Redis分布式锁,如何应对长尾词高并发场景?

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本文共计1126个文字,预计阅读时间需要5分钟。

Redis分布式锁,如何应对长尾词高并发场景?

java从网络导入以下类:- org.slf4j.Logger- org.slf4j.LoggerFactory- org.springframework.dao.DataAccessException- org.springframework.data.redis.connection.RedisConnection- org.springframework.data.redis.core.RedisCallback

摘自网络

import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.dao.DataAccessException; import org.springframework.data.redis.connection.RedisConnection; import org.springframework.data.redis.core.RedisCallback; import org.springframework.data.redis.core.RedisTemplate; import org.springframework.data.redis.serializer.StringRedisSerializer; /** * redis 实现分布式锁 * * blog * Created with IntelliJ IDEA. * User: JiaLi on 2017/9/29 15:05 */ public class RedisLock { private static Logger logger = LoggerFactory.getLogger(RedisLock.class); private RedisTemplate redisTemplate; private static final int DEFAULT_ACQUIRY_RESOLUTION_MILLIS = 100; /** * Lock key path. */ private String lockKey; /** * 锁超时时间,防止线程在入锁以后,无限的执行等待 */ private int expireMsecs = 60 * 1000; /** * 锁等待时间,防止线程饥饿 */ private int timeoutMsecs = 10 * 1000; private volatile boolean locked = false; /** * Detailed constructor with default acquire timeout 10000 msecs and lock expiration of 60000 * msecs. * * @param lockKey lock key (ex. account:1, ...) */ public RedisLock(RedisTemplate redisTemplate, String lockKey) { this.redisTemplate = redisTemplate; this.lockKey = lockKey + "_lock"; } /** * Detailed constructor with default lock expiration of 60000 msecs. */ public RedisLock(RedisTemplate redisTemplate, String lockKey, int timeoutMsecs) { this(redisTemplate, lockKey); this.timeoutMsecs = timeoutMsecs; } /** * Detailed constructor. */ public RedisLock(RedisTemplate redisTemplate, String lockKey, int timeoutMsecs, int expireMsecs) { this(redisTemplate, lockKey, timeoutMsecs); this.expireMsecs = expireMsecs; } /** * @return lock key */ public String getLockKey() { return lockKey; } private String get(final String key) { Object obj = null; try { obj = redisTemplate.execute(new RedisCallback() { @Override public Object doInRedis(RedisConnection connection) throws DataAccessException { StringRedisSerializer serializer = new StringRedisSerializer(); byte[] data = connection.get(serializer.serialize(key)); connection.close(); if (data == null) { return null; } return serializer.deserialize(data); } }); } catch (Exception e) { logger.error("get redis error, key : {}", key); } return obj != null ? obj.toString() : null; } private boolean setNX(final String key, final String value) { Object obj = null; try { obj = redisTemplate.execute(new RedisCallback() { @Override public Object doInRedis(RedisConnection connection) throws DataAccessException { StringRedisSerializer serializer = new StringRedisSerializer(); Boolean success = connection .setNX(serializer.serialize(key), serializer.serialize(value)); connection.close(); return success; } }); } catch (Exception e) { logger.error("setNX redis error, key : {}", key); } return obj != null ? (Boolean) obj : false; } private String getSet(final String key, final String value) { Object obj = null; try { obj = redisTemplate.execute(new RedisCallback() { @Override public Object doInRedis(RedisConnection connection) throws DataAccessException { StringRedisSerializer serializer = new StringRedisSerializer(); byte[] ret = connection .getSet(serializer.serialize(key), serializer.serialize(value)); connection.close(); return serializer.deserialize(ret); } }); } catch (Exception e) { logger.error("setNX redis error, key : {}", key); } return obj != null ? (String) obj : null; } /** * 获得 lock. * 实现思路: 主要是使用了redis 的setnx命令,缓存了锁. * reids缓存的key是锁的key,所有的共享, value是锁的到期时间(注意:这里把过期时间放在value了,没有时间上设置其超时时间) * 执行过程: * 1.通过setnx尝试设置某个key的值,成功(当前没有这个锁)则返回,成功获得锁 * 2.锁已经存在则获取锁的到期时间,和当前时间比较,超时的话,则设置新的值 * * @return true if lock is acquired, false acquire timeouted * @throws InterruptedException in case of thread interruption */ public synchronized boolean lock() throws InterruptedException { int timeout = timeoutMsecs; while (timeout >= 0) { long expires = System.currentTimeMillis() + expireMsecs + 1; String expiresStr = String.valueOf(expires); //锁到期时间 if (this.setNX(lockKey, expiresStr)) { // lock acquired locked = true; return true; } String currentValueStr = this.get(lockKey); //redis里的时间 if (currentValueStr != null && Long.parseLong(currentValueStr) < System .currentTimeMillis()) { //判断是否为空,不为空的情况下,如果被其他线程设置了值,则第二个条件判断是过不去的 // lock is expired String oldValueStr = this.getSet(lockKey, expiresStr); //获取上一个锁到期时间,并设置现在的锁到期时间, //只有一个线程才能获取上一个线上的设置时间,因为jedis.getSet是同步的 if (oldValueStr != null && oldValueStr.equals(currentValueStr)) { //防止误删(覆盖,因为key是相同的)了他人的锁——这里达不到效果,这里值会被覆盖,但是因为什么相差了很少的时间,所以可以接受 //[分布式的情况下]:如过这个时候,多个线程恰好都到了这里,但是只有一个线程的设置值和当前值相同,他才有权利获取锁 // lock acquired locked = true; return true; } } timeout -= DEFAULT_ACQUIRY_RESOLUTION_MILLIS; /* 延迟100 毫秒, 这里使用随机时间可能会好一点,可以防止饥饿进程的出现,即,当同时到达多个进程, 只会有一个进程获得锁,其他的都用同样的频率进行尝试,后面有来了一些进行,也以同样的频率申请锁,这将可能导致前面来的锁得不到满足. 使用随机的等待时间可以一定程度上保证公平性 */ Thread.sleep(DEFAULT_ACQUIRY_RESOLUTION_MILLIS); } return false; } /** * Acqurired lock release. */ public synchronized void unlock() { if (locked) { redisTemplate.delete(lockKey); locked = false; } } public static void main(String[] args) { RedisTemplate redisTemplate = new RedisTemplate(); String key = "lock-key"; RedisLock lock = new RedisLock(redisTemplate, key, 10000, 20000); try { if (lock.lock()) { //需要加锁的代码 } } catch (InterruptedException e) { e.printStackTrace(); } finally { //为了让分布式锁的算法更稳键些,持有锁的客户端在解锁之前应该再检查一次自己的锁是否已经超时,再去做DEL操作,因为可能客户端因为某个耗时的操作而挂起, //操作完的时候锁因为超时已经被别人获得,这时就不必解锁了。 ————这里没有做 lock.unlock(); } } }

Redis分布式锁,如何应对长尾词高并发场景?

本文共计1126个文字,预计阅读时间需要5分钟。

Redis分布式锁,如何应对长尾词高并发场景?

java从网络导入以下类:- org.slf4j.Logger- org.slf4j.LoggerFactory- org.springframework.dao.DataAccessException- org.springframework.data.redis.connection.RedisConnection- org.springframework.data.redis.core.RedisCallback

摘自网络

import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.dao.DataAccessException; import org.springframework.data.redis.connection.RedisConnection; import org.springframework.data.redis.core.RedisCallback; import org.springframework.data.redis.core.RedisTemplate; import org.springframework.data.redis.serializer.StringRedisSerializer; /** * redis 实现分布式锁 * * blog * Created with IntelliJ IDEA. * User: JiaLi on 2017/9/29 15:05 */ public class RedisLock { private static Logger logger = LoggerFactory.getLogger(RedisLock.class); private RedisTemplate redisTemplate; private static final int DEFAULT_ACQUIRY_RESOLUTION_MILLIS = 100; /** * Lock key path. */ private String lockKey; /** * 锁超时时间,防止线程在入锁以后,无限的执行等待 */ private int expireMsecs = 60 * 1000; /** * 锁等待时间,防止线程饥饿 */ private int timeoutMsecs = 10 * 1000; private volatile boolean locked = false; /** * Detailed constructor with default acquire timeout 10000 msecs and lock expiration of 60000 * msecs. * * @param lockKey lock key (ex. account:1, ...) */ public RedisLock(RedisTemplate redisTemplate, String lockKey) { this.redisTemplate = redisTemplate; this.lockKey = lockKey + "_lock"; } /** * Detailed constructor with default lock expiration of 60000 msecs. */ public RedisLock(RedisTemplate redisTemplate, String lockKey, int timeoutMsecs) { this(redisTemplate, lockKey); this.timeoutMsecs = timeoutMsecs; } /** * Detailed constructor. */ public RedisLock(RedisTemplate redisTemplate, String lockKey, int timeoutMsecs, int expireMsecs) { this(redisTemplate, lockKey, timeoutMsecs); this.expireMsecs = expireMsecs; } /** * @return lock key */ public String getLockKey() { return lockKey; } private String get(final String key) { Object obj = null; try { obj = redisTemplate.execute(new RedisCallback() { @Override public Object doInRedis(RedisConnection connection) throws DataAccessException { StringRedisSerializer serializer = new StringRedisSerializer(); byte[] data = connection.get(serializer.serialize(key)); connection.close(); if (data == null) { return null; } return serializer.deserialize(data); } }); } catch (Exception e) { logger.error("get redis error, key : {}", key); } return obj != null ? obj.toString() : null; } private boolean setNX(final String key, final String value) { Object obj = null; try { obj = redisTemplate.execute(new RedisCallback() { @Override public Object doInRedis(RedisConnection connection) throws DataAccessException { StringRedisSerializer serializer = new StringRedisSerializer(); Boolean success = connection .setNX(serializer.serialize(key), serializer.serialize(value)); connection.close(); return success; } }); } catch (Exception e) { logger.error("setNX redis error, key : {}", key); } return obj != null ? (Boolean) obj : false; } private String getSet(final String key, final String value) { Object obj = null; try { obj = redisTemplate.execute(new RedisCallback() { @Override public Object doInRedis(RedisConnection connection) throws DataAccessException { StringRedisSerializer serializer = new StringRedisSerializer(); byte[] ret = connection .getSet(serializer.serialize(key), serializer.serialize(value)); connection.close(); return serializer.deserialize(ret); } }); } catch (Exception e) { logger.error("setNX redis error, key : {}", key); } return obj != null ? (String) obj : null; } /** * 获得 lock. * 实现思路: 主要是使用了redis 的setnx命令,缓存了锁. * reids缓存的key是锁的key,所有的共享, value是锁的到期时间(注意:这里把过期时间放在value了,没有时间上设置其超时时间) * 执行过程: * 1.通过setnx尝试设置某个key的值,成功(当前没有这个锁)则返回,成功获得锁 * 2.锁已经存在则获取锁的到期时间,和当前时间比较,超时的话,则设置新的值 * * @return true if lock is acquired, false acquire timeouted * @throws InterruptedException in case of thread interruption */ public synchronized boolean lock() throws InterruptedException { int timeout = timeoutMsecs; while (timeout >= 0) { long expires = System.currentTimeMillis() + expireMsecs + 1; String expiresStr = String.valueOf(expires); //锁到期时间 if (this.setNX(lockKey, expiresStr)) { // lock acquired locked = true; return true; } String currentValueStr = this.get(lockKey); //redis里的时间 if (currentValueStr != null && Long.parseLong(currentValueStr) < System .currentTimeMillis()) { //判断是否为空,不为空的情况下,如果被其他线程设置了值,则第二个条件判断是过不去的 // lock is expired String oldValueStr = this.getSet(lockKey, expiresStr); //获取上一个锁到期时间,并设置现在的锁到期时间, //只有一个线程才能获取上一个线上的设置时间,因为jedis.getSet是同步的 if (oldValueStr != null && oldValueStr.equals(currentValueStr)) { //防止误删(覆盖,因为key是相同的)了他人的锁——这里达不到效果,这里值会被覆盖,但是因为什么相差了很少的时间,所以可以接受 //[分布式的情况下]:如过这个时候,多个线程恰好都到了这里,但是只有一个线程的设置值和当前值相同,他才有权利获取锁 // lock acquired locked = true; return true; } } timeout -= DEFAULT_ACQUIRY_RESOLUTION_MILLIS; /* 延迟100 毫秒, 这里使用随机时间可能会好一点,可以防止饥饿进程的出现,即,当同时到达多个进程, 只会有一个进程获得锁,其他的都用同样的频率进行尝试,后面有来了一些进行,也以同样的频率申请锁,这将可能导致前面来的锁得不到满足. 使用随机的等待时间可以一定程度上保证公平性 */ Thread.sleep(DEFAULT_ACQUIRY_RESOLUTION_MILLIS); } return false; } /** * Acqurired lock release. */ public synchronized void unlock() { if (locked) { redisTemplate.delete(lockKey); locked = false; } } public static void main(String[] args) { RedisTemplate redisTemplate = new RedisTemplate(); String key = "lock-key"; RedisLock lock = new RedisLock(redisTemplate, key, 10000, 20000); try { if (lock.lock()) { //需要加锁的代码 } } catch (InterruptedException e) { e.printStackTrace(); } finally { //为了让分布式锁的算法更稳键些,持有锁的客户端在解锁之前应该再检查一次自己的锁是否已经超时,再去做DEL操作,因为可能客户端因为某个耗时的操作而挂起, //操作完的时候锁因为超时已经被别人获得,这时就不必解锁了。 ————这里没有做 lock.unlock(); } } }

Redis分布式锁,如何应对长尾词高并发场景?