java画雪花_雪花算法 Java 版
雪花算法根据时间戳生成有序的 64 bit 的 Long 类型的唯一 ID
各 bit 含义：
1 bit: 符号位，0 是正数 1 是负数， ID 为正数，所以恒取 0
41 bit: 时间差，我们可以选择一个参考点，用它来计算与当前时间的时间差 (毫秒数)，41 bit 存储时间差，足够使用 69 年
10 bit: 机器码，能编码 1024 台机器；可以手动指定含义，比如前5 bit 作为机器编号、后 5 bit 作为进程编号
12 bit: 序列号，同一机器同一毫秒内产生不同的序列号，12 bit 可以支持 4096 个序列号
优点：
灵活配置：机器码可以根据需求灵活配置含义
无需持久化：如果序号自增往往需要持久化，本算法不需要持久化
ID 有含义/可逆性：ID 可以反解出来，对 ID 进行统计分析，可以很简单的分析出整个系统的繁忙曲线，还可以定位到每个机器，在某段时间承担了多少工作，分析出负载均衡情况
高性能：生成速度很快
public class Snowflake {
/**
* 每一部分所占位数
*/
private final long unusedBits = 1L;
private final long timestampBits = 41L;
private final long datacenterIdBits = 5L;
private final long workerIdBits = 5L;
private final long sequenceBits = 12L;
/**
* 向左的位移
*/
private final long timestampShift = sequenceBits + datacenterIdBits + workerIdBits;
private final long datacenterIdShift = sequenceBits + workerIdBits;
private final long workerIdShift = sequenceBits;
/**
* 起始时间戳，初始化后不可修改
*/
private final long epoch = 1451606400000L; // 2016-01-01
/**
* 数据中心编码，初始化后不可修改
* 最大值: 2^5-1 取值范围: [0,31]
*/
private final long datacenterId;
/**
* 机器或进程编码，初始化后不可修改
* 最大值: 2^5-1 取值范围: [0,31]
*/
private final long workerId;
/**
* 序列号
* 最大值: 2^12-1 取值范围: [0,4095]
*/
private long sequence = 0L;
/** 上次执行生成 ID 方法的时间戳 */
private long lastTimestamp = -1L;
/*
* 每一部分最大值
*/
private final long maxDatacenterId = -1L ^ (-1L << datacenterIdBits); // 2^5-1
private final long maxWorkerId = -1L ^ (-1L << workerIdBits); // 2^5-1
private final long maxSequence = -1L ^ (-1L << sequenceBits); // 2^12-1
/**
* 生成序列号
*/
public synchronized long nextId() {
long currTimestamp = timestampGen();
if (currTimestamp < lastTimestamp) {
throw new IllegalStateException(
String.format("Clock moved backwards. Refusing to generate id for %d milliseconds",
lastTimestamp - currTimestamp));
}
if (currTimestamp == lastTimestamp) {
sequence = (sequence + 1) & maxSequence;
if (sequence == 0) { // overflow: greater than max sequence
currTimestamp = waitNextMillis(currTimestamp);
}
} else { // reset to 0 for next period/millisecond
sequence = 0L;
}
// track and memo the time stamp last snowflake ID generated
lastTimestamp = currTimestamp;
return ((currTimestamp - epoch) << timestampShift) | //
(datacenterId << datacenterIdShift) | //
(workerId << workerIdShift) | // new line for nice looking
sequence;
}
public Snowflake(long datacenterId, long workerId) {
if (datacenterId > maxDatacenterId || datacenterId < 0) {
throw new IllegalArgumentException(
String.format("datacenter Id can't be greater than %d or less than 0", maxDatacenterId));
}
if (workerId > maxWorkerId || workerId < 0) {
throw new IllegalArgumentException(
String.format("worker Id can't be greater than %d or less than 0", maxWorkerId));
}
this.datacenterId = datacenterId;
this.workerId = workerId;
}
/**
* 追踪调用 waitNextMillis 方法的次数
*/
private final AtomicLong waitCount = new AtomicLong(0);
public long getWaitCount() {
return waitCount.get();
}
/**
* 循环阻塞直到下一秒
*/
protected long waitNextMillis(long currTimestamp) {
waitCount.incrementAndGet();
while (currTimestamp <= lastTimestamp) {
currTimestamp = timestampGen();
}
return currTimestamp;
}
/**
* 获取当前时间戳
*/
public long timestampGen() {
return System.currentTimeMillis();
}
}