1.Caffeine 是基于Java 8的高性能，接近最佳的缓存库。

2.LRUMap则是实现的LRP算法的Map集合类，它继承于AbstractLinkedMap抽象类。

主要依赖

     <dependency>
            <groupId>com.github.ben-manes.caffeine</groupId>
            <artifactId>caffeine</artifactId>
            <version>2.9.0</version>
     </dependency>
     <dependency>
           <groupId>org.apache.commons</groupId>
           <artifactId>commons-collections4</artifactId>
           <version>4.4</version>
      </dependency>

通用工具类代码

import com.github.benmanes.caffeine.cache.*;
import org.apache.commons.collections4.map.LRUMap;
import org.apache.commons.lang3.StringUtils;
import java.util.concurrent.*;

/**
 * @author beike
 */
public class IdempotentUtils {
    /**
     * 根据 LRU(Least Recently Used，最近最少使用)算法淘汰数据的 Map 集合，最大容量 100 个
     */
    private static final LRUMap<String, Integer> REQ_CACHE = new LRUMap<>(100);


    /**
     * 同步加载
     * 弱引用不管当前内存空间足够与否，都会回收它的内存
     */
    private static final LoadingCache<String, String> SYNC_LOADING_CACHE = Caffeine.newBuilder()
            //数量上限
            .maximumSize(1_000)
            //初始容量
            .initialCapacity(128)
            // 弱引用value
            .weakValues()
            // 过期机制
            .expireAfterWrite(5, TimeUnit.SECONDS)
            //刷新机制
            .refreshAfterWrite(5, TimeUnit.SECONDS)
            .removalListener((RemovalListener<String, String>) (key, value, cause) ->
                    System.out.println("key:" + key + ", value:" + value + ", 删除原因:" + cause.toString()))
            .build(key -> null);
    

    /**
     * Caffeine 同步加载
     *
     * @param key 一般是请求的url+业务id
     * @return 重复提交 true 第一次提交
     */
    public static boolean judgeCaffeineSync(String key) {
        String value = SYNC_LOADING_CACHE.get(key);
        // 重复请求判断
        if (StringUtils.isNotBlank(value)) {
            return false;
        }
        // 非重复请求，存储请求
        SYNC_LOADING_CACHE.put(key, key);
        return true;
    }


    /**
     * 双重检测锁 DCL+LRUMap
     *
     * @param key 一般是请求的url+业务id
     * @param lockClass 服务层Class
     * @return 重复提交 true 第一次提交
     */
    public static boolean judgeLruMap(String key, Object lockClass) {
        if (REQ_CACHE.containsKey(key)) {
            // 重复请求
            return false;
        }
        synchronized (lockClass) {
            // 重复请求判断
            if (REQ_CACHE.containsKey(key)) {
                return false;
            }
            // 非重复请求，存储请求key
            REQ_CACHE.put(key, 1);
        }
        return true;
    }
}

案例

    @PutMapping("/update")
    @ApiOperation(value = "更新商品", httpMethod = "PUT")
    public ResponseData<String> update(@RequestBody @Validated Vo vo) {
        log.info("{}用户更新,{}", TokenUtil.getCurrentUserName(), JSON.toJSONString(vo));
        if (!IdempotentUtils.judgeCaffeineSync("/v1/goods/update/" + vo.getId())) {
            return ResponseUtil.fail(MessageConstant.SYS_REPEAT_SUMMIT_FAIL);
        }
        //todo  执行业务代码
        service.update(vo);
        return ResponseUtil.success();
    }

Java后端防止频繁请求、重复提交

在客户端网络慢或者服务器响应慢时，用户有时是会频繁刷新页面或重复提交表单的，这样是会给服务器造成不小的负担的，同时在添加数据时有可能造成不必要的麻烦。所以我们在后端也有必要进行防抖操作。

1. 自定义注解

/**
 * @author Tzeao
 */
@Target(ElementType.METHOD) // 作用到方法上
@Retention(RetentionPolicy.RUNTIME) // 运行时有效
public @interface NoRepeatSubmit {

    //名称，如果不给就是要默认的
    String name() default "name";
}

2. 使用AOP实现该注解

/**
 * @author Tzeao
 */
@Aspect
@Component
@Slf4j
public class NoRepeatSubmitAop {

    @Autowired
    private RedisService redisService;

    /**
     * 切入点
     */
    @Pointcut("@annotation(com.qwt.part_time_admin_api.common.validation.NoRepeatSubmit)")
    public void pt() {
    }

    @Around("pt()")
    public Object arround(ProceedingJoinPoint joinPoint) throws Throwable {

        ServletRequestAttributes attributes = (ServletRequestAttributes) RequestContextHolder.getRequestAttributes();
        assert attributes != null;
        HttpServletRequest request = attributes.getRequest();
        //这里是唯一标识 根据情况而定
        String key = "1" + "-" + request.getServletPath();
        // 如果缓存中有这个url视为重复提交
        if (!redisService.haskey(key)) {
            //通过，执行下一步
            Object o = joinPoint.proceed();
            //然后存入redis 并且设置15s倒计时
            redisService.setCacheObject(key, 0, 15, TimeUnit.SECONDS);
            //返回结果
            return o;
        } else {
            return Result.fail(400, "请勿重复提交或者操作过于频繁！");
        }

    }
}

3. serice，也可以放在工具包里面，这里我们使用到了Redis来对key和标识码进行存储和倒计时,所以在使用时还需要连接一下Redis

package com.qwt.part_time_admin_api.service;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.*;
import org.springframework.stereotype.Component;

import java.util.*;
import java.util.concurrent.TimeUnit;


/**
* @author Tzeao
*/
@Component
public class RedisService {

@Autowired
public RedisTemplate redisTemplate;

/**
 * 缓存基本的对象，Integer、String、实体类等
 *
 * @param key   缓存的键值
 * @param value 缓存的值
 * @return 缓存的对象
 */
public <T> ValueOperations<String, T> setCacheObject(String key, T value) {
    ValueOperations<String, T> operation = redisTemplate.opsForValue();
    operation.set(key, value);
    return operation;
}

/**
 * 缓存基本的对象，Integer、String、实体类等
 *
 * @param key      缓存的键值
 * @param value    缓存的值
 * @param timeout  时间
 * @param timeUnit 时间颗粒度
 * @return 缓存的对象
 */
public <T> ValueOperations<String, T> setCacheObject(String key, T value, Integer timeout, TimeUnit timeUnit) {
    ValueOperations<String, T> operation = redisTemplate.opsForValue();
    operation.set(key, value, timeout, timeUnit);
    return operation;
}

/**
 * 获得缓存的基本对象。
 *
 * @param key 缓存键值
 * @return 缓存键值对应的数据
 */
public <T> T getCacheObject(String key) {
    ValueOperations<String, T> operation = redisTemplate.opsForValue();
    return operation.get(key);
}

/**
 * 删除单个对象
 *
 * @param key
 */
public void deleteObject(String key) {
    redisTemplate.delete(key);
}

/**
 * 删除集合对象
 *
 * @param collection
 */
public void deleteObject(Collection collection) {
    redisTemplate.delete(collection);
}

/**
 * 缓存List数据
 *
 * @param key      缓存的键值
 * @param dataList 待缓存的List数据
 * @return 缓存的对象
 */
public <T> ListOperations<String, T> setCacheList(String key, List<T> dataList) {
    ListOperations listOperation = redisTemplate.opsForList();
    if (null != dataList) {
        int size = dataList.size();
        for (int i = 0; i < size; i++) {
            listOperation.leftPush(key, dataList.get(i));
        }
    }
    return listOperation;
}

/**
 * 获得缓存的list对象
 *
 * @param key 缓存的键值
 * @return 缓存键值对应的数据
 */
public <T> List<T> getCacheList(String key) {
    List<T> dataList = new ArrayList<>();
    ListOperations<String, T> listOperation = redisTemplate.opsForList();
    Long size = listOperation.size(key);

    for (int i = 0; i < size; i++) {
        dataList.add(listOperation.index(key, i));
    }
    return dataList;
}

/**
 * 缓存Set
 *
 * @param key     缓存键值
 * @param dataSet 缓存的数据
 * @return 缓存数据的对象
 */
public <T> BoundSetOperations<String, T> setCacheSet(String key, Set<T> dataSet) {
    BoundSetOperations<String, T> setOperation = redisTemplate.boundSetOps(key);
    Iterator<T> it = dataSet.iterator();
    while (it.hasNext()) {
        setOperation.add(it.next());
    }
    return setOperation;
}

/**
 * 获得缓存的set
 *
 * @param key
 * @return
 */
public <T> Set<T> getCacheSet(String key) {
    Set<T> dataSet = new HashSet<>();
    BoundSetOperations<String, T> operation = redisTemplate.boundSetOps(key);
    dataSet = operation.members();
    return dataSet;
}

/**
 * 缓存Map
 *
 * @param key
 * @param dataMap
 * @return
 */
public <T> HashOperations<String, String, T> setCacheMap(String key, Map<String, T> dataMap) {
    HashOperations hashOperations = redisTemplate.opsForHash();
    if (null != dataMap) {
        for (Map.Entry<String, T> entry : dataMap.entrySet()) {
            hashOperations.put(key, entry.getKey(), entry.getValue());
        }
    }
    return hashOperations;
}

/**
 * 获得缓存的Map
 *
 * @param key
 * @return
 */
public <T> Map<String, T> getCacheMap(String key) {
    Map<String, T> map = redisTemplate.opsForHash().entries(key);
    return map;
}

/**
 * 获得缓存的基本对象列表
 *
 * @param pattern 字符串前缀
 * @return 对象列表
 */
public Collection<String> keys(String pattern) {
    return redisTemplate.keys(pattern);
}

/**
 * @param key
 * @return
 */
public boolean haskey(String key) {
    return redisTemplate.hasKey(key);
}

public Long getExpire(String key) {
    return redisTemplate.getExpire(key);
}


public <T> ValueOperations<String, T> setBillObject(String key, List<Map<String, Object>> value) {
    ValueOperations<String, T> operation = redisTemplate.opsForValue();
    operation.set(key, (T) value);
    return operation;
}

/**
 * 缓存list<Map<String, Object>>
 *
 * @param key      缓存的键值
 * @param value    缓存的值
 * @param timeout  时间
 * @param timeUnit 时间颗粒度
 * @return 缓存的对象
 */
public <T> ValueOperations<String, T> setBillObject(String key, List<Map<String, Object>> value, Integer timeout, TimeUnit timeUnit) {
    ValueOperations<String, T> operation = redisTemplate.opsForValue();
    operation.set(key, (T) value, timeout, timeUnit);
    return operation;
}

/**
 * 缓存Map
 *
 * @param key
 * @param dataMap
 * @return
 */
public <T> HashOperations<String, String, T> setCKdBillMap(String key, Map<String, T> dataMap) {
    HashOperations hashOperations = redisTemplate.opsForHash();
    if (null != dataMap) {
        for (Map.Entry<String, T> entry : dataMap.entrySet()) {
            hashOperations.put(key, entry.getKey(), entry.getValue());
        }
    }
    return hashOperations;
}
}

4. 测试

  @NoRepeatSubmit(name = "test") // 也可以不给名字，这样就会走默认名字
    @GetMapping("test")
    public Result test() {
        return Result.success("测试阶段！");
    }

15秒内重复点击就会给提示

这样就完成了一个防止重复提交、频繁申请的程序
参考：https://blog.csdn.net/chengmin123456789/article/details/107982095?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522164937993716780265483684%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=164937993716780265483684&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2_allfirst_rank_ecpm_v1~rank_v31_ecpm-1-107982095.142^v7pc_search_result_control_group,157^v4new_style&utm_term=%E5%90%8E%E7%AB%AF+%E9%98%B2%E6%AD%A2%E9%A2%91%E7%B9%81%E5%88%B7%E6%96%B0&spm=1018.2226.3001.4187

一、为什么会出现重复提交？

主要是由于网络的延迟问题以及页面刷新的操作。

二、表单的重复提交会导致的问题？

主要能够造成很多脏数据。

三、解决的办法：

3.1 前端解决办法：通过前端的方法将提交按钮变灰。对于前端的办法这里就不做演示了，因为前端的控制虽然能够防止数据的重复提交但是治标不治本。这里主要介绍第二种方法。

3.2 后端解决： 思路：主要是利用唯一Token值与提交参数相匹配验证。

后端解决的代码示例：

1.前端页面

<%@ page language="java" import="java.util.*" pageEncoding="utf-8"%>
<%
	String path = request.getContextPath();
	String basePath = request.getScheme() + "://" + request.getServerName() + ":" + request.getServerPort()
			+ path + "/";
%>

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<base href="<%=basePath%>">

<title>My JSP 'index.jsp' starting page</title>
<meta http-equiv="pragma" content="no-cache">
<meta http-equiv="cache-control" content="no-cache">
<meta http-equiv="expires" content="0">
<meta http-equiv="keywords" content="keyword1,keyword2,keyword3">
<meta http-equiv="description" content="This is my page">
<!--
	<link rel="stylesheet" type="text/css" href="styles.css">
	-->
</head>

<body>
	<form action="${pageContext.request.contextPath}/DoFormServlet" method="post">
		<input type="hidden" name="token" value="${sessionToken}">
		用户名：<input type="text" name="userName"> <input type="submit"
			value="提交" id="submit">
	</form>
</body>
</html>

package session;

import java.io.IOException;
import java.util.UUID;

import javax.servlet.ServletException;
import javax.servlet.annotation.WebServlet;
import javax.servlet.http.HttpServlet;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
@WebServlet("/SendTokenToForm")
public class SendTokenToForm extends HttpServlet {
	
	/**
	 * 
	 */
	private static final long serialVersionUID = 5841829906440324978L;

	@Override
	protected void doGet(HttpServletRequest req, HttpServletResponse resp) throws ServletException, IOException {
		req.getSession().setAttribute("sessionToken", UUID.randomUUID().toString());
		req.getRequestDispatcher("/index.jsp").forward(req, resp);
	}

}

package session;

import java.io.IOException;

import javax.servlet.ServletException;
import javax.servlet.annotation.WebServlet;
import javax.servlet.http.HttpServlet;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
@WebServlet("/DoFormServlet")
public class DoFormServlet extends HttpServlet {
	
	/**
	 * 
	 */
	private static final long serialVersionUID = 82128771669092572L;

	@Override
	protected void doPost(HttpServletRequest req, HttpServletResponse resp) throws ServletException, IOException {
		if (!isSubmit(req)) {
			resp.getWriter().write("数据已提交");
			System.out.println("数据已提交");
		}
		//让线程休眠0.9秒，方便测试
		try {
			Thread.sleep(900);
		} catch (InterruptedException e) {
			e.printStackTrace();
		}
		
		String userName = req.getParameter("userName");
		System.out.println("正在往数据库插入数据"+userName);
		resp.getWriter().write("success");
		
	}
	/**
	 * @Title: isSubmit
	 * @Description: 判断token值是否相同以及是否有伪token值得传入
	 * @author 西安工业大学-查文彬
	 * @time 2017年10月2日 下午5:53:41 
	 * @param request
	 * @return
	 * boolean
	 */
	
	public boolean isSubmit(HttpServletRequest request){
		String sessionToken = (String) request.getSession().getAttribute("sessionToken");
		String parameter = request.getParameter("token");
		if (!(sessionToken.equals(parameter))) {
			return false;
		}
		request.getSession().removeAttribute("sessionToken");
		return true;
	}

}