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 '當前最大id',
  step int(20) NOT NULL COMMENT '號段的長度',
  biz_type    int(20) NOT NULL COMMENT '業(yè)務類型',
  version int(20) NOT NULL COMMENT '版本號,是一個樂觀鎖，每次都更新version，保證并發(fā)時數(shù)據(jù)的正確性',
  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
     * 符號位    時間戳[31位]  自增序號【32位】
     * @param item
     * @return
     */
    public long nextId(String item){
        // 1.生成時間戳
        LocalDateTime now = LocalDateTime.now();
        // 格林威治時間差
        long nowSecond = now.toEpochSecond(ZoneOffset.UTC);
        // 我們需要獲取的 時間戳 信息
        long timestamp = nowSecond - BEGIN_TIMESTAMP;
        // 2.生成序號 --》 從Redis中獲取
        // 當前當前的日期
        String date = now.format(DateTimeFormatter.ofPattern("yyyy:MM:dd"));
        // 獲取對應的自增的序號
        Long increment = redisTemplate.opsForValue().increment("id:" + item + ":" + date);
        return timestamp << 32 | increment;
    }
}

public class SnowflakeIdWorker {
    // ==============================Fields===========================================
    /**
     * 開始時間截 (2020-11-03，一旦確定不可更改，否則時間被回調(diào)，或者改變，可能會造成id重復或沖突)
     */
    private final long twepoch = 1604374294980L;
    /**
     * 機器id所占的位數(shù)
     */
    private final long workerIdBits = 5L;
    /**
     * 數(shù)據(jù)標識id所占的位數(shù)
     */
    private final long datacenterIdBits = 5L;
    /**
     * 支持的最大機器id，結果是31 (這個移位算法可以很快的計算出幾位二進制數(shù)所能表示的最大十進制數(shù))
     */
    private final long maxWorkerId = -1L ^ (-1L << workerIdBits);
    /**
     * 支持的最大數(shù)據(jù)標識id，結果是31
     */
    private final long maxDatacenterId = -1L ^ (-1L << datacenterIdBits);
    /**
     * 序列在id中占的位數(shù)
     */
    private final long sequenceBits = 12L;
    /**
     * 機器ID向左移12位
     */
    private final long workerIdShift = sequenceBits;
    /**
     * 數(shù)據(jù)標識id向左移17位(12+5)
     */
    private final long datacenterIdShift = sequenceBits + workerIdBits;
    /**
     * 時間截向左移22位(5+5+12)
     */
    private final long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;
    /**
     * 生成序列的掩碼，這里為4095 (0b111111111111=0xfff=4095)
     */
    private final long sequenceMask = -1L ^ (-1L << sequenceBits);
    /**
     * 工作機器ID(0~31)
     */
    private long workerId;
    /**
     * 數(shù)據(jù)中心ID(0~31)
     */
    private long datacenterId;
    /**
     * 毫秒內(nèi)序列(0~4095)
     */
    private long sequence = 0L;
    /**
     * 上次生成ID的時間截
     */
    private long lastTimestamp = -1L;
    //==============================Constructors=====================================
    /**
     * 構造函數(shù)
     *
     */
    public SnowflakeIdWorker() {
        this.workerId = 0L;
        this.datacenterId = 0L;
    }
    /**
     * 構造函數(shù)
     *
     * @param workerId     工作ID (0~31)
     * @param datacenterId 數(shù)據(jù)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==========================================
    /**
     * 獲得下一個ID (該方法是線程安全的)
     *
     * @return SnowflakeId
     */
    public synchronized long nextId() {
        long timestamp = timeGen();
        //如果當前時間小于上一次ID生成的時間戳，說明系統(tǒng)時鐘回退過這個時候應當拋出異常
        if (timestamp < lastTimestamp) {
            throw new RuntimeException(
                    String.format("Clock moved backwards.  Refusing to generate id for %d milliseconds", lastTimestamp - timestamp));
        }
        //如果是同一時間生成的，則進行毫秒內(nèi)序列
        if (lastTimestamp == timestamp) {
            sequence = (sequence + 1) & sequenceMask;
            //毫秒內(nèi)序列溢出
            if (sequence == 0) {
                //阻塞到下一個毫秒,獲得新的時間戳
                timestamp = tilNextMillis(lastTimestamp);
            }
        }
        //時間戳改變，毫秒內(nèi)序列重置
        else {
            sequence = 0L;
        }
        //上次生成ID的時間截
        lastTimestamp = timestamp;
        //移位并通過或運算拼到一起組成64位的ID
        return ((timestamp - twepoch) << timestampLeftShift) //
                | (datacenterId << datacenterIdShift) //
                | (workerId << workerIdShift) //
                | sequence;
    }
    /**
     * 阻塞到下一個毫秒，直到獲得新的時間戳
     *
     * @param lastTimestamp 上次生成ID的時間截
     * @return 當前時間戳
     */
    protected long tilNextMillis(long lastTimestamp) {
        long timestamp = timeGen();
        while (timestamp <= lastTimestamp) {
            timestamp = timeGen();
        }
        return timestamp;
    }
    /**
     * 返回以毫秒為單位的當前時間
     *
     * @return 當前時間(毫秒)
     */
    protected long timeGen() {
        return System.currentTimeMillis();
    }
    /**
     * 隨機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=========================================
    /**
     * 測試
     */
    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);
        }
    }
}