使用Redis實現延時任務(二)
前提
前一篇文章經過Redis的有序集合Sorted Set和調度框架Quartz實例一版簡單的延時任務，可是有兩個相對重要的問題沒有解決：java
- 分片。
- 監控。
這篇文章的內容就是要完善這兩個方面的功能。前置文章：使用Redis實現延時任務(一)。web
爲何須要分片
這裏從新貼一下查詢腳本dequeue.lua的內容：redis
-- 參考jesque的部分Lua腳本實現
local zset_key = KEYS[1]
local hash_key = KEYS[2]
local min_score = ARGV[1]
local max_score = ARGV[2]
local offset = ARGV[3]
local limit = ARGV[4]
-- TYPE命令的返回結果是{'ok':'zset'}這樣子,這裏利用next作一輪迭代
local status, type = next(redis.call('TYPE', zset_key))
if status ~= nil and status == 'ok' then
if type == 'zset' then
local list = redis.call('ZREVRANGEBYSCORE', zset_key, max_score, min_score, 'LIMIT', offset, limit)
if list ~= nil and #list > 0 then
-- unpack函數能把table轉化爲可變參數
redis.call('ZREM', zset_key, unpack(list))
local result = redis.call('HMGET', hash_key, unpack(list))
redis.call('HDEL', hash_key, unpack(list))
return result
end
end
end
return nil
這個腳本一共用到了四個命令ZREVRANGEBYSCORE、ZREM、HMGET和HDEL（TYPE命令的時間複雜度能夠忽略）：spring
| 命令 | 時間複雜度 | 參數說明 |
|---|---|---|
ZREVRANGEBYSCORE |
O(log(N)+M) |
N是有序集合中的元素總數，M是返回的元素的數量 |
ZREM |
O(M*log(N)) |
N是有序集合中的元素總數，M是成功移除的元素的數量 |
HMGET |
O(L) |
L是成功返回的域的數量 |
HDEL |
O(L) |
L是要刪除的域的數量 |
接下來須要結合場景和具體參數分析，假如在生產環境，有序集合的元素總量維持在10000每小時（也就是說業務量是每小時下單1萬筆），因爲查詢Sorted Set和Hash的數據同時作了刪除，那麼30分鐘內常駐在這兩個集合中的數據有5000條，也就是上面表中的N = 5000。假設咱們初步定義查詢的LIMIT值爲100，也就是上面的M值爲100，假設Redis中每一個操做單元的耗時簡單認爲是T，那麼分析一下5000條數據處理的耗時：shell
| 序號 | 集合基數 | ZREVRANGEBYSCORE |
ZREM |
HMGET |
HDEL |
|---|---|---|---|---|---|
| 1 | 5000 |
log(5000T) + 100T |
log(5000T) * 100 |
100T |
100T |
| 2 | 4900 |
log(4900T) + 100T |
log(4900T) * 100 |
100T |
100T |
| 3 | 4800 |
log(4800T) + 100T |
log(4800T) * 100 |
100T |
100T |
| ... | ... | ... | ... | ... | ... |
理論上，腳本用到的四個命令中，ZREM命令的耗時是最大的，而ZREVRANGEBYSCORE和ZREM的時間複雜度函數都是M * log(N)，所以控制集合元素基數N對於下降Lua腳本運行的耗時是有必定幫助的。架構
分片
上面分析了dequeue.lua的時間複雜度，準備好的分片方案有兩個：app
- 方案一：單
Redis實例，對Sorted Set和Hash兩個集合的數據進行分片。 - 方案二：基於多個
Redis實例（能夠是哨兵或者集羣），實施方案一的分片操做。
爲了簡單起見，後面的例子中分片的數量（shardingCount）設計爲2，生產中分片數量應該根據實際狀況定製。預設使用長整型的用戶ID字段userId取模進行分片，假定測試數據中的userId是均勻分佈的。框架
通用實體：運維
@Data
public class OrderMessage {
private String orderId;
private BigDecimal amount;
private Long userId;
private String timestamp;
}
延遲隊列接口：jvm
public interface OrderDelayQueue {
void enqueue(OrderMessage message);
List<OrderMessage> dequeue(String min, String max, String offset, String limit, int index);
List<OrderMessage> dequeue(int index);
String enqueueSha();
String dequeueSha();
}
單Redis實例分片
單Redis實例分片比較簡單，示意圖以下：
編寫隊列實現代碼以下（部分參數寫死，僅供參考，切勿照搬到生產中）：
@RequiredArgsConstructor
@Component
public class RedisOrderDelayQueue implements OrderDelayQueue, InitializingBean {
private static final String MIN_SCORE = "0";
private static final String OFFSET = "0";
private static final String LIMIT = "10";
/**
* 分片數量
*/
private static final long SHARDING_COUNT = 2L;
private static final String ORDER_QUEUE_PREFIX = "ORDER_QUEUE_";
private static final String ORDER_DETAIL_QUEUE_PREFIX = "ORDER_DETAIL_QUEUE_";
private static final String ENQUEUE_LUA_SCRIPT_LOCATION = "/lua/enqueue.lua";
private static final String DEQUEUE_LUA_SCRIPT_LOCATION = "/lua/dequeue.lua";
private static final AtomicReference<String> ENQUEUE_LUA_SHA = new AtomicReference<>();
private static final AtomicReference<String> DEQUEUE_LUA_SHA = new AtomicReference<>();
private final JedisProvider jedisProvider;
@Override
public void enqueue(OrderMessage message) {
List<String> args = Lists.newArrayList();
args.add(message.getOrderId());
args.add(String.valueOf(System.currentTimeMillis()));
args.add(message.getOrderId());
args.add(JSON.toJSONString(message));
List<String> keys = Lists.newArrayList();
long index = message.getUserId() % SHARDING_COUNT;
keys.add(ORDER_QUEUE_PREFIX + index);
keys.add(ORDER_DETAIL_QUEUE_PREFIX + index);
try (Jedis jedis = jedisProvider.provide()) {
jedis.evalsha(ENQUEUE_LUA_SHA.get(), keys, args);
}
}
@Override
public List<OrderMessage> dequeue(int index) {
// 30分鐘以前
String maxScore = String.valueOf(System.currentTimeMillis() - 30 * 60 * 1000);
return dequeue(MIN_SCORE, maxScore, OFFSET, LIMIT, index);
}
@SuppressWarnings("unchecked")
@Override
public List<OrderMessage> dequeue(String min, String max, String offset, String limit, int index) {
List<String> args = new ArrayList<>();
args.add(min);
args.add(max);
args.add(offset);
args.add(limit);
List<OrderMessage> result = Lists.newArrayList();
List<String> keys = Lists.newArrayList();
keys.add(ORDER_QUEUE_PREFIX + index);
keys.add(ORDER_DETAIL_QUEUE_PREFIX + index);
try (Jedis jedis = jedisProvider.provide()) {
List<String> eval = (List<String>) jedis.evalsha(DEQUEUE_LUA_SHA.get(), keys, args);
if (null != eval) {
for (String e : eval) {
result.add(JSON.parseObject(e, OrderMessage.class));
}
}
}
return result;
}
@Override
public String enqueueSha() {
return ENQUEUE_LUA_SHA.get();
}
@Override
public String dequeueSha() {
return DEQUEUE_LUA_SHA.get();
}
@Override
public void afterPropertiesSet() throws Exception {
// 加載Lua腳本
loadLuaScript();
}
private void loadLuaScript() throws Exception {
try (Jedis jedis = jedisProvider.provide()) {
ClassPathResource resource = new ClassPathResource(ENQUEUE_LUA_SCRIPT_LOCATION);
String luaContent = StreamUtils.copyToString(resource.getInputStream(), StandardCharsets.UTF_8);
String sha = jedis.scriptLoad(luaContent);
ENQUEUE_LUA_SHA.compareAndSet(null, sha);
resource = new ClassPathResource(DEQUEUE_LUA_SCRIPT_LOCATION);
luaContent = StreamUtils.copyToString(resource.getInputStream(), StandardCharsets.UTF_8);
sha = jedis.scriptLoad(luaContent);
DEQUEUE_LUA_SHA.compareAndSet(null, sha);
}
}
}
消費者定時任務的實現以下：
DisallowConcurrentExecution
@Component
public class OrderMessageConsumer implements Job {
private static final Logger LOGGER = LoggerFactory.getLogger(OrderMessageConsumer.class);
private static final AtomicInteger COUNTER = new AtomicInteger();
/**
* 初始化業務線程池
*/
private static final ExecutorService BUSINESS_WORKER_POOL = Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors(), r -> {
Thread thread = new Thread(r);
thread.setDaemon(true);
thread.setName("OrderMessageConsumerWorker-" + COUNTER.getAndIncrement());
return thread;
});
@Autowired
private OrderDelayQueue orderDelayQueue;
@Override
public void execute(JobExecutionContext context) throws JobExecutionException {
// 這裏爲了簡單起見，分片的下標暫時使用Quartz的任務執行上下文存放
int shardingIndex = context.getMergedJobDataMap().getInt("shardingIndex");
LOGGER.info("訂單消息消費者定時任務開始執行,shardingIndex:[{}]...", shardingIndex);
List<OrderMessage> dequeue = orderDelayQueue.dequeue(shardingIndex);
if (null != dequeue) {
final CountDownLatch latch = new CountDownLatch(1);
BUSINESS_WORKER_POOL.execute(new ConsumeTask(latch, dequeue, shardingIndex));
try {
latch.await();
} catch (InterruptedException ignore) {
//ignore
}
}
LOGGER.info("訂單消息消費者定時任務執行完畢,shardingIndex:[{}]...", shardingIndex);
}
@RequiredArgsConstructor
private static class ConsumeTask implements Runnable {
private final CountDownLatch latch;
private final List<OrderMessage> messages;
private final int shardingIndex;
@Override
public void run() {
try {
for (OrderMessage message : messages) {
LOGGER.info("shardingIndex:[{}],處理訂單消息,內容:{}", shardingIndex, JSON.toJSONString(message));
// 模擬耗時
TimeUnit.MILLISECONDS.sleep(50);
}
} catch (Exception ignore) {
} finally {
latch.countDown();
}
}
}
}
啓動定時任務和寫入測試數據的CommandLineRunner實現以下：
@Component
public class QuartzJobStartCommandLineRunner implements CommandLineRunner {
@Autowired
private Scheduler scheduler;
@Autowired
private JedisProvider jedisProvider;
@Override
public void run(String... args) throws Exception {
int shardingCount = 2;
// 準備測試數據
prepareOrderMessageData(shardingCount);
for (ConsumerTask task : prepareConsumerTasks(shardingCount)) {
scheduler.scheduleJob(task.getJobDetail(), task.getTrigger());
}
}
private void prepareOrderMessageData(int shardingCount) throws Exception {
DateTimeFormatter f = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss.SSS");
try (Jedis jedis = jedisProvider.provide()) {
List<OrderMessage> messages = Lists.newArrayList();
for (int i = 0; i < 100; i++) {
OrderMessage message = new OrderMessage();
message.setAmount(BigDecimal.valueOf(i));
message.setOrderId("ORDER_ID_" + i);
message.setUserId((long) i);
message.setTimestamp(LocalDateTime.now().format(f));
messages.add(message);
}
for (OrderMessage message : messages) {
// 30分鐘前
Double score = Double.valueOf(String.valueOf(System.currentTimeMillis() - 30 * 60 * 1000));
long index = message.getUserId() % shardingCount;
jedis.hset("ORDER_DETAIL_QUEUE_" + index, message.getOrderId(), JSON.toJSONString(message));
jedis.zadd("ORDER_QUEUE_" + index, score, message.getOrderId());
}
}
}
private List<ConsumerTask> prepareConsumerTasks(int shardingCount) {
List<ConsumerTask> tasks = Lists.newArrayList();
for (int i = 0; i < shardingCount; i++) {
JobDetail jobDetail = JobBuilder.newJob(OrderMessageConsumer.class)
.withIdentity("OrderMessageConsumer-" + i, "DelayTask")
.usingJobData("shardingIndex", i)
.build();
Trigger trigger = TriggerBuilder.newTrigger()
.withIdentity("OrderMessageConsumerTrigger-" + i, "DelayTask")
.withSchedule(SimpleScheduleBuilder.simpleSchedule().withIntervalInSeconds(10).repeatForever())
.build();
tasks.add(new ConsumerTask(jobDetail, trigger));
}
return tasks;
}
@Getter
@RequiredArgsConstructor
private static class ConsumerTask {
private final JobDetail jobDetail;
private final Trigger trigger;
}
}
啓動應用，輸出以下：
2019-08-28 00:13:20.648 INFO 50248 --- [ main] c.t.s.s.NoneJdbcSpringApplication : Started NoneJdbcSpringApplication in 1.35 seconds (JVM running for 5.109)
2019-08-28 00:13:20.780 INFO 50248 --- [ryBean_Worker-1] c.t.s.sharding.OrderMessageConsumer : 訂單消息消費者定時任務開始執行,shardingIndex:[0]...
2019-08-28 00:13:20.781 INFO 50248 --- [ryBean_Worker-2] c.t.s.sharding.OrderMessageConsumer : 訂單消息消費者定時任務開始執行,shardingIndex:[1]...
2019-08-28 00:13:20.788 INFO 50248 --- [onsumerWorker-1] c.t.s.sharding.OrderMessageConsumer : shardingIndex:[1],處理訂單消息,內容:{"amount":99,"orderId":"ORDER_ID_99","timestamp":"2019-08-28 00:13:20.657","userId":99}
2019-08-28 00:13:20.788 INFO 50248 --- [onsumerWorker-0] c.t.s.sharding.OrderMessageConsumer : shardingIndex:[0],處理訂單消息,內容:{"amount":98,"orderId":"ORDER_ID_98","timestamp":"2019-08-28 00:13:20.657","userId":98}
2019-08-28 00:13:20.840 INFO 50248 --- [onsumerWorker-1] c.t.s.sharding.OrderMessageConsumer : shardingIndex:[1],處理訂單消息,內容:{"amount":97,"orderId":"ORDER_ID_97","timestamp":"2019-08-28 00:13:20.657","userId":97}
2019-08-28 00:13:20.840 INFO 50248 --- [onsumerWorker-0] c.t.s.sharding.OrderMessageConsumer : shardingIndex:[0],處理訂單消息,內容:{"amount":96,"orderId":"ORDER_ID_96","timestamp":"2019-08-28 00:13:20.657","userId":96}
// ... 省略大量輸出
2019-08-28 00:13:21.298 INFO 50248 --- [ryBean_Worker-1] c.t.s.sharding.OrderMessageConsumer : 訂單消息消費者定時任務執行完畢,shardingIndex:[0]...
2019-08-28 00:13:21.298 INFO 50248 --- [ryBean_Worker-2] c.t.s.sharding.OrderMessageConsumer : 訂單消息消費者定時任務執行完畢,shardingIndex:[1]...
// ... 省略大量輸出
多Redis實例分片
單Redis實例分片其實存在一個問題，就是Redis實例老是單線程處理客戶端的命令，即便客戶端是多個線程執行Redis命令，示意圖以下：
這種狀況下，雖然經過分片下降了Lua腳本命令的複雜度，可是Redis的命令處理模型（單線程）也有可能成爲另外一個性能瓶頸隱患。所以，能夠考慮基於多Redis實例進行分片。
這裏爲了簡單起見，用兩個單點的Redis實例作編碼示例。代碼以下：
// Jedis提供者
@Component
public class JedisProvider implements InitializingBean {
private final Map<Long, JedisPool> pools = Maps.newConcurrentMap();
private JedisPool defaultPool;
@Override
public void afterPropertiesSet() throws Exception {
JedisPool pool = new JedisPool("localhost");
defaultPool = pool;
pools.put(0L, pool);
// 這個是虛擬機上的redis實例
pool = new JedisPool("192.168.56.200");
pools.put(1L, pool);
}
public Jedis provide(Long index) {
return pools.getOrDefault(index, defaultPool).getResource();
}
}
// 訂單消息
@Data
public class OrderMessage {
private String orderId;
private BigDecimal amount;
private Long userId;
}
// 訂單延時隊列接口
public interface OrderDelayQueue {
void enqueue(OrderMessage message);
List<OrderMessage> dequeue(String min, String max, String offset, String limit, long index);
List<OrderMessage> dequeue(long index);
String enqueueSha(long index);
String dequeueSha(long index);
}
// 延時隊列實現
@RequiredArgsConstructor
@Component
public class RedisOrderDelayQueue implements OrderDelayQueue, InitializingBean {
private static final String MIN_SCORE = "0";
private static final String OFFSET = "0";
private static final String LIMIT = "10";
private static final long SHARDING_COUNT = 2L;
private static final String ORDER_QUEUE = "ORDER_QUEUE";
private static final String ORDER_DETAIL_QUEUE = "ORDER_DETAIL_QUEUE";
private static final String ENQUEUE_LUA_SCRIPT_LOCATION = "/lua/enqueue.lua";
private static final String DEQUEUE_LUA_SCRIPT_LOCATION = "/lua/dequeue.lua";
private static final ConcurrentMap<Long, String> ENQUEUE_LUA_SHA = Maps.newConcurrentMap();
private static final ConcurrentMap<Long, String> DEQUEUE_LUA_SHA = Maps.newConcurrentMap();
private final JedisProvider jedisProvider;
@Override
public void enqueue(OrderMessage message) {
List<String> args = Lists.newArrayList();
args.add(message.getOrderId());
args.add(String.valueOf(System.currentTimeMillis() - 30 * 60 * 1000));
args.add(message.getOrderId());
args.add(JSON.toJSONString(message));
List<String> keys = Lists.newArrayList();
long index = message.getUserId() % SHARDING_COUNT;
keys.add(ORDER_QUEUE);
keys.add(ORDER_DETAIL_QUEUE);
try (Jedis jedis = jedisProvider.provide(index)) {
jedis.evalsha(ENQUEUE_LUA_SHA.get(index), keys, args);
}
}
@Override
public List<OrderMessage> dequeue(long index) {
// 30分鐘以前
String maxScore = String.valueOf(System.currentTimeMillis() - 30 * 60 * 1000);
return dequeue(MIN_SCORE, maxScore, OFFSET, LIMIT, index);
}
@SuppressWarnings("unchecked")
@Override
public List<OrderMessage> dequeue(String min, String max, String offset, String limit, long index) {
List<String> args = new ArrayList<>();
args.add(min);
args.add(max);
args.add(offset);
args.add(limit);
List<OrderMessage> result = Lists.newArrayList();
List<String> keys = Lists.newArrayList();
keys.add(ORDER_QUEUE);
keys.add(ORDER_DETAIL_QUEUE);
try (Jedis jedis = jedisProvider.provide(index)) {
List<String> eval = (List<String>) jedis.evalsha(DEQUEUE_LUA_SHA.get(index), keys, args);
if (null != eval) {
for (String e : eval) {
result.add(JSON.parseObject(e, OrderMessage.class));
}
}
}
return result;
}
@Override
public String enqueueSha(long index) {
return ENQUEUE_LUA_SHA.get(index);
}
@Override
public String dequeueSha(long index) {
return DEQUEUE_LUA_SHA.get(index);
}
@Override
public void afterPropertiesSet() throws Exception {
// 加載Lua腳本
loadLuaScript();
}
private void loadLuaScript() throws Exception {
for (long i = 0; i < SHARDING_COUNT; i++) {
try (Jedis jedis = jedisProvider.provide(i)) {
ClassPathResource resource = new ClassPathResource(ENQUEUE_LUA_SCRIPT_LOCATION);
String luaContent = StreamUtils.copyToString(resource.getInputStream(), StandardCharsets.UTF_8);
String sha = jedis.scriptLoad(luaContent);
ENQUEUE_LUA_SHA.put(i, sha);
resource = new ClassPathResource(DEQUEUE_LUA_SCRIPT_LOCATION);
luaContent = StreamUtils.copyToString(resource.getInputStream(), StandardCharsets.UTF_8);
sha = jedis.scriptLoad(luaContent);
DEQUEUE_LUA_SHA.put(i, sha);
}
}
}
}
// 消費者
public class OrderMessageConsumer implements Job {
private static final Logger LOGGER = LoggerFactory.getLogger(OrderMessageConsumer.class);
private static final AtomicInteger COUNTER = new AtomicInteger();
// 初始化業務線程池
private final ExecutorService businessWorkerPool = Executors.newSingleThreadExecutor(r -> {
Thread thread = new Thread(r);
thread.setDaemon(true);
thread.setName("OrderMessageConsumerWorker-" + COUNTER.getAndIncrement());
return thread;
});
@Autowired
private OrderDelayQueue orderDelayQueue;
@Override
public void execute(JobExecutionContext context) throws JobExecutionException {
long shardingIndex = context.getMergedJobDataMap().getLong("shardingIndex");
LOGGER.info("訂單消息消費者定時任務開始執行,shardingIndex:[{}]...", shardingIndex);
List<OrderMessage> dequeue = orderDelayQueue.dequeue(shardingIndex);
if (null != dequeue) {
// 這裏的倒數柵欄，在線程池資源充足的前提下能夠去掉
final CountDownLatch latch = new CountDownLatch(1);
businessWorkerPool.execute(new ConsumeTask(latch, dequeue, shardingIndex));
try {
latch.await();
} catch (InterruptedException ignore) {
//ignore
}
}
LOGGER.info("訂單消息消費者定時任務執行完畢,shardingIndex:[{}]...", shardingIndex);
}
@RequiredArgsConstructor
private static class ConsumeTask implements Runnable {
private final CountDownLatch latch;
private final List<OrderMessage> messages;
private final long shardingIndex;
@Override
public void run() {
try {
for (OrderMessage message : messages) {
LOGGER.info("shardingIndex:[{}],處理訂單消息,內容:{}", shardingIndex, JSON.toJSONString(message));
// 模擬處理耗時50毫秒
TimeUnit.MILLISECONDS.sleep(50);
}
} catch (Exception ignore) {
} finally {
latch.countDown();
}
}
}
}
// 配置
@Configuration
public class QuartzConfiguration {
@Bean
public AutowiredSupportQuartzJobFactory autowiredSupportQuartzJobFactory() {
return new AutowiredSupportQuartzJobFactory();
}
@Bean
public SchedulerFactoryBean schedulerFactoryBean(AutowiredSupportQuartzJobFactory autowiredSupportQuartzJobFactory) {
SchedulerFactoryBean factory = new SchedulerFactoryBean();
factory.setSchedulerName("RamScheduler");
factory.setAutoStartup(true);
factory.setJobFactory(autowiredSupportQuartzJobFactory);
return factory;
}
public static class AutowiredSupportQuartzJobFactory extends AdaptableJobFactory implements BeanFactoryAware {
private AutowireCapableBeanFactory autowireCapableBeanFactory;
@Override
public void setBeanFactory(BeanFactory beanFactory) throws BeansException {
this.autowireCapableBeanFactory = (AutowireCapableBeanFactory) beanFactory;
}
@Override
protected Object createJobInstance(@Nonnull TriggerFiredBundle bundle) throws Exception {
Object jobInstance = super.createJobInstance(bundle);
autowireCapableBeanFactory.autowireBean(jobInstance);
return jobInstance;
}
}
}
// CommandLineRunner
@Component
public class QuartzJobStartCommandLineRunner implements CommandLineRunner {
@Autowired
private Scheduler scheduler;
@Autowired
private JedisProvider jedisProvider;
@Override
public void run(String... args) throws Exception {
long shardingCount = 2;
prepareData(shardingCount);
for (ConsumerTask task : prepareConsumerTasks(shardingCount)) {
scheduler.scheduleJob(task.getJobDetail(), task.getTrigger());
}
}
private void prepareData(long shardingCount) {
for (long i = 0L; i < shardingCount; i++) {
Map<String, Double> z = Maps.newHashMap();
Map<String, String> h = Maps.newHashMap();
for (int k = 0; k < 100; k++) {
OrderMessage message = new OrderMessage();
message.setAmount(BigDecimal.valueOf(k));
message.setUserId((long) k);
message.setOrderId("ORDER_ID_" + k);
// 30 min ago
z.put(message.getOrderId(), Double.valueOf(String.valueOf(System.currentTimeMillis() - 30 * 60 * 1000)));
h.put(message.getOrderId(), JSON.toJSONString(message));
}
Jedis jedis = jedisProvider.provide(i);
jedis.hmset("ORDER_DETAIL_QUEUE", h);
jedis.zadd("ORDER_QUEUE", z);
}
}
private List<ConsumerTask> prepareConsumerTasks(long shardingCount) {
List<ConsumerTask> tasks = Lists.newArrayList();
for (long i = 0; i < shardingCount; i++) {
JobDetail jobDetail = JobBuilder.newJob(OrderMessageConsumer.class)
.withIdentity("OrderMessageConsumer-" + i, "DelayTask")
.usingJobData("shardingIndex", i)
.build();
Trigger trigger = TriggerBuilder.newTrigger()
.withIdentity("OrderMessageConsumerTrigger-" + i, "DelayTask")
.withSchedule(SimpleScheduleBuilder.simpleSchedule().withIntervalInSeconds(10).repeatForever())
.build();
tasks.add(new ConsumerTask(jobDetail, trigger));
}
return tasks;
}
@Getter
@RequiredArgsConstructor
private static class ConsumerTask {
private final JobDetail jobDetail;
private final Trigger trigger;
}
}
新增一個啓動函數而且啓動，控制檯輸出以下：
// ...省略大量輸出
2019-09-01 14:08:27.664 INFO 13056 --- [ main] c.t.multi.NoneJdbcSpringApplication : Started NoneJdbcSpringApplication in 1.333 seconds (JVM running for 5.352)
2019-09-01 14:08:27.724 INFO 13056 --- [eduler_Worker-2] c.throwable.multi.OrderMessageConsumer : 訂單消息消費者定時任務開始執行,shardingIndex:[1]...
2019-09-01 14:08:27.724 INFO 13056 --- [eduler_Worker-1] c.throwable.multi.OrderMessageConsumer : 訂單消息消費者定時任務開始執行,shardingIndex:[0]...
2019-09-01 14:08:27.732 INFO 13056 --- [onsumerWorker-1] c.throwable.multi.OrderMessageConsumer : shardingIndex:[1],處理訂單消息,內容:{"amount":99,"orderId":"ORDER_ID_99","userId":99}
2019-09-01 14:08:27.732 INFO 13056 --- [onsumerWorker-0] c.throwable.multi.OrderMessageConsumer : shardingIndex:[0],處理訂單消息,內容:{"amount":99,"orderId":"ORDER_ID_99","userId":99}
2019-09-01 14:08:27.782 INFO 13056 --- [onsumerWorker-0] c.throwable.multi.OrderMessageConsumer : shardingIndex:[0],處理訂單消息,內容:{"amount":98,"orderId":"ORDER_ID_98","userId":98}
2019-09-01 14:08:27.782 INFO 13056 --- [onsumerWorker-1] c.throwable.multi.OrderMessageConsumer : shardingIndex:[1],處理訂單消息,內容:{"amount":98,"orderId":"ORDER_ID_98","userId":98}
// ...省略大量輸出
2019-09-01 14:08:28.239 INFO 13056 --- [eduler_Worker-2] c.throwable.multi.OrderMessageConsumer : 訂單消息消費者定時任務執行完畢,shardingIndex:[1]...
2019-09-01 14:08:28.240 INFO 13056 --- [eduler_Worker-1] c.throwable.multi.OrderMessageConsumer : 訂單消息消費者定時任務執行完畢,shardingIndex:[0]...
// ...省略大量輸出
生產中應該避免Redis服務單點，通常經常使用哨兵配合樹狀主從的部署方式（參考《Redis開發與運維》），2套Redis哨兵的部署示意圖以下：
須要什麼監控項
咱們須要相對實時地知道Redis中的延時隊列集合有多少積壓數據，每次出隊的耗時大概是多少等等監控項參數，這樣咱們才能更好地知道延時隊列模塊是否正常運行、是否存在性能瓶頸等等。具體的監控項，須要按需定製，這裏爲了方便舉例，只作兩個監控項的監控：
- 有序集合
Sorted Set中積壓的元素數量。 - 每次調用
dequeue.lua的耗時。
採用的是應用實時上報數據的方式，依賴於spring-boot-starter-actuator、Prometheus、Grafana搭建的監控體系，若是並不熟悉這個體系能夠看兩篇前置文章：
監控
引入依賴：
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
<version>1.2.0</version>
</dependency>
這裏選用Gauge的Meter進行監控數據收集，添加監控類OrderDelayQueueMonitor：。
// OrderDelayQueueMonitor
@Component
public class OrderDelayQueueMonitor implements InitializingBean {
private static final long SHARDING_COUNT = 2L;
private final ConcurrentMap<Long, AtomicLong> remain = Maps.newConcurrentMap();
private final ConcurrentMap<Long, AtomicLong> lua = Maps.newConcurrentMap();
private ScheduledExecutorService executor;
@Autowired
private JedisProvider jedisProvider;
@Override
public void afterPropertiesSet() throws Exception {
executor = Executors.newSingleThreadScheduledExecutor(r -> {
Thread thread = new Thread(r, "OrderDelayQueueMonitor");
thread.setDaemon(true);
return thread;
});
for (long i = 0L; i < SHARDING_COUNT; i++) {
AtomicLong l = new AtomicLong();
Metrics.gauge("order.delay.queue.lua.cost", Collections.singleton(Tag.of("index", String.valueOf(i))),
l, AtomicLong::get);
lua.put(i, l);
AtomicLong r = new AtomicLong();
Metrics.gauge("order.delay.queue.remain", Collections.singleton(Tag.of("index", String.valueOf(i))),
r, AtomicLong::get);
remain.put(i, r);
}
// 每五秒上報一次集合中的剩餘數據
executor.scheduleWithFixedDelay(new MonitorTask(jedisProvider), 0, 5, TimeUnit.SECONDS);
}
public void recordRemain(Long index, long count) {
remain.get(index).set(count);
}
public void recordLuaCost(Long index, long count) {
lua.get(index).set(count);
}
@RequiredArgsConstructor
private class MonitorTask implements Runnable {
private final JedisProvider jedisProvider;
@Override
public void run() {
for (long i = 0L; i < SHARDING_COUNT; i++) {
try (Jedis jedis = jedisProvider.provide(i)) {
recordRemain(i, jedis.zcount("ORDER_QUEUE", "-inf", "+inf"));
}
}
}
}
}
原來的RedisOrderDelayQueue#dequeue()進行改造：
@RequiredArgsConstructor
@Component
public class RedisOrderDelayQueue implements OrderDelayQueue, InitializingBean {
// ... 省略沒有改動的代碼
private final OrderDelayQueueMonitor orderDelayQueueMonitor;
// ... 省略沒有改動的代碼
@Override
public List<OrderMessage> dequeue(String min, String max, String offset, String limit, long index) {
List<String> args = new ArrayList<>();
args.add(min);
args.add(max);
args.add(offset);
args.add(limit);
List<OrderMessage> result = Lists.newArrayList();
List<String> keys = Lists.newArrayList();
keys.add(ORDER_QUEUE);
keys.add(ORDER_DETAIL_QUEUE);
try (Jedis jedis = jedisProvider.provide(index)) {
long start = System.nanoTime();
List<String> eval = (List<String>) jedis.evalsha(DEQUEUE_LUA_SHA.get(index), keys, args);
long end = System.nanoTime();
// 添加dequeue的耗時監控-單位微秒
orderDelayQueueMonitor.recordLuaCost(index, TimeUnit.NANOSECONDS.toMicros(end - start));
if (null != eval) {
for (String e : eval) {
result.add(JSON.parseObject(e, OrderMessage.class));
}
}
}
return result;
}
// ... 省略沒有改動的代碼
}
其餘配置這裏簡單說一下。
application.yaml要開放prometheus端點的訪問權限：
server:
port: 9091
management:
endpoints:
web:
exposure:
include: 'prometheus'
Prometheus服務配置儘可能減小查詢的間隔時間，暫定爲5秒：
# my global config
global:
scrape_interval: 5s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.
# scrape_timeout is set to the global default (10s).
# Alertmanager configuration
alerting:
alertmanagers:
- static_configs:
- targets:
# - alertmanager:9093
# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:
# - "first_rules.yml"
# - "second_rules.yml"
# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
# The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
- job_name: 'prometheus'
metrics_path: '/actuator/prometheus'
# metrics_path defaults to '/metrics'
# scheme defaults to 'http'.
static_configs:
- targets: ['localhost:9091']
Grafana的基本配置項以下：
出隊耗時 order_delay_queue_lua_cost 分片編號-{{index}}
訂單延時隊列積壓量 order_delay_queue_remain 分片編號-{{index}}
最終能夠在Grafana配置每5秒刷新，見效果以下：
這裏的監控項更多時候應該按需定製，說實話，監控的工做每每是最複雜和繁瑣的。
小結
全文相對詳細地介紹了基於Redis實現延時任務的分片和監控的具體實施過程，核心代碼僅供參考，還有一些具體的細節例如Prometheus、Grafana的一些應用，這裏限於篇幅不會詳細地展開。說實話，基於實際場景作一次中間件和架構的選型並非一件簡單的事，並且每每初期的實施並非最大的難點，更大的難題在後面的優化以及監控。
（本文完 c-3-d 20190901 身體不適，拖了一下）
原文連接
- Github Page：http://throwable.club/2019/09/01/redis-delay-task-second/
- Coding Page：http://throwable.coding.me/2019/09/01/redis-delay-task-second/
相關文章
- 1. 使用Redis實現延時任務(一)
- 2. 基於REDIS實現延時任務
- 3. springboot使用RabbitMQ實現延時任務
- 4. redis使用之延時任務
- 5. 延時任務實現
- 6. Rabbitmq 實現延時任務
- 7. 使用RabbitMQ實現延遲任務
- 8. 【延時隊列】Spring定時任務+Redis的簡單實現
- 9. 使用Redis keyspace notifications來實現延遲任務（NodeJS版）
- 10. DelayQueue實現Java延時任務
- 更多相關文章...
- • Eclipse 任務管理 - Eclipse 教程
- • 使用Redis和Lua的原子性實現搶紅包功能 - 紅包項目實戰
- • Spring Cloud 微服務實戰(三) - 服務註冊與發現
- • ☆基於Java Instrument的Agent實現
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
- 1. 升級Gradle後報錯Gradle‘s dependency cache may be corrupt (this sometimes occurs
- 2. Smarter, Not Harder
- 3. mac-2019-react-native 本地環境搭建(xcode-11.1和android studio3.5.2中Genymotion2.12.1 和VirtualBox-5.2.34 )
- 4. 查看文件中關鍵字前後幾行的內容
- 5. XXE萌新進階全攻略
- 6. Installation failed due to: ‘Connection refused: connect‘安卓studio端口占用
- 7. zabbix5.0通過agent監控winserve12
- 8. IT行業UI前景、潛力如何？
- 9. Mac Swig 3.0.12 安裝
- 10. Windows上FreeRDP-WebConnect是一個開源HTML5代理，它提供對使用RDP的任何Windows服務器和工作站的Web訪問
歡迎關注本站公眾號,獲取更多信息
