038 [main] DEBUG reactor.core.publisher.Operators - onNextDropped: 12
16:31:17.043 [main] INFO com.example.demo.ProcessorTest - begin to sleep 7 seconds
16:31:24.053 [main] INFO com.example.demo.ProcessorTest - flux subscriber:1
16:31:24.053 [main] INFO com.example.demo.ProcessorTest - flux subscriber:2
16:31:24.053 [main] INFO com.example.demo.ProcessorTest - flux subscriber:3
16:31:24.053 [main] INFO com.example.demo.ProcessorTest - flux subscriber:4
16:31:24.053 [main] INFO com.example.demo.ProcessorTest - flux subscriber:5
16:31:24.054 [main] INFO com.example.demo.ProcessorTest - flux subscriber:6
16:31:24.054 [main] INFO com.example.demo.ProcessorTest - flux subscriber:7
16:31:24.054 [main] INFO com.example.demo.ProcessorTest - flux subscriber:8
16:31:24.058 [main] ERROR com.example.demo.ProcessorTest - The receiver is overrun by more signals than expected (bounded queue...)
reactor.core.Exceptions$OverflowException: The receiver is overrun by more signals than expected (bounded queue...)
at reactor.core.Exceptions.failWithOverflow(Exceptions.java:202)
at reactor.core.publisher.UnicastProcessor.onNext(UnicastProcessor.java:330)
at com.example.demo.ProcessorTest.lambda$testUnicastProcessor$8(ProcessorTest.java:108)
at java.util.stream.Streams$RangeIntSpliterator.forEachRemaining(Streams.java:110)
at java.util.stream.IntPipeline$Head.forEach(IntPipeline.java:557)
synchronous
EmitterProcessor
- 能够支持多个subscriber,同时还对每个subscriber支持backpressure。它也可以订阅publisher,然后把数据同步重放。
- 它有一个bufferSize参数,用来在发布数据之后还没有订阅者期间的数据,onNext会一直阻塞直到数据被消费;当第一个订阅者订阅之后,它会接收到buffer里头的数据,而后续的订阅者就只能消费到自他们订阅那个时候起发布的数据。
- 当所有的subscriber都取消订阅之后,该processor会清空buffer,并停止接收新的订阅。
@Test
public void testEmitterProcessor() throws InterruptedException {
int bufferSize = 3; //小于8的会被重置为8
FluxProcessor<Integer, Integer> processor = EmitterProcessor.create(bufferSize);
Flux<Integer> flux1 = processor.map(e -> e);
Flux<Integer> flux2 = processor.map(e -> e*10);
IntStream.rangeClosed(1,8).forEach(e -> {
LOGGER.info("emit:{}",e);
processor.onNext(e); //如果发布的未消费数据超过bufferSize,则会阻塞在这里
});
flux1.subscribe(e -> {
LOGGER.info("flux1 subscriber:{}",e);
});
IntStream.rangeClosed(9,10).forEach(e -> {
LOGGER.info("emit:{}",e);
processor.onNext(e);
try {
TimeUnit.SECONDS.sleep(1);
} catch (InterruptedException e1) {
e1.printStackTrace();
}
});
//这个是后面添加的订阅,只能消费之后发布的数据
flux2.subscribe(e -> {
LOGGER.info("flux2 subscriber:{}",e);
});
processor.onNext(11);
processor.onNext(12);
processor.onComplete();
processor.blockLast();
}
输出实例
17:27:01.008 [main] DEBUG reactor.util.Loggers$LoggerFactory - Using Slf4j logging framework
17:27:01.044 [main] INFO com.example.demo.ProcessorTest - emit:1
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:2
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:3
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:4
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:5
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:6
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:7
17:27:01.084 [main] INFO com.example.demo.ProcessorTest - emit:8
17:27:01.086 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:1
17:27:01.086 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:2
17:27:01.087 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:3
17:27:01.087 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:4
17:27:01.087 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:5
17:27:01.087 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:6
17:27:01.087 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:7
17:27:01.087 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:8
17:27:01.088 [main] INFO com.example.demo.ProcessorTest - emit:9
17:27:01.088 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:9
17:27:02.091 [main] INFO com.example.demo.ProcessorTest - emit:10
17:27:02.092 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:10
17:27:03.096 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:11
17:27:03.096 [main] INFO com.example.demo.ProcessorTest - flux2 subscriber:110
17:27:03.096 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:12
17:27:03.096 [main] INFO com.example.demo.ProcessorTest - flux2 subscriber:120
ReplayProcessor
可以缓存通过sink产生的数据或者订阅publisher的数据,然后重放给后来的订阅者。有如下四种配置
- cacheLast
只缓存最后一个数据
- create(int)
缓存最后N个数据
- createTimeout(Duration)
对每个数据打上时间戳标签,只缓存age在指定ttl内的数据
- createSizeOrTimeout(int,Duration)
对每个数据打上时间戳标签,只缓存age在指定ttl内的N个数据
实例
@Test
public void testReplayProcessor() throws InterruptedException {
ReplayProcessor<Integer> replayProcessor = ReplayProcessor.create(3);
Flux<Integer> flux1 = replayProcessor
.map(e -> e);
Flux<Integer> flux2 = replayProcessor
.map(e -> e);
flux1.subscribe(e -> {
LOGGER.info("flux1 subscriber:{}",e);
});
IntStream.rangeClosed(1,5)
.forEach(e -> {
replayProcessor.onNext(e);
try {
TimeUnit.SECONDS.sleep(1);
} catch (InterruptedException e1) {
e1.printStackTrace();
}
});
LOGGER.info("finish publish data");
TimeUnit.SECONDS.sleep(3);
LOGGER.info("begin to subscribe flux2");
flux2.subscribe(e -> {
LOGGER.info("flux2 subscriber:{}",e);
});
replayProcessor.onComplete();
replayProcessor.blockLast();
}
输出如下
15:13:39.415 [main] DEBUG reactor.util.Loggers$LoggerFactory - Using Slf4j logging framework
15:13:39.438 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:1
15:13:40.445 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:2
15:13:41.449 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:3
15:13:42.454 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:4
15:13:43.459 [main] INFO com.example.demo.ProcessorTest - flux1 subscriber:5
15:13:44.463 [main] INFO com.example.demo.ProcessorTest - finish publish data
15:13:47.466 [main] INFO com.example.demo.ProcessorTest - begin to subscribe flux2
15:13:47.467 [main] INFO com.example.demo.ProcessorTest - flux2 subscriber:3
15:13:47.467 [main] INFO com.example.demo.ProcessorTest - flux2 subscriber:4
15:13:47.468 [main] INFO com.example.demo.ProcessorTest - flux2 subscriber:5
asynchronous
TopicProcessor
- TopicProcessor是一个异步的processor,当shared设置为true的时候,支持对多个publisher的并发重放。如果订阅的publisher是一个并发的stream或者是需要并发调用Topicrocessor的onNext,onCompleete,onError方法,则必须强制开启share。关闭share则是遵循reactive streams规范的processor,不允许并发调用。
- TopicProcessor也支持把消息广播(fan-out)到多个subscriber,它给每个subscriber绑定一个线程。能够支持的subscriber的最大个数由线程池executor限制。
- TopicProcessor使用了RingBuffer数据结构来推送数据,每个subscriber线程都在RingBuffer记录其消费的位置
- TopicProcessor也支持autoCancel选项,默认为true,也就是当所有subscriber都取消订阅的时候,publisher也会被自动cannel
@Test
public void testTopicProcessor() throws InterruptedException {
TopicProcessor<Integer> topicProcessor = TopicProcessor.<Integer>builder()
.share(true)
// .executor(Executors.newSingleThreadExecutor())
.build();
Flux<Integer> flux1 = topicProcessor
.map(e -> e);
Flux<Integer> flux2 = topicProcessor
.map(e -> e);
Flux<Integer> flux3 = topicProcessor
.map(e -> e);
AtomicInteger count = new AtomicInteger(0);
flux1.subscribe(e -> {
LOGGER.info("flux1 subscriber:{}",e);
count.incrementAndGet();
});
flux2.subscribe(e -> {
LOGGER.info("flux2 subscriber:{}",e);
});
flux3.subscribe(e -> {
LOGGER.info("flux3 subscriber:{}",e);
});
IntStream.rangeClosed(1,100)
.parallel()
.forEach(e -> {
// LOGGER.info("emit:{}",e);
topicProcessor.onNext(e);
});
topicProcessor.onComplete();
topicProcessor.blockLast();
TimeUnit.SECONDS.sleep(10);
System.out.println(count.get());
}
注意两个地方:
- share
share背后设置的是EventLoopProcessor的multiproducers属性
reactor-core-3.1.2.RELEASE-sources.jar!/reactor/core/publisher/EventLoopProcessor.java
EventLoopProcessor(
int bufferSize,
@Nullable ThreadFactory threadFactory,
@Nullable ExecutorService executor,
ExecutorService requestExecutor,
boolean autoCancel,
boolean multiproducers,
Supplier<Slot<IN>> factory,
WaitStrategy strategy) {
if (!Queues.isPowerOfTwo(bufferSize)) {
throw new IllegalArgumentException("bufferSize must be a power of 2 : " + bufferSize);
}
if (bufferSize < 1){
throw new IllegalArgumentException("bufferSize must be strictly positive, " +
"was: "+bufferSize);
}
this.autoCancel = autoCancel;
contextClassLoader = new EventLoopContext(multiproducers);
this.name = defaultName(threadFactory, getClass());
this.requestTaskExecutor = Objects.requireNonNull(requestExecutor, "requestTaskExecutor");
if (executor == null) {
this.executor = Executors.newCachedThreadPool(threadFactory);
}
else {
this.executor = executor;
}
if (multiproducers) {
this.ringBuffer = RingBuffer.createMultiProducer(factory,
bufferSize,
strategy,
this);
}
else {
this.ringBuffer = RingBuffer.createSingleProducer(factory,
bufferSize,
strategy,
this);
}
}
如果share为true,则创建的是createMultiProducer.
具体的表象就是如果有多线程调用processor的onNext方法,而没有开启share的话,会有并发问题,即数据会丢失.比如上面的代码,如果注释掉share(true),则最后count的大小就不一定是100,而开启share为true就能保证最后count的大小是100如果设置executor(Executors.newSingleThreadExecutor()),则flux1,flux2,flux3的订阅者则是顺序执行,而不是并发的.
WorkQueueProcessor
- WorkQueueProcessor也是一个异步的processor,当shared设置为true的时候,支持对多个publisher的并发重放。
- WorkQueueProcessor使用了RingBuffer数据结构来推送数据。
- WorkQueueProcessor不是每来一个subscriber就给其创建一个线程,因此比TopicProcessor的伸缩性更好一点。能够支持的subscriber的最大个数由线程池executor限制。但是值得注意的是最好不要给WorkQueueProcessor添加过多的subscriber,这样会增加processor的锁竞争。最好使用ThreadPoolExecutor或者ForkJoinPool,processor可以检测他们的容量然后再订阅者过多的时候抛出异常。
- WorkQueueProcessor不遵循reactive streams的规范,因此比TopicProcessor所消耗的资源更少。作为trade-off,所有subscriber的request会累加在一起,然后WorkQueueProcessor每次只给一个subscriber重放数据,相比于TopicProcessorde fan-out广播模式,它类似于round-robin模式,但是公平的round-robin模式是不被保证的。
@Test
public void testWorkQueueProcessor(){
WorkQueueProcessor<Integer> workQueueProcessor = WorkQueueProcessor.create();
Flux<Integer> flux1 = workQueueProcessor
.map(e -> e);
Flux<Integer> flux2 = workQueueProcessor
.map(e -> e);
Flux<Integer> flux3 = workQueueProcessor
.map(e -> e);
flux1.subscribe(e -> {
LOGGER.info("flux1 subscriber:{}",e);
});
flux2.subscribe(e -> {
LOGGER.info("flux2 subscriber:{}",e);
});
flux3.subscribe(e -> {
LOGGER.info("flux3 subscriber:{}",e);
});
IntStream.range(1,20)
.forEach(e -> {
workQueueProcessor.onNext(e);
});
workQueueProcessor.onComplete();
workQueueProcessor.blockLast();
}
输出实例
21:56:58.203 [main] DEBUG reactor.util.Loggers$LoggerFactory - Using Slf4j logging framework
21:56:58.214 [main] DEBUG reactor.core.publisher.UnsafeSupport - Starting UnsafeSupport init in Java 1.8
21:56:58.215 [main] DEBUG reactor.core.publisher.UnsafeSupport - Unsafe is available
21:56:58.228 [WorkQueueProcessor-1] INFO com.example.demo.ProcessorTest - flux1 subscriber:1
21:56:58.228 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:3
21:56:58.228 [WorkQueueProcessor-2] INFO com.example.demo.ProcessorTest - flux2 subscriber:2
21:56:58.229 [WorkQueueProcessor-1] INFO com.example.demo.ProcessorTest - flux1 subscriber:4
21:56:58.229 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:5
21:56:58.229 [WorkQueueProcessor-2] INFO com.example.demo.ProcessorTest - flux2 subscriber:6
21:56:58.230 [WorkQueueProcessor-1] INFO com.example.demo.ProcessorTest - flux1 subscriber:7
21:56:58.230 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:8
21:56:58.230 [WorkQueueProcessor-2] INFO com.example.demo.ProcessorTest - flux2 subscriber:9
21:56:58.230 [WorkQueueProcessor-1] INFO com.example.demo.ProcessorTest - flux1 subscriber:10
21:56:58.230 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:11
21:56:58.230 [WorkQueueProcessor-2] INFO com.example.demo.ProcessorTest - flux2 subscriber:12
21:56:58.230 [WorkQueueProcessor-1] INFO com.example.demo.ProcessorTest - flux1 subscriber:13
21:56:58.230 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:14
21:56:58.230 [WorkQueueProcessor-2] INFO com.example.demo.ProcessorTest - flux2 subscriber:15
21:56:58.230 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:17
21:56:58.230 [WorkQueueProcessor-1] INFO com.example.demo.ProcessorTest - flux1 subscriber:16
21:56:58.230 [WorkQueueProcessor-3] INFO com.example.demo.ProcessorTest - flux3 subscriber:19
21:56:58.230 [WorkQueueProcessor-2] INFO com.example.demo.ProcessorTest - flux2 subscriber:18
可以看到WorkQueueProcessor的subscriber就类似kafka的同属于一个group的consumer,各自消费的消息总和就是publisher发布的总消息,不像TopicProcessor那种广播式的消息传递.
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