一、什么是Snowflake ID
Snowflake ID是Twitter开源的基于时间戳生成唯一ID的算法,它通过将一个64位的长整型分为四部分,每部分分别表示不同信息组成,从而保证了生成的ID的唯一性。
这四个部分依次是:1位符号位(始终为0),41位时间戳(精确到毫秒),10位工作机器ID和12位序列号。
具体而言,每一个Snowflake ID是由以下四个部分组成的:
- 1位符号位(始终为0)
- 41位时间戳(精确到毫秒)
- 10位工作机器ID(可指定多台机器采用不同ID)
- 12位序列号(防止同一毫秒内生成的ID重复)
在实际应用中,程序员可以根据需要对时间戳、工作机器ID和序列号进行自定义。
二、Snowflake Id Worker
Snowflake Id Worker是一个类,用于生成和解析Snowflake ID。
public class SnowflakeIdWorker { private final long workerId; private final long epoch = 1288834974657L; private final long workerIdBits = 5L; private final long maxWorkerId = -1L ^ (-1L << workerIdBits); private final long sequenceBits = 12L; private final long workerIdShift = sequenceBits; private final long timestampLeftShift = sequenceBits + workerIdBits; private final long sequenceMask = -1L ^ (-1L << sequenceBits); private long lastTimestamp = -1L; private long sequence = 0L; public SnowflakeIdWorker(long workerId) { if (workerId > maxWorkerId || workerId < 0) { throw new IllegalArgumentException(String.format("worker Id can't be greater than %d or less than 0", maxWorkerId)); } this.workerId = workerId; } public synchronized long nextId() { long timestamp = System.currentTimeMillis(); if (timestamp < lastTimestamp) { throw new RuntimeException(String.format("Clock moved backwards. Refusing to generate id for %d milliseconds", lastTimestamp - timestamp)); } if (lastTimestamp == timestamp) { sequence = (sequence + 1) & sequenceMask; if (sequence == 0) { timestamp = tilNextMillis(lastTimestamp); } } else { sequence = 0L; } lastTimestamp = timestamp; return ((timestamp - epoch) << timestampLeftShift) | (workerId << workerIdShift) | sequence; } private long tilNextMillis(long lastTimestamp) { long timestamp = System.currentTimeMillis(); while (timestamp <= lastTimestamp) { timestamp = System.currentTimeMillis(); } return timestamp; } }
上述代码中,workerId代表工作机器ID,只需要设置一次;lastTimestamp和sequence分别记录上一次生成ID的时间戳和序列号;epoch代表起始时间(默认为Thu, 04 Nov 2010 01:42:54 GMT)。
三、Snowflake Id Factory
Snowflake Id Factory是一个基于Snowflake ID生成器的工厂类,主要用于创建和管理Snowflake ID生成器。
public class SnowflakeIdFactory { private final MapworkerMap = new ConcurrentHashMap<>(); public SnowflakeIdWorker getSnowflakeIdWorker(long workerId) { return workerMap.computeIfAbsent(workerId, id -> new SnowflakeIdWorker(id)); } }
上面的代码中,workerMap是一个ConcurrentHashMap,用于存储WorkerId和SnowflakeIdWorker之间的映射关系;getSnowflakeIdWorker方法则用于创建并返回相应的SnowflakeIdWorker对象。
四、Snowflake Id Generator
Snowflake Id Generator是使用Snowflake ID的工具类,用于生成唯一的ID。
public class SnowflakeIdGenerator { private static final SnowflakeIdFactory FACTORY = new SnowflakeIdFactory(); public static long nextId(long workerId) { SnowflakeIdWorker worker = FACTORY.getSnowflakeIdWorker(workerId); return worker.nextId(); } }
在上述代码中,nextId方法接受一个workerId参数,并使用SnowflakeIdWorker生成唯一的ID。
五、Snowflake Id在分布式系统中的应用
在分布式系统中,为了保证在不同的节点上生成唯一的ID,需要对Snowflake ID算法进行调整。通常的做法是,使用ZooKeeper来分配不同的workerId,并使用Redis或其他共享存储来记录各个worker的生成序列号。
下面是一个基于Redis的Snowflake生成器示例:
public class RedisSnowflakeIdWorker { private final long workerId; private final SnowflakeIdFactory idFactory; private final JedisPool jedisPool; private final String redisKey = "snowflake:id"; private volatile long sequence = 0L; public RedisSnowflakeIdWorker(long workerId, JedisPool jedisPool) { this.workerId = workerId; this.idFactory = new SnowflakeIdFactory(); this.jedisPool = jedisPool; init(); } private void init() { try (Jedis jedis = jedisPool.getResource()) { if (!jedis.exists(redisKey)) { jedis.set(redisKey, "1"); } sequence = Long.parseLong(jedis.get(redisKey)); } } public synchronized long nextId() { long timestamp = System.currentTimeMillis(); if (sequence >= (1 << 12)) { try (Jedis jedis = jedisPool.getResource()) { long current = Long.parseLong(jedis.get(redisKey)); if (current > sequence) { sequence = current; } else { jedis.incr(redisKey); sequence = Long.parseLong(jedis.get(redisKey)); } } } SnowflakeIdWorker worker = idFactory.getSnowflakeIdWorker(workerId); return worker.nextId() + sequence; } }
在上述代码中,RedisSnowflakeIdWorker继承了SnowflakeIdWorker类,通过Redis来维护sequence序列号,实现了分布式环境下的唯一ID生成器。