java-spring基于redis单机版(redisTemplate)实现的分布式锁+redis消息队列,可用于秒杀,定时器,高并发,抢购

此教程不涉及整合spring整合redis,可另行查阅资料教程。

代码:

RedisLock

package com.cashloan.analytics.utils;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisCallback;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.StringRedisSerializer;
import org.springframework.stereotype.Component; @Component
public class RedisLock {
private static Logger logger = LoggerFactory.getLogger(RedisLock.class);
private static final int DEFAULT_ACQUIRY_RESOLUTION_MILLIS = 100;
public static final String LOCK_PREFIX = "redis_lock_"; @Autowired
private RedisTemplate<String, Object> redisTemplate; /**
* 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; public String get(final String key) {
Object obj = null;
try {
obj = redisTemplate.execute((RedisCallback<Object>) connection -> {
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;
} public boolean setNX(final String key, final String value) {
Object obj = null;
try {
obj = redisTemplate.execute((RedisCallback<Object>) connection -> {
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((RedisCallback<Object>) connection -> {
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 boolean lock(String lockKey) throws InterruptedException {
lockKey = LOCK_PREFIX + lockKey;
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)) {
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
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 void unlock(String lockKey) {
lockKey = LOCK_PREFIX + lockKey;
redisTemplate.delete(lockKey);
} }

redis消息队列:RedisQueue

package com.cashloan.analytics.utils;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Component; import java.util.List;
import java.util.concurrent.TimeUnit; /**
* redis消息队列
*/
@Component
public class RedisQueue {
@Autowired
private RedisTemplate<String, Object> redisTemplate; /** ---------------------------------- redis消息队列 ---------------------------------- */
/**
* 存值
* @param key 键
* @param value 值
* @return
*/
public boolean lpush(String key, Object value) {
try {
redisTemplate.opsForList().leftPush(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
} /**
* 取值 - <rpop:非阻塞式>
* @param key 键
* @return
*/
public Object rpop(String key) {
try {
return redisTemplate.opsForList().rightPop(key);
} catch (Exception e) {
e.printStackTrace();
return null;
}
} /**
* 取值 - <brpop:阻塞式> - 推荐使用
* @param key 键
* @param timeout 超时时间
* @param timeUnit 给定单元粒度的时间段
* TimeUnit.DAYS //天
* TimeUnit.HOURS //小时
* TimeUnit.MINUTES //分钟
* TimeUnit.SECONDS //秒
* TimeUnit.MILLISECONDS //毫秒
* @return
*/
public Object brpop(String key, long timeout, TimeUnit timeUnit) {
try {
return redisTemplate.opsForList().rightPop(key, timeout, timeUnit);
} catch (Exception e) {
e.printStackTrace();
return null;
}
} /**
* 查看值
* @param key 键
* @param start 开始
* @param end 结束 0 到 -1代表所有值
* @return
*/
public List<Object> lrange(String key, long start, long end) {
try {
return redisTemplate.opsForList().range(key, start, end);
} catch (Exception e) {
e.printStackTrace();
return null;
}
} }

测试类controller:Test

package com.cashloan.analytics.controller;

import com.cashloan.analytics.utils.RedisLock;
import com.cashloan.analytics.utils.RedisQueue;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController; import java.util.*; @RestController
@RequestMapping("/test")
public class Test {
private final static String MESSAGE = "testmq";
@Autowired
private RedisQueue redisQueue;
@Autowired
private RedisLock redisLock; @GetMapping("/add")
public String add() {
String uuid = UUID.randomUUID().toString().replaceAll("-", "");
Map map = new HashMap();
map.put("id", uuid);
// 加入redis消息队列
redisQueue.lpush(MESSAGE, map);
addBatch();
return "success";
} public void addBatch() {
try {
if (redisLock.lock(MESSAGE)) {
List<Object> lrange = redisQueue.lrange(MESSAGE, 0, -1);
int size = lrange.size();
if (size >= 10) {
List<Map> maps = new ArrayList<>();
for (int i = 0; i < size; i++) {
Object brpop = redisQueue.rpop(MESSAGE);
if (brpop != null) {
maps.add((Map) brpop);
}
}
// 记录数据
if (!maps.isEmpty()) {
for (int i = 0; i < maps.size(); i++) {
System.out.println(maps.get(i).get("id"));
Thread.sleep(100);
}
}
}
}
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
redisLock.unlock(MESSAGE);
}
} }

另有一份模拟高并发多线程请求的工具(python3):

# -*- coding: utf-8 -*-
import requests
import threading class postrequests():
def __init__(self):
self.url = 'http://localhost:9090/test/add'
def post(self):
try:
r = requests.get(self.url)
print(r.text)
except Exception as e:
print(e) def test():
test = postrequests()
return test.post()
try:
i = 0
# 开启线程数目
tasks_number = 105
print('测试启动')
while i < tasks_number:
t = threading.Thread(target=test)
t.start()
i += 1
except Exception as e:
print(e)
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