Java防止频繁请求、重复提交的操作代码(后端防抖操作)

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

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