前提
最近在生产环境刚好遇到了延时任务的场景，调研了一下目前主流的方案，分析了一下优劣并且敲定了最终的方案。这篇文章记录了调研的过程，以及初步方案的实现。
候选方案对比
下面是想到的几种实现延时任务的方案，总结了一下相应的优势和劣势。
| 方案 | 优势 | 劣势 | 选用场景 |
JDK内置的延迟队列DelayQueue |
实现简单 | 数据内存态，不可靠 | 一致性相对低的场景 |
调度框架和MySQL进行短间隔轮询 |
实现简单，可靠性高 | 存在明显的性能瓶颈 | 数据量较少实时性相对低的场景 |
RabbitMQ的DLX和TTL，一般称为死信队列方案 |
异步交互可以削峰 | 延时的时间长度不可控，如果数据需要持久化则性能会降低 | - |
调度框架和Redis进行短间隔轮询 |
数据持久化，高性能 | 实现难度大 | 常见于支付结果回调方案 |
| 时间轮 | 实时性高 | 实现难度大，内存消耗大 | 实时性高的场景 |
如果应用的数据量不高，实时性要求比较低，选用调度框架和MySQL进行短间隔轮询这个方案是最优的方案。但是笔者遇到的场景数据量相对比较大，实时性并不高，采用扫库的方案一定会对MySQL实例造成比较大的压力。记得很早之前，看过一个PPT叫《盒子科技聚合支付系统演进》，其中里面有一张图片给予笔者一点启发：
里面刚好用到了调度框架和Redis进行短间隔轮询实现延时任务的方案，不过为了分摊应用的压力，图中的方案还做了分片处理。鉴于笔者当前业务紧迫，所以在第一期的方案暂时不考虑分片，只做了一个简化版的实现。
由于PPT中没有任何的代码或者框架贴出，有些需要解决的技术点需要自行思考，下面会重现一次整个方案实现的详细过程。
场景设计
实际的生产场景是笔者负责的某个系统需要对接一个外部的资金方，每一笔资金下单后需要延时30分钟推送对应的附件。这里简化为一个订单信息数据延迟处理的场景，就是每一笔下单记录一条订单消息(暂时叫做OrderMessage)，订单消息需要延迟5到15秒后进行异步处理。
否决的候选方案实现思路
下面介绍一下其它四个不选用的候选方案，结合一些伪代码和流程分析一下实现过程。
JDK内置延迟队列
DelayQueue是一个阻塞队列的实现，它的队列元素必须是Delayed的子类，这里做个简单的例子：
public class DelayQueueMain { private static final Logger LOGGER = LoggerFactory.getLogger(DelayQueueMain.class); public static void main(String[] args) throws Exception { DelayQueue<OrderMessage> queue = new DelayQueue<>(); // 默认延迟5秒 OrderMessage message = new OrderMessage("ORDER_ID_10086"); queue.add(message); // 延迟6秒 message = new OrderMessage("ORDER_ID_10087", 6); queue.add(message); // 延迟10秒 message = new OrderMessage("ORDER_ID_10088", 10); queue.add(message); ExecutorService executorService = Executors.newSingleThreadExecutor(r -> { Thread thread = new Thread(r); thread.setName("DelayWorker"); thread.setDaemon(true); return thread; }); LOGGER.info("开始执行调度线程..."); executorService.execute(() -> { while (true) { try { OrderMessage task = queue.take(); LOGGER.info("延迟处理订单消息,{}", task.getDescription()); } catch (Exception e) { LOGGER.error(e.getMessage(), e); } } }); Thread.sleep(Integer.MAX_VALUE); } private static class OrderMessage implements Delayed { private static final DateTimeFormatter F = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); /** * 默认延迟5000毫秒 */ private static final long DELAY_MS = 1000L * 5; /** * 订单ID */ private final String orderId; /** * 创建时间戳 */ private final long timestamp; /** * 过期时间 */ private final long expire; /** * 描述 */ private final String description; public OrderMessage(String orderId, long expireSeconds) { this.orderId = orderId; this.timestamp = System.currentTimeMillis(); this.expire = this.timestamp + expireSeconds * 1000L; this.description = String.format("订单[%s]-创建时间为:%s,超时时间为:%s", orderId, LocalDateTime.ofInstant(Instant.ofEpochMilli(timestamp), ZoneId.systemDefault()).format(F), LocalDateTime.ofInstant(Instant.ofEpochMilli(expire), ZoneId.systemDefault()).format(F)); } public OrderMessage(String orderId) { this.orderId = orderId; this.timestamp = System.currentTimeMillis(); this.expire = this.timestamp + DELAY_MS; this.description = String.format("订单[%s]-创建时间为:%s,超时时间为:%s", orderId, LocalDateTime.ofInstant(Instant.ofEpochMilli(timestamp), ZoneId.systemDefault()).format(F), LocalDateTime.ofInstant(Instant.ofEpochMilli(expire), ZoneId.systemDefault()).format(F)); } public String getOrderId() { return orderId; } public long getTimestamp() { return timestamp; } public long getExpire() { return expire; } public String getDescription() { return description; } @Override public long getDelay(TimeUnit unit) { return unit.convert(this.expire - System.currentTimeMillis(), TimeUnit.MILLISECONDS); } @Override public int compareTo(Delayed o) { return (int) (this.getDelay(TimeUnit.MILLISECONDS) - o.getDelay(TimeUnit.MILLISECONDS)); } } } 复制代码
注意一下，OrderMessage实现Delayed接口，关键是需要实现Delayed#getDelay()和Delayed#compareTo()。运行一下main()方法：
10:16:08.240 [main] INFO club.throwable.delay.DelayQueueMain - 开始执行调度线程... 10:16:13.224 [DelayWorker] INFO club.throwable.delay.DelayQueueMain - 延迟处理订单消息,订单[ORDER_ID_10086]-创建时间为:2019-08-20 10:16:08,超时时间为:2019-08-20 10:16:13 10:16:14.237 [DelayWorker] INFO club.throwable.delay.DelayQueueMain - 延迟处理订单消息,订单[ORDER_ID_10087]-创建时间为:2019-08-20 10:16:08,超时时间为:2019-08-20 10:16:14 10:16:18.237 [DelayWorker] INFO club.throwable.delay.DelayQueueMain - 延迟处理订单消息,订单[ORDER_ID_10088]-创建时间为:2019-08-20 10:16:08,超时时间为:2019-08-20 10:16:18 复制代码
调度框架 + MySQL
使用调度框架对MySQL表进行短间隔轮询是实现难度比较低的方案，通常服务刚上线，表数据不多并且实时性不高的情况下应该首选这个方案。不过要注意以下几点：
- 注意轮询间隔不能太短，否则会对
MySQL实例产生影响。 - 注意每次查询的数量，结果集数量太多有可能会导致调度阻塞和占用应用大量内存，从而影响时效性。
- 注意要设计状态值和最大重试次数，这样才能尽量避免大量数据积压和重复查询的问题。
- 最好通过时间列做索引，查询指定时间范围内的数据。
引入Quartz、MySQL的Java驱动包和spring-boot-starter-jdbc（这里只是为了方便用相对轻量级的框架实现，生产中可以按场景按需选择其他更合理的框架）：
<dependency> <groupId>mysql</groupId> <artifactId>mysql-connector-java</artifactId> <version>5.1.48</version> <scope>test</scope> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-jdbc</artifactId> <version>2.1.7.RELEASE</version> <scope>test</scope> </dependency> <dependency> <groupId>org.quartz-scheduler</groupId> <artifactId>quartz</artifactId> <version>2.3.1</version> <scope>test</scope> </dependency> 复制代码
假设表设计如下：
CREATE DATABASE `delayTask` CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_520_ci; USE `delayTask`; CREATE TABLE `t_order_message` ( id BIGINT UNSIGNED PRIMARY KEY AUTO_INCREMENT, order_id VARCHAR(50) NOT NULL COMMENT '订单ID', create_time DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建日期时间', edit_time DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '修改日期时间', retry_times TINYINT NOT NULL DEFAULT 0 COMMENT '重试次数', order_status TINYINT NOT NULL DEFAULT 0 COMMENT '订单状态', INDEX idx_order_id (order_id), INDEX idx_create_time (create_time) ) COMMENT '订单信息表'; # 写入两条测试数据 INSERT INTO t_order_message(order_id) VALUES ('10086'),('10087'); 复制代码
编写代码：
// 常量 public class OrderConstants { public static final int MAX_RETRY_TIMES = 5; public static final int PENDING = 0; public static final int SUCCESS = 1; public static final int FAIL = -1; public static final int LIMIT = 10; } // 实体 @Builder @Data public class OrderMessage { private Long id; private String orderId; private LocalDateTime createTime; private LocalDateTime editTime; private Integer retryTimes; private Integer orderStatus; } // DAO @RequiredArgsConstructor public class OrderMessageDao { private final JdbcTemplate jdbcTemplate; private static final ResultSetExtractor<List<OrderMessage>> M = r -> { List<OrderMessage> list = Lists.newArrayList(); while (r.next()) { list.add(OrderMessage.builder() .id(r.getLong("id")) .orderId(r.getString("order_id")) .createTime(r.getTimestamp("create_time").toLocalDateTime()) .editTime(r.getTimestamp("edit_time").toLocalDateTime()) .retryTimes(r.getInt("retry_times")) .orderStatus(r.getInt("order_status")) .build()); } return list; }; public List<OrderMessage> selectPendingRecords(LocalDateTime start, LocalDateTime end, List<Integer> statusList, int maxRetryTimes, int limit) { StringJoiner joiner = new StringJoiner(","); statusList.forEach(s -> joiner.add(String.valueOf(s))); return jdbcTemplate.query("SELECT * FROM t_order_message WHERE create_time >= ? AND create_time <= ? " + "AND order_status IN (?) AND retry_times < ? LIMIT ?", p -> { p.setTimestamp(1, Timestamp.valueOf(start)); p.setTimestamp(2, Timestamp.valueOf(end)); p.setString(3, joiner.toString()); p.setInt(4, maxRetryTimes); p.setInt(5, limit); }, M); } public int updateOrderStatus(Long id, int status) { return jdbcTemplate.update("UPDATE t_order_message SET order_status = ?,edit_time = ? WHERE id =?", p -> { p.setInt(1, status); p.setTimestamp(2, Timestamp.valueOf(LocalDateTime.now())); p.setLong(3, id); }); } } // Service @RequiredArgsConstructor public class OrderMessageService { private static final Logger LOGGER = LoggerFactory.getLogger(OrderMessageService.class); private final OrderMessageDao orderMessageDao; private static final List<Integer> STATUS = Lists.newArrayList(); static { STATUS.add(OrderConstants.PENDING); STATUS.add(OrderConstants.FAIL); } public void executeDelayJob() { LOGGER.info("订单处理定时任务开始执行......"); LocalDateTime end = LocalDateTime.now(); // 一天前 LocalDateTime start = end.minusDays(1); List<OrderMessage> list = orderMessageDao.selectPendingRecords(start, end, STATUS, OrderConstants.MAX_RETRY_TIMES, OrderConstants.LIMIT); if (!list.isEmpty()) { for (OrderMessage m : list) { LOGGER.info("处理订单[{}],状态由{}更新为{}", m.getOrderId(), m.getOrderStatus(), OrderConstants.SUCCESS); // 这里其实可以优化为批量更新 orderMessageDao.updateOrderStatus(m.getId(), OrderConstants.SUCCESS); } } LOGGER.info("订单处理定时任务开始完毕......"); } } // Job @DisallowConcurrentExecution public class OrderMessageDelayJob implements Job { @Override public void execute(JobExecutionContext jobExecutionContext) throws JobExecutionException { OrderMessageService service = (OrderMessageService) jobExecutionContext.getMergedJobDataMap().get("orderMessageService"); service.executeDelayJob(); } public static void main(String[] args) throws Exception { HikariConfig config = new HikariConfig(); config.setJdbcUrl("jdbc:mysql://localhost:3306/delayTask?useSSL=false&characterEncoding=utf8"); config.setDriverClassName(Driver.class.getName()); config.setUsername("root"); config.setPassword("root"); HikariDataSource dataSource = new HikariDataSource(config); OrderMessageDao orderMessageDao = new OrderMessageDao(new JdbcTemplate(dataSource)); OrderMessageService service = new OrderMessageService(orderMessageDao); // 内存模式的调度器 StdSchedulerFactory factory = new StdSchedulerFactory(); Scheduler scheduler = factory.getScheduler(); // 这里没有用到IOC容器,直接用Quartz数据集合传递服务引用 JobDataMap jobDataMap = new JobDataMap(); jobDataMap.put("orderMessageService", service); // 新建Job JobDetail job = JobBuilder.newJob(OrderMessageDelayJob.class) .withIdentity("orderMessageDelayJob", "delayJob") .usingJobData(jobDataMap) .build(); // 新建触发器,10秒执行一次 Trigger trigger = TriggerBuilder.newTrigger() .withIdentity("orderMessageDelayTrigger", "delayJob") .withSchedule(SimpleScheduleBuilder.simpleSchedule().withIntervalInSeconds(10).repeatForever()) .build(); scheduler.scheduleJob(job, trigger); // 启动调度器 scheduler.start(); Thread.sleep(Integer.MAX_VALUE); } } 复制代码
这个例子里面用了create_time做轮询，实际上可以添加一个调度时间schedule_time列做轮询，这样子才能更容易定制空闲时和忙碌时候的调度策略。上面的示例的运行效果如下：
11:58:27.202 [main] INFO org.quartz.core.QuartzScheduler - Scheduler meta-data: Quartz Scheduler (v2.3.1) 'DefaultQuartzScheduler' with instanceId 'NON_CLUSTERED' Scheduler class: 'org.quartz.core.QuartzScheduler' - running locally. NOT STARTED. Currently in standby mode. Number of jobs executed: 0 Using thread pool 'org.quartz.simpl.SimpleThreadPool' - with 10 threads. Using job-store 'org.quartz.simpl.RAMJobStore' - which does not support persistence. and is not clustered. 11:58:27.202 [main] INFO org.quartz.impl.StdSchedulerFactory - Quartz scheduler 'DefaultQuartzScheduler' initialized from default resource file in Quartz package: 'quartz.properties' 11:58:27.202 [main] INFO org.quartz.impl.StdSchedulerFactory - Quartz scheduler version: 2.3.1 11:58:27.209 [main] INFO org.quartz.core.QuartzScheduler - Scheduler DefaultQuartzScheduler_$_NON_CLUSTERED started. 11:58:27.212 [DefaultQuartzScheduler_QuartzSchedulerThread] DEBUG org.quartz.core.QuartzSchedulerThread - batch acquisition of 1 triggers 11:58:27.217 [DefaultQuartzScheduler_QuartzSchedulerThread] DEBUG org.quartz.simpl.PropertySettingJobFactory - Producing instance of Job 'delayJob.orderMessageDelayJob', class=club.throwable.jdbc.OrderMessageDelayJob 11:58:27.219 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Added connection com.mysql.jdbc.JDBC4Connection@10eb8c53 11:58:27.220 [DefaultQuartzScheduler_QuartzSchedulerThread] DEBUG org.quartz.core.QuartzSchedulerThread - batch acquisition of 0 triggers 11:58:27.221 [DefaultQuartzScheduler_Worker-1] DEBUG org.quartz.core.JobRunShell - Calling execute on job delayJob.orderMessageDelayJob 11:58:34.440 [DefaultQuartzScheduler_Worker-1] INFO club.throwable.jdbc.OrderMessageService - 订单处理定时任务开始执行...... 11:58:34.451 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Added connection com.mysql.jdbc.JDBC4Connection@3d27ece4 11:58:34.459 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Added connection com.mysql.jdbc.JDBC4Connection@64e808af 11:58:34.470 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Added connection com.mysql.jdbc.JDBC4Connection@79c8c2b7 11:58:34.477 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Added connection com.mysql.jdbc.JDBC4Connection@19a62369 11:58:34.485 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Added connection com.mysql.jdbc.JDBC4Connection@1673d017 11:58:34.485 [HikariPool-1 connection adder] DEBUG com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - After adding stats (total=10, active=0, idle=10, waiting=0) 11:58:34.559 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - Executing prepared SQL query 11:58:34.565 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - Executing prepared SQL statement [SELECT * FROM t_order_message WHERE create_time >= ? AND create_time <= ? AND order_status IN (?) AND retry_times < ? LIMIT ?] 11:58:34.645 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.datasource.DataSourceUtils - Fetching JDBC Connection from DataSource 11:58:35.210 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - SQLWarning ignored: SQL state '22007', error code '1292', message [Truncated incorrect DOUBLE value: '0,-1'] 11:58:35.335 [DefaultQuartzScheduler_Worker-1] INFO club.throwable.jdbc.OrderMessageService - 处理订单[10086],状态由0更新为1 11:58:35.342 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - Executing prepared SQL update 11:58:35.346 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - Executing prepared SQL statement [UPDATE t_order_message SET order_status = ?,edit_time = ? WHERE id =?] 11:58:35.347 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.datasource.DataSourceUtils - Fetching JDBC Connection from DataSource 11:58:35.354 [DefaultQuartzScheduler_Worker-1] INFO club.throwable.jdbc.OrderMessageService - 处理订单[10087],状态由0更新为1 11:58:35.355 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - Executing prepared SQL update 11:58:35.355 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.core.JdbcTemplate - Executing prepared SQL statement [UPDATE t_order_message SET order_status = ?,edit_time = ? WHERE id =?] 11:58:35.355 [DefaultQuartzScheduler_Worker-1] DEBUG org.springframework.jdbc.datasource.DataSourceUtils - Fetching JDBC Connection from DataSource 11:58:35.361 [DefaultQuartzScheduler_Worker-1] INFO club.throwable.jdbc.OrderMessageService - 订单处理定时任务开始完毕...... 11:58:35.363 [DefaultQuartzScheduler_QuartzSchedulerThread] DEBUG org.quartz.core.QuartzSchedulerThread - batch acquisition of 1 triggers 11:58:37.206 [DefaultQuartzScheduler_QuartzSchedulerThread] DEBUG org.quartz.simpl.PropertySettingJobFactory - Producing instance of Job 'delayJob.orderMessageDelayJob', class=club.throwable.jdbc.OrderMessageDelayJob 11:58:37.206 [DefaultQuartzScheduler_QuartzSchedulerThread] DEBUG org.quartz.core.QuartzSchedulerThread - batch acquisition of 0 triggers 复制代码
RabbitMQ死信队列
使用RabbitMQ死信队列依赖于RabbitMQ的两个特性：TTL和DLX。
TTL：Time To Live，消息存活时间，包括两个维度：队列消息存活时间和消息本身的存活时间。DLX：Dead Letter Exchange，死信交换器。
画个图描述一下这两个特性：
下面为了简单起见，TTL使用了针对队列的维度。引入RabbitMQ的Java驱动：
<dependency> <groupId>com.rabbitmq</groupId> <artifactId>amqp-client</artifactId> <version>5.7.3</version> <scope>test</scope> </dependency> 复制代码
代码如下：
public class DlxMain { private static final DateTimeFormatter F = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); private static final Logger LOGGER = LoggerFactory.getLogger(DlxMain.class); public static void main(String[] args) throws Exception { ConnectionFactory factory = new ConnectionFactory(); Connection connection = factory.newConnection(); Channel producerChannel = connection.createChannel(); Channel consumerChannel = connection.createChannel(); // dlx交换器名称为dlx.exchange,类型是direct,绑定键为dlx.key,队列名为dlx.queue producerChannel.exchangeDeclare("dlx.exchange", "direct"); producerChannel.queueDeclare("dlx.queue", false, false, false, null); producerChannel.queueBind("dlx.queue", "dlx.exchange", "dlx.key"); Map<String, Object> queueArgs = new HashMap<>(); // 设置队列消息过期时间,5秒 queueArgs.put("x-message-ttl", 5000); // 指定DLX相关参数 queueArgs.put("x-dead-letter-exchange", "dlx.exchange"); queueArgs.put("x-dead-letter-routing-key", "dlx.key"); // 声明业务队列 producerChannel.queueDeclare("business.queue", false, false, false, queueArgs); ExecutorService executorService = Executors.newSingleThreadExecutor(r -> { Thread thread = new Thread(r); thread.setDaemon(true); thread.setName("DlxConsumer"); return thread; }); // 启动消费者 executorService.execute(() -> { try { consumerChannel.basicConsume("dlx.queue", true, new DlxConsumer(consumerChannel)); } catch (IOException e) { LOGGER.error(e.getMessage(), e); } }); OrderMessage message = new OrderMessage("10086"); producerChannel.basicPublish("", "business.queue", MessageProperties.TEXT_PLAIN, message.getDescription().getBytes(StandardCharsets.UTF_8)); LOGGER.info("发送消息成功,订单ID:{}", message.getOrderId()); message = new OrderMessage("10087"); producerChannel.basicPublish("", "business.queue", MessageProperties.TEXT_PLAIN, message.getDescription().getBytes(StandardCharsets.UTF_8)); LOGGER.info("发送消息成功,订单ID:{}", message.getOrderId()); message = new OrderMessage("10088"); producerChannel.basicPublish("", "business.queue", MessageProperties.TEXT_PLAIN, message.getDescription().getBytes(StandardCharsets.UTF_8)); LOGGER.info("发送消息成功,订单ID:{}", message.getOrderId()); Thread.sleep(Integer.MAX_VALUE); } private static class DlxConsumer extends DefaultConsumer { DlxConsumer(Channel channel) { super(channel); } @Override public void handleDelivery(String consumerTag, Envelope envelope, AMQP.BasicProperties properties, byte[] body) throws IOException { LOGGER.info("处理消息成功:{}", new String(body, StandardCharsets.UTF_8)); } } private static class OrderMessage { private final String orderId; private final long timestamp; private final String description; OrderMessage(String orderId) { this.orderId = orderId; this.timestamp = System.currentTimeMillis(); this.description = String.format("订单[%s],订单创建时间为:%s", orderId, LocalDateTime.ofInstant(Instant.ofEpochMilli(timestamp), ZoneId.systemDefault()).format(F)); } public String getOrderId() { return orderId; } public long getTimestamp() { return timestamp; } public String getDescription() { return description; } } } 复制代码
运行main()方法结果如下：
16:35:58.638 [main] INFO club.throwable.dlx.DlxMain - 发送消息成功,订单ID:10086 16:35:58.641 [main] INFO club.throwable.dlx.DlxMain - 发送消息成功,订单ID:10087 16:35:58.641 [main] INFO club.throwable.dlx.DlxMain - 发送消息成功,订单ID:10088 16:36:03.646 [pool-1-thread-4] INFO club.throwable.dlx.DlxMain - 处理消息成功:订单[10086],订单创建时间为:2019-08-20 16:35:58 16:36:03.670 [pool-1-thread-5] INFO club.throwable.dlx.DlxMain - 处理消息成功:订单[10087],订单创建时间为:2019-08-20 16:35:58 16:36:03.670 [pool-1-thread-6] INFO club.throwable.dlx.DlxMain - 处理消息成功:订单[10088],订单创建时间为:2019-08-20 16:35:58 复制代码
时间轮
时间轮TimingWheel是一种高效、低延迟的调度数据结构，底层采用数组实现存储任务列表的环形队列，示意图如下：
这里暂时不对时间轮和其实现作分析，只简单举例说明怎么使用时间轮实现延时任务。这里使用Netty提供的HashedWheelTimer，引入依赖：
<dependency> <groupId>io.netty</groupId> <artifactId>netty-common</artifactId> <version>4.1.39.Final</version> </dependency> 复制代码
代码如下：
public class HashedWheelTimerMain { private static final DateTimeFormatter F = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss.SSS"); public static void main(String[] args) throws Exception { AtomicInteger counter = new AtomicInteger(); ThreadFactory factory = r -> { Thread thread = new Thread(r); thread.setDaemon(true); thread.setName("HashedWheelTimerWorker-" + counter.getAndIncrement()); return thread; }; // tickDuration - 每tick一次的时间间隔, 每tick一次就会到达下一个槽位 // unit - tickDuration的时间单位 // ticksPerWhee - 时间轮中的槽位数 Timer timer = new HashedWheelTimer(factory, 1, TimeUnit.SECONDS, 60); TimerTask timerTask = new DefaultTimerTask("10086"); timer.newTimeout(timerTask, 5, TimeUnit.SECONDS); timerTask = new DefaultTimerTask("10087"); timer.newTimeout(timerTask, 10, TimeUnit.SECONDS); timerTask = new DefaultTimerTask("10088"); timer.newTimeout(timerTask, 15, TimeUnit.SECONDS); Thread.sleep(Integer.MAX_VALUE); } private static class DefaultTimerTask implements TimerTask { private final String orderId; private final long timestamp; public DefaultTimerTask(String orderId) { this.orderId = orderId; this.timestamp = System.currentTimeMillis(); } @Override public void run(Timeout timeout) throws Exception { System.out.println(String.format("任务执行时间:%s,订单创建时间:%s,订单ID:%s", LocalDateTime.now().format(F), LocalDateTime.ofInstant(Instant.ofEpochMilli(timestamp), ZoneId.systemDefault()).format(F), orderId)); } } } 复制代码
运行结果：
任务执行时间:2019-08-20 17:19:49.310,订单创建时间:2019-08-20 17:19:43.294,订单ID:10086 任务执行时间:2019-08-20 17:19:54.297,订单创建时间:2019-08-20 17:19:43.301,订单ID:10087 任务执行时间:2019-08-20 17:19:59.297,订单创建时间:2019-08-20 17:19:43.301,订单ID:10088 复制代码
一般来说，任务执行的时候应该使用另外的业务线程池，以免阻塞时间轮本身的运动。
