disruptor3.x 简单例子

这个是最新的 disruptor3的例子....来自官方代码稍微简化后的

 

 

package io.grass.core.collect;

import static com.lmax.disruptor.RingBuffer.createSingleProducer;

import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import com.lmax.disruptor.BatchEventProcessor;
import com.lmax.disruptor.EventFactory;
import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.SequenceBarrier;
import com.lmax.disruptor.YieldingWaitStrategy;
import com.lmax.disruptor.util.PaddedLong;

/**
 * 简单测试
 * 
 * @author zuoge85
 * 
 */
public class DisruptorBaseTest {
	protected static final Logger log = LoggerFactory.getLogger(DisruptorBaseTest.class);
	
	private static final int THREAD_NUMS = 1;
	private static final int BUFFER_SIZE = 1024 * 8;
	private static final long NUMS = 1000_000_00L;

	public static void main(String[] args) throws InterruptedException {
		RingBuffer<MessageEvent> ringBuffer = createSingleProducer(
				MessageEvent.EVENT_FACTORY, BUFFER_SIZE,
				new YieldingWaitStrategy());
		ExecutorService executors = Executors.newFixedThreadPool(THREAD_NUMS);
		SequenceBarrier sequenceBarrier = ringBuffer.newBarrier();

		MessageMutationEventHandler[] handlers = new MessageMutationEventHandler[THREAD_NUMS];
		BatchEventProcessor<?>[] batchEventProcessors = new BatchEventProcessor[THREAD_NUMS];

		for (int i = 0; i < THREAD_NUMS; i++) {
			handlers[i] = new MessageMutationEventHandler();
			batchEventProcessors[i] = new BatchEventProcessor<MessageEvent>(
					ringBuffer, sequenceBarrier, handlers[i]);
			ringBuffer
					.addGatingSequences(batchEventProcessors[i].getSequence());
		}

		CountDownLatch latch = new CountDownLatch(THREAD_NUMS);
		for (int i = 0; i < THREAD_NUMS; i++) {
			long n =  batchEventProcessors[i].getSequence().get() + NUMS;
			System.out.println(n +"    "  +NUMS+"  "+batchEventProcessors[i].getSequence().get() );
			handlers[i].reset(latch, n);
			executors.submit(batchEventProcessors[i]);
		}
		long start = System.currentTimeMillis();

		for (long i = 0; i < NUMS; i++) {
			long sequence = ringBuffer.next();
			ringBuffer.get(sequence).setValue(i);
			ringBuffer.publish(sequence);
		}

		latch.await();
		long opsPerSecond = (NUMS * 1000L)
				/ (System.currentTimeMillis() - start);

		for (int i = 0; i < THREAD_NUMS; i++) {
			batchEventProcessors[i].halt();
			if ((NUMS - 1) == handlers[i].getValue()) {

			} else {
				log.error("error");
			}
		}
		executors.shutdown();
		log.info(String.format("Run %d, Disruptor=%,d ops/sec%n", 1, opsPerSecond));
	}

	public static final class MessageMutationEventHandler implements
			EventHandler<MessageEvent> {
		private final PaddedLong value = new PaddedLong();
		private long count;
		private CountDownLatch latch;

		public MessageMutationEventHandler() {
			
		}

		public long getValue() {
			return value.get();
		}

		public void reset(final CountDownLatch latch, final long expectedCount) {
			value.set(0L);
			this.latch = latch;
			count = expectedCount;
		}

		@Override
		public void onEvent(final MessageEvent event, final long sequence,
				final boolean endOfBatch) throws Exception {
			//log.info("onEvent:{}",event.getValue());
			value.set(event.getValue());
			if (count == sequence) {
				latch.countDown();
			}
		}
	}

	public static final class MessageEvent {
		private long value;

		public long getValue() {
			return value;
		}

		public void setValue(final long value) {
			this.value = value;
		}

		public final static EventFactory<MessageEvent> EVENT_FACTORY = new EventFactory<MessageEvent>() {
			public MessageEvent newInstance() {
				return new MessageEvent();
			}
		};
	}
}

 

 

关于Log4j是否支持异步写入的问题,这与提供的有关SQL查询中`COUNT()`函数处理空值以及NULL概念的引用内容关联不大。不过,针对所询问的主题: Log4j确实支持异步写入功能。通过配置异步记录器或异步追加器(appender),应用程序可以在不影响主线程性能的情况下执行日志记录操作。这种方式能够显著减少由于同步I/O操作带来的延迟。 为了实现这一点,在Log4j 2.x版本里引入了LMAX Disruptor库来提供高效的事件处理机制。这意味着开发者可以通过简单的配置更改使自己的应用受益于高性能的日志记录能力[^3]。 下面是一段展示如何设置异步记录器的例子: ```xml <Configuration status="WARN"> <Appenders> <!-- 定义一个常规RollingFile appender --> <RollingFile name="RollingFile" fileName="logs/app.log" filePattern="logs/$${date:yyyy-MM}/app-%d{MM-dd-yyyy}-%i.log.gz"> <PatternLayout> <pattern>%d %p %c{1.} [%t] %m%n</pattern> </PatternLayout> <Policies> <TimeBasedTriggeringPolicy /> </Policies> </RollingFile> <!-- 将上述定义封装成异步形式 --> <Async name="Async"> <AppenderRef ref="RollingFile"/> </Async> </Appenders> <Loggers> <Root level="error"> <AppenderRef ref="Async"/> </Root> </Loggers> </Configuration> ``` 这段XML片段展示了怎样创建一个名为`RollingFile`的标准文件滚动追加器,并将其包裹在一个叫做`Async`的异步组件内。这样做的好处是可以让所有的日志消息先存放在内存缓冲区中,由专门的工作线程负责实际磁盘写入工作,从而提高整体效率并降低对业务逻辑的影响[^3]。
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