java九种分布式ID解决方案

import java.util.UUID;
public class Test {
    public static void main(String[] args) {
        System.out.println(UUID.randomUUID());
    }
}

CREATE TABLE `unique_id`  (
  `id` bigint NOT NULL AUTO_INCREMENT,
  `biz` char(1) NOT NULL,
  PRIMARY KEY (`id`),
	UNIQUE KEY `biz` (`biz`)
) ENGINE = InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET =utf8;

BEGIN;
REPLACE INTO unique_id (biz) values ('o') ;
SELECT LAST_INSERT_ID();
COMMIT;

show variables like '%increment%'

CREATE TABLE id_generator (
  id int(10) NOT NULL,
  max_id bigint(20) NOT NULL COMMENT '当前最大id',
  step int(20) NOT NULL COMMENT '号段的长度',
  biz_type    int(20) NOT NULL COMMENT '业务类型',
  version int(20) NOT NULL COMMENT '版本号,是一个乐观锁，每次都更新version，保证并发时数据的正确性',
  PRIMARY KEY (`id`)
) 

/**
 *  Redis 分布式ID生成器
 */
@Component
public class RedisDistributedId {
    @Autowired
    private StringRedisTemplate redisTemplate;
    private static final long BEGIN_TIMESTAMP = 1659312000l;
    /**
     * 生成分布式ID
     * 符号位    时间戳[31位]  自增序号【32位】
     * @param item
     * @return
     */
    public long nextId(String item){
        // 1.生成时间戳
        LocalDateTime now = LocalDateTime.now();
        // 格林威治时间差
        long nowSecond = now.toEpochSecond(ZoneOffset.UTC);
        // 我们需要获取的 时间戳 信息
        long timestamp = nowSecond - BEGIN_TIMESTAMP;
        // 2.生成序号 --》 从Redis中获取
        // 当前当前的日期
        String date = now.format(DateTimeFormatter.ofPattern("yyyy:MM:dd"));
        // 获取对应的自增的序号
        Long increment = redisTemplate.opsForValue().increment("id:" + item + ":" + date);
        return timestamp << 32 | increment;
    }
}

public class SnowflakeIdWorker {
    // ==============================Fields===========================================
    /**
     * 开始时间截 (2020-11-03，一旦确定不可更改，否则时间被回调，或者改变，可能会造成id重复或冲突)
     */
    private final long twepoch = 1604374294980L;
    /**
     * 机器id所占的位数
     */
    private final long workerIdBits = 5L;
    /**
     * 数据标识id所占的位数
     */
    private final long datacenterIdBits = 5L;
    /**
     * 支持的最大机器id，结果是31 (这个移位算法可以很快的计算出几位二进制数所能表示的最大十进制数)
     */
    private final long maxWorkerId = -1L ^ (-1L << workerIdBits);
    /**
     * 支持的最大数据标识id，结果是31
     */
    private final long maxDatacenterId = -1L ^ (-1L << datacenterIdBits);
    /**
     * 序列在id中占的位数
     */
    private final long sequenceBits = 12L;
    /**
     * 机器ID向左移12位
     */
    private final long workerIdShift = sequenceBits;
    /**
     * 数据标识id向左移17位(12+5)
     */
    private final long datacenterIdShift = sequenceBits + workerIdBits;
    /**
     * 时间截向左移22位(5+5+12)
     */
    private final long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;
    /**
     * 生成序列的掩码，这里为4095 (0b111111111111=0xfff=4095)
     */
    private final long sequenceMask = -1L ^ (-1L << sequenceBits);
    /**
     * 工作机器ID(0~31)
     */
    private long workerId;
    /**
     * 数据中心ID(0~31)
     */
    private long datacenterId;
    /**
     * 毫秒内序列(0~4095)
     */
    private long sequence = 0L;
    /**
     * 上次生成ID的时间截
     */
    private long lastTimestamp = -1L;
    //==============================Constructors=====================================
    /**
     * 构造函数
     *
     */
    public SnowflakeIdWorker() {
        this.workerId = 0L;
        this.datacenterId = 0L;
    }
    /**
     * 构造函数
     *
     * @param workerId     工作ID (0~31)
     * @param datacenterId 数据中心ID (0~31)
     */
    public SnowflakeIdWorker(long workerId, long datacenterId) {
        if (workerId > maxWorkerId || workerId < 0) {
            throw new IllegalArgumentException(String.format("worker Id can't be greater than %d or less than 0", maxWorkerId));
        }
        if (datacenterId > maxDatacenterId || datacenterId < 0) {
            throw new IllegalArgumentException(String.format("datacenter Id can't be greater than %d or less than 0", maxDatacenterId));
        }
        this.workerId = workerId;
        this.datacenterId = datacenterId;
    }
    // ==============================Methods==========================================
    /**
     * 获得下一个ID (该方法是线程安全的)
     *
     * @return SnowflakeId
     */
    public synchronized long nextId() {
        long timestamp = timeGen();
        //如果当前时间小于上一次ID生成的时间戳，说明系统时钟回退过这个时候应当抛出异常
        if (timestamp < lastTimestamp) {
            throw new RuntimeException(
                    String.format("Clock moved backwards.  Refusing to generate id for %d milliseconds", lastTimestamp - timestamp));
        }
        //如果是同一时间生成的，则进行毫秒内序列
        if (lastTimestamp == timestamp) {
            sequence = (sequence + 1) & sequenceMask;
            //毫秒内序列溢出
            if (sequence == 0) {
                //阻塞到下一个毫秒,获得新的时间戳
                timestamp = tilNextMillis(lastTimestamp);
            }
        }
        //时间戳改变，毫秒内序列重置
        else {
            sequence = 0L;
        }
        //上次生成ID的时间截
        lastTimestamp = timestamp;
        //移位并通过或运算拼到一起组成64位的ID
        return ((timestamp - twepoch) << timestampLeftShift) //
                | (datacenterId << datacenterIdShift) //
                | (workerId << workerIdShift) //
                | sequence;
    }
    /**
     * 阻塞到下一个毫秒，直到获得新的时间戳
     *
     * @param lastTimestamp 上次生成ID的时间截
     * @return 当前时间戳
     */
    protected long tilNextMillis(long lastTimestamp) {
        long timestamp = timeGen();
        while (timestamp <= lastTimestamp) {
            timestamp = timeGen();
        }
        return timestamp;
    }
    /**
     * 返回以毫秒为单位的当前时间
     *
     * @return 当前时间(毫秒)
     */
    protected long timeGen() {
        return System.currentTimeMillis();
    }
    /**
     * 随机id生成，使用雪花算法
     *
     * @return
     */
    public static String getSnowId() {
        SnowflakeIdWorker sf = new SnowflakeIdWorker();
        String id = String.valueOf(sf.nextId());
        return id;
    }
    //=========================================Test=========================================
    /**
     * 测试
     */
    public static void main(String[] args) {
        SnowflakeIdWorker idWorker = new SnowflakeIdWorker(0, 0);
        for (int i = 0; i < 1000; i++) {
            long id = idWorker.nextId();
            System.out.println(id);
        }
    }
}