Twitter的分布式自增ID算法Snowflake
- - 企业架构 - ITeye博客Twitter-Snowflake算法产生的背景相当简单,为了满足Twitter每秒上万条消息的请求,每条消息都必须分配一条唯一的id,这些id还需要一些大致的顺序(方便客户端排序),并且在分布式系统中不同机器产生的id必须不同. Snowflake算法核心. 把 时间戳, 工作机器id, 序列号组合在一起.
SnowFlake不依赖第三方介质,不像基于ZK,Redis等,每次用完一个区间还得通过网络去获取下一个区间,效率较低,基于SnowFlake的分布式ID生成是目前我见过的最快的
SnowFlake生成的是一个64位的数字,其中42位时间戳,接下来10位是自定义的数,其作用就是区分集群中的所有机器,最后12位是毫秒内序列,集群内每个机器能够在1毫秒内生成2^12 - 1个ID
/**
* 基于SnowFlake的序列号生成实现, 64位ID (42(毫秒)+5(机器ID)+5(业务编码)+12(重复累加))
*/
static class Generator {
private final static long TWEPOCH = 1288834974657L;
// 机器标识位数
private final static long WORKER_ID_BITS = 5L;
// 数据中心标识位数
private final static long DATA_CENTER_ID_BITS = 5L;
// 机器ID最大值 31
private final static long MAX_WORKER_ID = -1L ^ (-1L << WORKER_ID_BITS);
// 数据中心ID最大值 31
private final static long MAX_DATA_CENTER_ID = -1L ^ (-1L << DATA_CENTER_ID_BITS);
// 毫秒内自增位
private final static long SEQUENCE_BITS = 12L;
// 机器ID偏左移12位
private final static long WORKER_ID_SHIFT = SEQUENCE_BITS;
private final static long DATA_CENTER_ID_SHIFT = SEQUENCE_BITS + WORKER_ID_BITS;
// 时间毫秒左移22位
private final static long TIMESTAMP_LEFT_SHIFT = SEQUENCE_BITS + WORKER_ID_BITS + DATA_CENTER_ID_BITS;
private final static long SEQUENCE_MASK = -1L ^ (-1L << SEQUENCE_BITS);
private long lastTimestamp = -1L;
private long sequence = 0L;
private final long workerId;
private final long dataCenterId;
//private final AtomicBoolean lock = new AtomicBoolean(false);
Generator(long workerId, long dataCenterId) {
if (workerId > MAX_WORKER_ID || workerId < 0) {
throw new IllegalArgumentException(String.format("%s must range from %d to %d", K_WORK_ID, 0,
MAX_WORKER_ID));
}
if (dataCenterId > MAX_DATA_CENTER_ID || dataCenterId < 0) {
throw new IllegalArgumentException(String.format("%s must range from %d to %d", K_DC_ID, 0,
MAX_DATA_CENTER_ID));
}
this.workerId = workerId;
this.dataCenterId = dataCenterId;
}
synchronized long nextValue() throws SequenceException {
long timestamp = time();
if (timestamp < lastTimestamp) {
throw new SequenceException("Clock moved backwards, refuse to generate id for "
+ (lastTimestamp - timestamp) + " milliseconds");
}
if (lastTimestamp == timestamp) {
// 当前毫秒内,则+1
sequence = (sequence + 1) & SEQUENCE_MASK;
if (sequence == 0) {
// 当前毫秒内计数满了,则等待下一秒
timestamp = tilNextMillis(lastTimestamp);
}
} else {
sequence = 0;
}
lastTimestamp = timestamp;
// ID偏移组合生成最终的ID,并返回ID
long nextId = ((timestamp - TWEPOCH) << TIMESTAMP_LEFT_SHIFT)
| (dataCenterId << DATA_CENTER_ID_SHIFT) | (workerId << WORKER_ID_SHIFT) | sequence;
return nextId;
}
private long tilNextMillis(final long lastTimestamp) {
long timestamp = this.time();
while (timestamp <= lastTimestamp) {
timestamp = this.time();
}
return timestamp;
}
private long time() {
return System.currentTimeMillis();
}
}