/**
 * Twitter_Snowflake<br>
 * SnowFlake的結構如下(每部分用-分開):<br>
 * 0 - 0000000000 0000000000 0000000000 0000000000 0 - 00000 - 00000 - 000000000000 <br>
 * 1位標識，由于long基本類型在Java中是帶符號的，最高位是符號位，正數(shù)是0，負數(shù)是1，所以id一般是正數(shù)，最高位是0<br>
 * 41位時間截(毫秒級)，注意，41位時間截不是存儲當前時間的時間截，而是存儲時間截的差值（當前時間截 - 開始時間截)
 * 得到的值），這里的的開始時間截，一般是我們的id生成器開始使用的時間，由我們程序來指定的（如下下面程序IdWorker類的startTime屬性）。41位的時間截，可以使用69年，年T = (1L << 41) / (1000L * 60 * 60 * 24 * 365) = 69<br>
 * 10位的數(shù)據(jù)機器位，可以部署在1024個節(jié)點，包括5位datacenterId和5位workerId<br>
 * 12位序列，毫秒內的計數(shù)，12位的計數(shù)順序號支持每個節(jié)點每毫秒(同一機器，同一時間截)產生4096個ID序號<br>
 * 加起來剛好64位，為一個Long型。<br>
 * SnowFlake的優(yōu)點是，整體上按照時間自增排序，并且整個分布式系統(tǒng)內不會產生ID碰撞(由數(shù)據(jù)中心ID和機器ID作區(qū)分)，并且效率較高，經測試，SnowFlake每秒能夠產生26萬ID左右。
 */
public class SnowflakeIdWorker {

 // ==============================Fields===========================================
 /** 開始時間截 (2015-01-01) */
 private final long twepoch = 1420041600000L;

 /** 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)
  * @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，則進行毫秒內序列
  if (lastTimestamp == timestamp) {
   sequence = (sequence + 1) & sequenceMask;
   //毫秒內序列溢出
   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();
 }

 //==============================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(Long.toBinaryString(id));
   System.out.println(id);
  }
 }
}

<dependency>
   <groupId>com.baomidou</groupId>
   <artifactId>mybatis-plus-boot-starter</artifactId>
   <version>3.1.0</version>
	</dependency>

mybatis-plus:
 #mapper-locations: classpath:mybatis/**/*Mapper.xml
 # 在classpath前添加星號可以使項目熱加載成功
 mapper-locations: classpath*:mybatis/**/*Mapper.xml
 #實體掃描，多個package用逗號或者分號分隔
 typeAliasesPackage: com.nis.project
 global-config:
 #主鍵類型 0:"數(shù)據(jù)庫ID自增", 1:"用戶輸入ID",2:"全局唯一ID (數(shù)字類型唯一ID)", 3:"全局唯一ID UUID";
 id-type: 3
 #機器 ID 部分(影響雪花ID)
 workerId: 1
 #數(shù)據(jù)標識 ID 部分(影響雪花ID)(workerId 和 datacenterId 一起配置才能重新初始化 Sequence)
 datacenterId: 18
 #字段策略 0:"忽略判斷",1:"非 NULL 判斷"),2:"非空判斷"
 field-strategy: 2
 #駝峰下劃線轉換
 db-column-underline: true
 #刷新mapper 調試神器
 refresh-mapper: true
 #數(shù)據(jù)庫大寫下劃線轉換
 #capital-mode: true
 #序列接口實現(xiàn)類配置
 #key-generator: com.baomidou.springboot.xxx
 #邏輯刪除配置（下面3個配置）
 logic-delete-value: 0
 logic-not-delete-value: 1
 #自定義SQL注入器
 #sql-injector: com.baomidou.mybatisplus.mapper.LogicSqlInjector
 #自定義填充策略接口實現(xiàn)
 #meta-object-handler: com.baomidou.springboot.xxx
 configuration:
 map-underscore-to-camel-case: true
 cache-enabled: false
 # 這個配置會將執(zhí)行的sql打印出來，在開發(fā)或測試的時候可以用
 log-impl: org.apache.ibatis.logging.stdout.StdOutImpl

public interface UserMapper extends BaseMapper<User>

@TableId
 @JsonFormat(shape = JsonFormat.Shape.STRING)
 private Long userId;

package com.nis.framework.config;

import com.baomidou.mybatisplus.extension.plugins.PaginationInterceptor;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.transaction.annotation.EnableTransactionManagement;

/**
 * Mybatis-Plus插件配置類
 *
 * @author lwj
 */
@EnableTransactionManagement
@Configuration
@MapperScan({"com.nis.project.*.mapper","com.nis.project.*.*.mapper"})
public class MybatisPlusConfig {

 /**
  * 分頁插件
  */
 @Bean
 public PaginationInterceptor paginationInterceptor() {
  return new PaginationInterceptor();
 }
}

@GetMapping("/list")
 @ResponseBody
 public Msg list(User user, HttpServletRequest request) {
  Map<String, Object> params = MapDataUtil.convertDataMap(request);
  user.getParams().putAll(params);
  Page<User> page = startMybatisPlusPage(user);
  IPage<User> userIPage = userService.selectUserList(page, user);
  return Msg.success(userIPage);
 }

@Override
 @DataScope(tableAlias = "b")
 public IPage<User> selectUserList(Page<User> page, User user) {
  return UserMapper.selectUserList(page, user);
 }

IPage<User> selectUserList(@Param("pg") Page<User> page, @Param("ps") User user);

 <select id="selectUserList" resultType="com.nis.project.system.user.domain.User" parameterType="com.nis.project.system.user.domain.User">
  select
  a.user_id,
  a.dept_id,
  a.login_name,
  a.user_name,
  a.email,
  a.phone_number,
  a.sex,
  a.avatar,
  a.status,
  a.login_ip,
  a.login_date,
  a.order_num,
  b.dept_name
  from sys_user a
  left join sys_dept b on b.dept_id = a.dept_id
  where 1=1
  <if test="ps.loginName != null and ps.loginName != ''">and a.login_name like concat('%', #{ps.loginName}, '%')</if>
  <if test="ps.userName != null and ps.userName != ''">and a.user_name like concat('%', #{ps.userName}, '%')</if>
  <if test="ps.deptId != null and ps.deptId != ''">and b.dept_id = #{ps.deptId}</if>
  <if test="ps.email != null and ps.email != ''">and a.email = #{ps.email}</if>
  <if test="ps.phoneNumber != null and ps.phoneNumber != ''">and a.phone_number like concat('%', #{ps.phoneNumber}, '%')</if>
  <if test="ps.params.deptIds != null and ps.params.deptIds != ''">and find_in_set(a.dept_id,#{ps.params.deptIds})</if>
  <if test="ps.status != null and ps.status != ''">and a.status = #{ps.status}</if>
  <!-- 數(shù)據(jù)范圍過濾 -->
  ${ps.params.dataScope}
  order by b.ancestors,a.order_num
 </select>

SELECT (1146667501642584065>>12)&0x1f as workerId,(1146667501642584065>>17)&0x1f as datacenterId;