一、公共状态类封装
先想一下抢购逻辑，点击购买按钮后，通过post请求将数据传递给接口，接口返回成功或失败信息。因此我们需要先封装一个类描述返回信息，在response文件夹下新建BaseResponse，包含一个状态码，成功失败信息以及数据
package com.sdxb.secondkill.response; import com.sdxb.secondkill.enums.StatusCode; public class BaseResponse<T> { private Integer code; private String msg; private T data; public BaseResponse(Integer code, String msg, T data) { this.code = code; this.msg = msg; this.data = data; } public BaseResponse(StatusCode code) { this.code = code.getCode(); this.msg = code.getMsg(); } public BaseResponse(Integer code, String msg) { this.code=code; this.msg=msg; } public Integer getCode() { return code; } public void setCode(Integer code) { this.code = code; } public String getMsg() { return msg; } public void setMsg(String msg) { this.msg = msg; } public T getData() { return data; } public void setData(T data) { this.data = data; } @Override public String toString() { return "BaseResponse{" + "code=" + code + ", msg='" + msg + '\'' + ", data=" + data + '}'; } }
BaseResponse中的状态码和成功失败信息我们通过枚举类来总结，在enums中新建一个StatusCode
package com.sdxb.secondkill.enums; public enum StatusCode { //表示成功 Success(0,"成功"), //表示失败 Fail(-1,"失败"), //表示参数非法 InvalidParam(201,"非法的参数"), //表示用户未登录 UserNotLog(202,"用户未登录"), ; private Integer code; private String msg; StatusCode(Integer code,String msg){ this.code=code; this.msg=msg; } public Integer getCode() { return code; } public void setCode(Integer code) { this.code = code; } public String getMsg() { return msg; } public void setMsg(String msg) { this.msg = msg; } }
接下来就可以通过BaseResponse来返回接口的成功或失败信息。
再写一个枚举类用于记录订单支付的状态，在enums下新建SysConstant
public class SysConstant { public enum OrderStatus{ //订单无效 Invalid(-1,"无效"), //订单成功未付款 SuccessNotPayed(0,"成功-未付款"), //订单已付款 HasPayed(1,"已付款"), //订单已取消 Cancel(2,"已取消"), ; private Integer code; private String msg; OrderStatus(Integer code, String msg) { this.code = code; this.msg = msg; } public Integer getCode() { return code; } public void setCode(Integer code) { this.code = code; } public String getMsg() { return msg; } public void setMsg(String msg) { this.msg = msg; } } }
二、抢购业务逻辑编写
高并发环境下需要快速生成唯一且递增的订单编号，这个ID需要全局唯一，为了防止ID冲突可以使用36位的UUID，但是UUID有以下缺点：
这里就可以用雪花算法来解决订单编号的问题：雪花算法是推特开源的分布式id生成算法，雪花算法的具体原理我们不做介绍，只要知道它可以在硬件级别上快速生成递增id就可以了，直接放代码：
package com.sdxb.secondkill.utils; public class SnowFlake { /** * 起始的时间戳 */ private final static long START_STAMP = 1480166465631L; /** * 每一部分占用的位数 */ private final static long SEQUENCE_BIT = 12; //序列号占用的位数 private final static long MACHINE_BIT = 5; //机器标识占用的位数 private final static long DATA_CENTER_BIT = 5;//数据中心占用的位数 /** * 每一部分的最大值 */ private final static long MAX_DATA_CENTER_NUM = -1L ^ (-1L << DATA_CENTER_BIT); private final static long MAX_MACHINE_NUM = -1L ^ (-1L << MACHINE_BIT); private final static long MAX_SEQUENCE = -1L ^ (-1L << SEQUENCE_BIT); /** * 每一部分向左的位移 */ private final static long MACHINE_LEFT = SEQUENCE_BIT; private final static long DATA_CENTER_LEFT = SEQUENCE_BIT + MACHINE_BIT; private final static long TIMESTAMP_LEFT = DATA_CENTER_LEFT + DATA_CENTER_BIT; private long dataCenterId; //数据中心 private long machineId; //机器标识 private long sequence = 0L; //序列号 private long lastStamp = -1L;//上一次时间戳 public SnowFlake(long dataCenterId, long machineId) { if (dataCenterId > MAX_DATA_CENTER_NUM || dataCenterId < 0) { throw new IllegalArgumentException("dataCenterId can't be greater than MAX_DATA_CENTER_NUM or less than 0"); } if (machineId > MAX_MACHINE_NUM || machineId < 0) { throw new IllegalArgumentException("machineId can't be greater than MAX_MACHINE_NUM or less than 0"); } this.dataCenterId = dataCenterId; this.machineId = machineId; } /** * 产生下一个ID * * @return */ public synchronized long nextId() { long currStamp = getNewStamp(); if (currStamp < lastStamp) { throw new RuntimeException("Clock moved backwards. Refusing to generate id"); } if (currStamp == lastStamp) { //相同毫秒内，序列号自增 sequence = (sequence + 1) & MAX_SEQUENCE; //同一毫秒的序列数已经达到最大 if (sequence == 0L) { currStamp = getNextMill(); } } else { //不同毫秒内，序列号置为0 sequence = 0L; } lastStamp = currStamp; return (currStamp - START_STAMP) << TIMESTAMP_LEFT //时间戳部分 | dataCenterId << DATA_CENTER_LEFT //数据中心部分 | machineId << MACHINE_LEFT //机器标识部分 | sequence; //序列号部分 } private long getNextMill() { long mill = getNewStamp(); while (mill <= lastStamp) { mill = getNewStamp(); } return mill; } private long getNewStamp() { return System.currentTimeMillis(); } public static void main(String[] args) { SnowFlake snowFlake = new SnowFlake(2, 3); long start = System.currentTimeMillis(); for (int i = 0; i < 1000000; i++) { System.out.println("当前生成的有序数字串："+snowFlake.nextId()); } System.out.println("总共耗时："+(System.currentTimeMillis() - start)); } }
我在类中写了一个main方法测试生成100万个id的速度，生成100万个id一共花费4.4秒
三、抢购处理逻辑编写
抢购逻辑中需要编写两项DTO类，KillDto中保存订单id和用户id，抢购时就通过这两个数据来发起抢购，dto下新建KillDto：
@Data @ToString public class KillDto implements Serializable { private Integer killid; private Integer userid; public KillDto() { } public KillDto(Integer killid, Integer userid) { this.killid = killid; this.userid = userid; } }
在Controller文件下新建一个KillController，用来接受抢购请求
package com.sdxb.secondkill.controller; import com.sdxb.secondkill.enums.StatusCode; import com.sdxb.secondkill.response.BaseResponse; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.http.MediaType; import org.springframework.stereotype.Controller; import org.springframework.validation.BindingResult; import org.springframework.validation.annotation.Validated; import org.springframework.web.bind.annotation.RequestBody; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RequestMethod; import org.springframework.web.bind.annotation.ResponseBody; import javax.servlet.http.HttpSession; @Controller public class KillController { private static final String prefix="kill"; @Autowired private KillService killService; @RequestMapping(value = prefix+"/execute",method = RequestMethod.POST,consumes = MediaType.APPLICATION_JSON_UTF8_VALUE) @ResponseBody public BaseResponse execute(@RequestBody @Validated KillDto killDto, BindingResult result, HttpSession httpSession){ if (result.hasErrors()||killDto.getKillid()<0){ return new BaseResponse(StatusCode.InvalidParam); } //未创建登陆模块前先默认为10 Integer userid=10; try { Boolean res=killService.KillItem(killDto.getKillid(),userid); if (!res){ return new BaseResponse(StatusCode.Fail.getCode(),"商品已经抢购完或您已抢购过该商品"); } } catch (Exception e) { e.printStackTrace(); } BaseResponse baseResponse=new BaseResponse(StatusCode.Success); return baseResponse; } @RequestMapping(value = prefix+"/execute/success",method = RequestMethod.GET) public String killsuccess(){ return "killsuccess"; } @RequestMapping(value = prefix+"/execute/fail",method = RequestMethod.GET) public String killfail(){ return "killfail"; } }
所有的业务处理都放到Service中去处理，在Service文件下创建KillService接口
public interface KillService { Boolean KillItem(Integer killId,Integer userId) throws Exception; }
在Service下的Impl文件夹中创建KillServiceImpl类，用于处理详细的业务：
@Service public class KillServiceImpl implements KillService { private SnowFlake snowFlake=new SnowFlake(2,3); @Autowired private ItemKillMapper itemKillMapper; @Autowired private ItemKillSuccessMapper itemKillSuccessMapper; public Boolean KillItem(Integer killId, Integer userId) throws Exception { Boolean result=false; //判断当前用户是否抢购过该商品 if (itemKillSuccessMapper.countByKillUserId(killId,userId)<=0){ //获取商品详情 ItemKill itemKill=itemKillMapper.selectByid(killId); if (itemKill!=null&&itemKill.getCanKill()==1){ int res=itemKillMapper.updateKillItem(killId); if (res>0){ commonRecordKillSuccessInfo(itemKill,userId); result=true; } } }else { System.out.println("您已经抢购过该商品"); } return result; } private void commonRecordKillSuccessInfo(ItemKill itemKill, Integer userId) { ItemKillSuccess entity=new ItemKillSuccess(); String orderNo=String.valueOf(snowFlake.nextId()); entity.setCode(orderNo); entity.setItemId(itemKill.getItemId()); entity.setKillId(itemKill.getId()); entity.setUserId(userId.toString()); entity.setStatus(SysConstant.OrderStatus.SuccessNotPayed.getCode().byteValue()); entity.setCreateTime(DateTime.now().toDate()); if (itemKillSuccessMapper.countByKillUserId(itemKill.getId(),userId) <= 0){ int res=itemKillSuccessMapper.insertSelective(entity); if(res>0){ //处理抢购成功后的流程 //这里的业务可以自己加 } } }
对于订单抢购的数据库操作在ItemKillSuccessMapper 中进行，在mapper文件下编写ItemKillSuccessMapper :主要的操作有根据用户ID查询订单以及订单抢购成功后插入item_kill_success表
@Mapper public interface ItemKillSuccessMapper { @Select("select count(1) from item_kill_success where user_id=#{userId} and kill_id=#{killId} and status in (0)") int countByKillUserId(@Param("killId") Integer killId, @Param("userId") Integer userId); @Insert("insert into item_kill_success(code,item_id,kill_id,user_id,status,create_time) values(#{code},#{itemId},#{killId},#{userId},#{status},#{createTime})") int insertSelective(ItemKillSuccess entity); }
在ItemKillMapper中增加一条更新数据的代码，用来处理抢购成功后更新余量
@Update("update item_kill set total=total-1 where id=#{killId}") int updateKillItem(Integer killId);
四、效果展示
运行项目，进入首页https://link.juejin.cn/?target=http%3A%2F%2Flocalhost%3A8080%2Fitem
点击详情：
点击抢购：
输出购买成功，数据库中生成一条信息
当再次购买时，显示已经抢购：
到当前功能的代码都放到https://link.juejin.cn/?target=https%3A%2F%2Fgithub.com%2FOliverLiy%2FSecondKill%2Ftree%2Fversion3.0中
我搭建了一个微信公众号《Java鱼仔》，如果你对本项目有任何疑问，欢迎在公众号中联系我，我会尽自己所能为大家解答。
