java 雪花算法生成9位id

雪花算法是一种分布式唯一 ID 生成算法，可以生成唯一的、有序的、可排序的、高并发的 ID。以下是 Java 实现的 9 位雪花算法生成 ID 的示例代码：

public class SnowflakeIdGenerator {
    private static final long START_STAMP = 1577808000000L; // 2020-01-01 00:00:00
    private static final long SEQUENCE_BITS = 4L;
    private static final long WORKER_ID_BITS = 5L;
    private static final long MAX_SEQUENCE = ~(-1L << SEQUENCE_BITS);
    private static final long MAX_WORKER_ID = ~(-1L << WORKER_ID_BITS);
    private static final long WORKER_ID_SHIFT = SEQUENCE_BITS;
    private static final long TIMESTAMP_SHIFT = SEQUENCE_BITS + WORKER_ID_BITS;

    private volatile long lastTimestamp = -1L;
    private volatile long sequence = 0L;
    private final long workerId;

    public SnowflakeIdGenerator(long workerId) {
        if (workerId > MAX_WORKER_ID || workerId < 0) {
            throw new IllegalArgumentException("Worker ID must be between 0 and " + MAX_WORKER_ID);
        }
        this.workerId = workerId;
    }

    public synchronized long nextId() {
        long currentTimestamp = System.currentTimeMillis();
        if (currentTimestamp < lastTimestamp) {
            throw new RuntimeException("Clock moved backwards! Refusing to generate ID");
        }
        if (currentTimestamp == lastTimestamp) {
            sequence = (sequence + 1) & MAX_SEQUENCE;
            if (sequence == 0) {
                currentTimestamp = nextTimestamp(currentTimestamp);
            }
        } else {
            sequence = 0L;
        }
        lastTimestamp = currentTimestamp;
        return ((currentTimestamp - START_STAMP) << TIMESTAMP_SHIFT) |
                (workerId << WORKER_ID_SHIFT) |
                sequence;
    }

    private long nextTimestamp(long currentTimestamp) {
        long timestamp = System.currentTimeMillis();
        while (timestamp <= currentTimestamp) {
            timestamp = System.currentTimeMillis();
        }
        return timestamp;
    }
}

此代码中，我们使用一个 long 类型的变量来表示生成的 ID，其中，前 41 位是时间戳（毫秒级），接着的 5 位是机器 ID，最后的 4 位是序列号。根据雪花算法的规则，序列号是每毫秒内的计数器，最大值为 15，超过则等待下一毫秒再生成 ID。

使用此类生成 9 位 ID，我们可以将机器 ID 的位数减少为 4，序列号的位数减少为 1，时间戳的起点可以设为 2020-01-01 00:00:00，代码如下：

public class NineDigitsSnowflakeIdGenerator {
    private static final long START_STAMP = 1577808000000L; // 2020-01-01 00:00:00
    private static final long SEQUENCE_BITS = 1L;
    private static final long WORKER_ID_BITS = 4L;
    private static final long MAX_SEQUENCE = ~(-1L << SEQUENCE_BITS);
    private static final long MAX_WORKER_ID = ~(-1L << WORKER_ID_BITS);
    private static final long WORKER_ID_SHIFT = SEQUENCE_BITS;
    private static final long TIMESTAMP_SHIFT = SEQUENCE_BITS + WORKER_ID_BITS;

    private volatile long lastTimestamp = -1L;
    private volatile long sequence = 0L;
    private final long workerId;

    public NineDigitsSnowflakeIdGenerator(long workerId) {
        if (workerId > MAX_WORKER_ID || workerId < 0) {
            throw new IllegalArgumentException("Worker ID must be between 0 and " + MAX_WORKER_ID);
        }
        this.workerId = workerId;
    }

    public synchronized long nextId() {
        long currentTimestamp = System.currentTimeMillis();
        if (currentTimestamp < lastTimestamp) {
            throw new RuntimeException("Clock moved backwards! Refusing to generate ID");
        }
        if (currentTimestamp == lastTimestamp) {
            sequence = (sequence + 1) & MAX_SEQUENCE;
            if (sequence == 0) {
                currentTimestamp = nextTimestamp(currentTimestamp);
            }
        } else {
            sequence = 0L;
        }
        lastTimestamp = currentTimestamp;
        return ((currentTimestamp - START_STAMP) << TIMESTAMP_SHIFT) |
                (workerId << WORKER_ID_SHIFT) |
                sequence;
    }

    private long nextTimestamp(long currentTimestamp) {
        long timestamp = System.currentTimeMillis();
        while (timestamp <= currentTimestamp) {
            timestamp = System.currentTimeMillis();
        }
        return timestamp;
    }
}