java高并发秒杀活动的各种简单实现【springBoot+mybatis+redis+mysql】
最近遇到比较多数据不一致的问题，大多数都是因为并发请求时，没及时处理的原因，故用一个比较有代表性的业务场景【活动秒杀】来模拟一下这个这种高并发所产生的问题。
首先搭建一个springboot项目在这里我做演示了，不会的可以自行百度，搭建过程很简单。
1：搭建好的项目目录结构
2：商品表(记录商品名称，本次可以秒杀的库存量)
加了一条记录（后面每次测试都先手动把库存恢复成100才进行测试）
3：实体类（这里不用实体类也可以，根据自己的需求来）
一、不做任何处理的高并发秒杀实现（错误演示）：
1.Controller层，模拟500个并发调用：
package com.mybatis.controller;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.*;
@Controller
@RequestMapping(value="/miaoshagoods")
public class MiaoshaController {
@Autowired
public MiaoshaService miaoshaService;
@PostMapping("/miaosha_java_sql_lock")
public @ResponseBody BaseResponse miaoshaJavaSqlLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
//不做任何处理的秒杀实现
miaoshaService.miaoshaGoods(request,response);
}
});
thread.start();
}
return response;
}
}
2.Service层，每个请求进来就去数据库里查剩余的库存量，并且抢购成功后，就减1个库存：
package com.mybatis.service.Impl;
import com.mybatis.dao.MiaoShaGoodsDao;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.model.MiaoShaGoods;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Service
public class MiashaServiceImpl implements MiaoshaService{
@Autowired
MiaoShaGoodsDao miaoShaGoodsDao;
private Lock lock = new ReentrantLock();
@Autowired
private RedisTemplate<String,String> redisTemplate;
/**
* 不做任何处理的秒杀实现
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods(MiaoshaRequest request, BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
}
3.dao层（mybatis的xml文件）：
<select id="getGoods" parameterType="java.lang.String" resultMap="BaseResultMap">
select
<include refid="Base_Column_List" />
from miao_sha_goods
where goods_name = #{goodsName,jdbcType=VARCHAR}
</select>
<update id="updateMsGoods" parameterType="com.mybatis.model.MiaoShaGoods">
update miao_sha_goods
set goods_sum = #{goodsSum,jdbcType=INTEGER}
where goods_name = #{goodsName,jdbcType=VARCHAR}
</update>
4.测试结果：
截图表明，居然有500个人抢购成功，而且库存量却只减少了12个，这是明显是错误的。
二、数据库乐观锁处理的高并发秒杀实现：
package com.mybatis.controller;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.*;
@Controller
@RequestMapping(value="/miaoshagoods")
public class MiaoshaController {
@Autowired
public MiaoshaService miaoshaService;
@PostMapping("/miaosha_java_sql_lock")
public @ResponseBody BaseResponse miaoshaJavaSqlLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
//不做任何处理的秒杀实现
//miaoshaService.miaoshaGoods(request,response);
//数据库乐观锁秒杀
miaoshaService.miaoshaGoods_sql_optimistic_lock(request,response);
}
});
thread.start();
}
return response;
}
}
2.Service层，每个请求进来就去数据库里查剩余的库存量，并且抢购成功后，就减1个库存：
package com.mybatis.service.Impl;
import com.mybatis.dao.MiaoShaGoodsDao;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.model.MiaoShaGoods;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Service
public class MiashaServiceImpl implements MiaoshaService{
@Autowired
MiaoShaGoodsDao miaoShaGoodsDao;
private Lock lock = new ReentrantLock();
@Autowired
private RedisTemplate<String,String> redisTemplate;
/**
* 不做任何处理的秒杀实现
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods(MiaoshaRequest request, BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* 数据库乐观锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_sql_optimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_lgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_lgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
//做出相应的逻辑（记录抢购成功的用户名什么的....）
}else{
System.out.println("抢到iphoneX,失败！");
//重试或者返回友好的提示什么的....
}
return response;
}
}
3.dao层（mybatis的xml文件）[在SQL层面改为数据库乐观锁]：
<select id="getGoods_lgs" parameterType="java.lang.String" resultMap="BaseResultMap">
select
<include refid="Base_Column_List" />
from miao_sha_goods
where goods_name = #{goodsName,jdbcType=VARCHAR}
</select>
<update id="updateMsGoods_lgs" parameterType="com.mybatis.model.MiaoShaGoods">
update miao_sha_goods
set goods_sum = #{goodsSum,jdbcType=INTEGER},version=version+1
where goods_name = #{goodsName,jdbcType=VARCHAR} and version = #{version,jdbcType=VARCHAR}
</update>
4.测试结果：
截图表明，总共有500个人抢，有29个人抢购成功，而且库存量减少了29个，这保证了库存的正确性。但却会有抢购不成功的请求，需要我们后续去处理。
三、数据库悲观锁处理的高并发秒杀实现：
1.Controller层，模拟500个并发调用：
package com.mybatis.controller;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.*;
@Controller
@RequestMapping(value="/miaoshagoods")
public class MiaoshaController {
@Autowired
public MiaoshaService miaoshaService;
@PostMapping("/miaosha_java_sql_lock")
public @ResponseBody BaseResponse miaoshaJavaSqlLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
//不做任何处理的秒杀实现
//miaoshaService.miaoshaGoods(request,response);
//数据库乐观锁秒杀
//miaoshaService.miaoshaGoods_sql_optimistic_lock(request,response);
//数据库悲观锁秒杀
miaoshaService.miaoshaGoods_sql_pessimistic_lock(request,response);
}
});
thread.start();
}
return response;
}
}
2.Service层，每个请求进来就去数据库里查剩余的库存量，并且抢购成功后，就减1个库存（查询和更新必须在同一个事务）：
package com.mybatis.service.Impl;
import com.mybatis.dao.MiaoShaGoodsDao;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.model.MiaoShaGoods;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Service
public class MiashaServiceImpl implements MiaoshaService{
@Autowired
MiaoShaGoodsDao miaoShaGoodsDao;
private Lock lock = new ReentrantLock();
@Autowired
private RedisTemplate<String,String> redisTemplate;
/**
* 不做任何处理的秒杀实现
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods(MiaoshaRequest request, BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* 数据库乐观锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_sql_optimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_lgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_lgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
//做出相应的逻辑（记录抢购成功的用户名什么的....）
}else{
System.out.println("抢到iphoneX,失败！");
//重试或者返回友好的提示什么的....
}
return response;
}
/**
* 数据库悲观锁实现秒杀
* @param request
* @return
*/
@Override
@Transactional
public BaseResponse miaoshaGoods_sql_pessimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_bgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_bgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
}
3.dao层（mybatis的xml文件）[在SQL层面改为数据库悲观锁]：
<select id="getGoods_bgs" parameterType="java.lang.String" resultMap="BaseResultMap">
select
<include refid="Base_Column_List" />
from miao_sha_goods
where goods_name = #{goodsName,jdbcType=VARCHAR} FOR UPDATE
</select>
<update id="updateMsGoods_bgs" parameterType="com.mybatis.model.MiaoShaGoods">
update miao_sha_goods
set goods_sum = #{goodsSum,jdbcType=INTEGER}
where goods_name = #{goodsName,jdbcType=VARCHAR}
</update>
4.测试结果：
截图表明，总共有500个人抢，有100个人抢购成功，而且库存量减少了100个，这保证了库存的正确性。
四、java线程同步锁处理的高并发秒杀实现：
1.Controller层，模拟500个并发调用：
package com.mybatis.controller;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.*;
@Controller
@RequestMapping(value="/miaoshagoods")
public class MiaoshaController {
@Autowired
public MiaoshaService miaoshaService;
@PostMapping("/miaosha_java_sql_lock")
public @ResponseBody BaseResponse miaoshaJavaSqlLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
//不做任何处理的秒杀实现
//miaoshaService.miaoshaGoods(request,response);
//数据库乐观锁秒杀
//miaoshaService.miaoshaGoods_sql_optimistic_lock(request,response);
//数据库悲观锁秒杀
//miaoshaService.miaoshaGoods_sql_pessimistic_lock(request,response);
//java线程同步锁秒杀
miaoshaService.miaoshaGoods_java_synchronized_lock(request,response);
}
});
thread.start();
}
return response;
}
}
2.Service层，每个请求进来就去数据库里查剩余的库存量，并且抢购成功后，就减1个库存：
package com.mybatis.service.Impl;
import com.mybatis.dao.MiaoShaGoodsDao;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.model.MiaoShaGoods;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Service
public class MiashaServiceImpl implements MiaoshaService{
@Autowired
MiaoShaGoodsDao miaoShaGoodsDao;
private Lock lock = new ReentrantLock();
@Autowired
private RedisTemplate<String,String> redisTemplate;
/**
* 不做任何处理的秒杀实现
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods(MiaoshaRequest request, BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* 数据库乐观锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_sql_optimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_lgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_lgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
//做出相应的逻辑（记录抢购成功的用户名什么的....）
}else{
System.out.println("抢到iphoneX,失败！");
//重试或者返回友好的提示什么的....
}
return response;
}
/**
* 数据库悲观锁实现秒杀
* @param request
* @return
*/
@Override
@Transactional
public BaseResponse miaoshaGoods_sql_pessimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_bgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_bgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* java同步锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_java_synchronized_lock(MiaoshaRequest request,BaseResponse response) {
synchronized(this){
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
}
return response;
}
}
3.dao层（mybatis的xml文件）：
<select id="getGoods" parameterType="java.lang.String" resultMap="BaseResultMap">
select
<include refid="Base_Column_List" />
from miao_sha_goods
where goods_name = #{goodsName,jdbcType=VARCHAR}
</select>
<update id="updateMsGoods" parameterType="com.mybatis.model.MiaoShaGoods">
update miao_sha_goods
set goods_sum = #{goodsSum,jdbcType=INTEGER}
where goods_name = #{goodsName,jdbcType=VARCHAR}
</update>
4.测试结果：
截图表明，总共有500个人抢，有100个人抢购成功，而且库存量减少了100个，这保证了库存的正确性。
五、java线程可重入锁处理的高并发秒杀实现：
1.Controller层，模拟500个并发调用：
package com.mybatis.controller;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.*;
@Controller
@RequestMapping(value="/miaoshagoods")
public class MiaoshaController {
@Autowired
public MiaoshaService miaoshaService;
@PostMapping("/miaosha_java_sql_lock")
public @ResponseBody BaseResponse miaoshaJavaSqlLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
//不做任何处理的秒杀实现
//miaoshaService.miaoshaGoods(request,response);
//数据库乐观锁秒杀
//miaoshaService.miaoshaGoods_sql_optimistic_lock(request,response);
//数据库悲观锁秒杀
//miaoshaService.miaoshaGoods_sql_pessimistic_lock(request,response);
//java线程同步锁秒杀
//miaoshaService.miaoshaGoods_java_synchronized_lock(request,response);
//java线程可重入锁秒杀
miaoshaService.miaoshaGoods_java_reentrant_lock(request,response);
}
});
thread.start();
}
return response;
}
}
2.Service层，每个请求进来就去数据库里查剩余的库存量，并且抢购成功后，就减1个库存：
package com.mybatis.service.Impl;
import com.mybatis.dao.MiaoShaGoodsDao;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.model.MiaoShaGoods;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Service
public class MiashaServiceImpl implements MiaoshaService{
@Autowired
MiaoShaGoodsDao miaoShaGoodsDao;
private Lock lock = new ReentrantLock();
@Autowired
private RedisTemplate<String,String> redisTemplate;
/**
* 不做任何处理的秒杀实现
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods(MiaoshaRequest request, BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* 数据库乐观锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_sql_optimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_lgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_lgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
//做出相应的逻辑（记录抢购成功的用户名什么的....）
}else{
System.out.println("抢到iphoneX,失败！");
//重试或者返回友好的提示什么的....
}
return response;
}
/**
* 数据库悲观锁实现秒杀
* @param request
* @return
*/
@Override
@Transactional
public BaseResponse miaoshaGoods_sql_pessimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_bgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_bgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* java同步锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_java_synchronized_lock(MiaoshaRequest request,BaseResponse response) {
synchronized(this){
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
}
return response;
}
/**
* java可重入锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_java_reentrant_lock(MiaoshaRequest request,BaseResponse response) {
lock.lock();
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println(request.getGoodNames()+"抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
lock.unlock();
return response;
}
}
3.dao层（mybatis的xml文件）：
<select id="getGoods" parameterType="java.lang.String" resultMap="BaseResultMap">
select
<include refid="Base_Column_List" />
from miao_sha_goods
where goods_name = #{goodsName,jdbcType=VARCHAR}
</select>
<update id="updateMsGoods" parameterType="com.mybatis.model.MiaoShaGoods">
update miao_sha_goods
set goods_sum = #{goodsSum,jdbcType=INTEGER}
where goods_name = #{goodsName,jdbcType=VARCHAR}
</update>
4.测试结果：
截图表明，总共有500个人抢，有100个人抢购成功，而且库存量减少了100个，这保证了库存的正确性。
六、redis单线程处理的高并发秒杀实现（推荐）：
1.Controller层，模拟500个并发调用：
package com.mybatis.controller;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.*;
@Controller
@RequestMapping(value="/miaoshagoods")
public class MiaoshaController {
@Autowired
public MiaoshaService miaoshaService;
@Autowired
private RedisTemplate<String,String> redisTemplate;
@PostMapping("/miaosha_java_sql_lock")
public @ResponseBody BaseResponse miaoshaJavaSqlLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
//不做任何处理的秒杀实现
//miaoshaService.miaoshaGoods(request,response);
//数据库乐观锁秒杀
//miaoshaService.miaoshaGoods_sql_optimistic_lock(request,response);
//数据库悲观锁秒杀
//miaoshaService.miaoshaGoods_sql_pessimistic_lock(request,response);
//java线程同步锁秒杀
//miaoshaService.miaoshaGoods_java_synchronized_lock(request,response);
//java线程可重入锁秒杀
miaoshaService.miaoshaGoods_java_reentrant_lock(request,response);
}
});
thread.start();
}
return response;
}
// redis 防止超卖
@PostMapping("/miaosha_redis_lock")
public @ResponseBody BaseResponse miaoshaRedisLock(@RequestBody MiaoshaRequest request){
BaseResponse response=new BaseResponse();
//初始化商品数量
Integer goodsSum=miaoshaService.getGoodsSum(request);
redisTemplate.opsForValue().set(request.getGoodNames()+":goodsSum",goodsSum+"");
System.out.println("总共的库存量："+goodsSum);
for(int i=0;i<500;i++){
Thread thread=new Thread(new Runnable() {
@Override
public void run() {
miaoshaService.miaoshaGoods_redis(request,response);
}
});
thread.start();
}
return response;
}
}
2.Service层，先把参与秒杀的总库存量写入redis里，然后再利用redis的增量方法去递减：
package com.mybatis.service.Impl;
import com.mybatis.dao.MiaoShaGoodsDao;
import com.mybatis.domain.BaseResponse;
import com.mybatis.domain.MiaoshaRequest;
import com.mybatis.model.MiaoShaGoods;
import com.mybatis.service.MiaoshaService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
@Service
public class MiashaServiceImpl implements MiaoshaService{
@Autowired
MiaoShaGoodsDao miaoShaGoodsDao;
private Lock lock = new ReentrantLock();
@Autowired
private RedisTemplate<String,String> redisTemplate;
/**
* 不做任何处理的秒杀实现
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods(MiaoshaRequest request, BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* 数据库乐观锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_sql_optimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_lgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_lgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
//做出相应的逻辑（记录抢购成功的用户名什么的....）
}else{
System.out.println("抢到iphoneX,失败！");
//重试或者返回友好的提示什么的....
}
return response;
}
/**
* 数据库悲观锁实现秒杀
* @param request
* @return
*/
@Override
@Transactional
public BaseResponse miaoshaGoods_sql_pessimistic_lock(MiaoshaRequest request,BaseResponse response) {
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods_bgs(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods_bgs(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
return response;
}
/**
* java同步锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_java_synchronized_lock(MiaoshaRequest request,BaseResponse response) {
synchronized(this){
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println("抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
}
return response;
}
/**
* java可重入锁实现秒杀
* @param request
* @return
*/
@Override
public BaseResponse miaoshaGoods_java_reentrant_lock(MiaoshaRequest request,BaseResponse response) {
lock.lock();
int countSuc=0;
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
if(miaoShaGoods.getGoodsSum()>0){
miaoShaGoods.setGoodsSum(miaoShaGoods.getGoodsSum()-1);
countSuc= miaoShaGoodsDao.updateMsGoods(miaoShaGoods);
}
if(countSuc==1){
System.out.println(request.getGoodNames()+"抢到iphoneX,成功！");
}else{
System.out.println("抢到iphoneX,失败！");
}
lock.unlock();
return response;
}
@Override
public Integer getGoodsSum(MiaoshaRequest request) {
MiaoShaGoods miaoShaGoods=miaoShaGoodsDao.getGoods(request.getGoodNames());
return miaoShaGoods.getGoodsSum();
}
/**
* redis实现秒杀
* @param response
* @return
*/
@Override
public BaseResponse miaoshaGoods_redis(MiaoshaRequest request,BaseResponse response) {
//增量计算剩余库存(利用redis的单线程特性)
double goodsSurplusSum=redisTemplate.opsForValue().increment(request.getGoodNames()+":goodsSum",-1);
if(goodsSurplusSum>=0){
System.out.println("抢到iphoneX,成功！还剩下："+goodsSurplusSum);
}else {
System.out.println("抢到iphoneX,失败！");
}
return response;
}
}
3.测试结果：
截图表明，总共有500个人抢，有100个人抢购成功，而且库存量减少了100个，这保证了库存的正确性，抢后redis显示是-400个，说明有500个人进来了，有400个人抢不到。
综上所述，要控制库存量，一般要用锁机制。但是一般加锁的话会比较影响性能（只能用于单服务），推荐大家使用redis自带的线程安全属性来实现（可实现分布式锁）。
posted on 2021-05-26 11:25 UnmatchedSelf 阅读(2136) 评论(0) 编辑 收藏 举报
