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Spring之借助Redis设计一个简单访问计数器

为什么要做一个访问计数？之前的个人博客用得是卜算子做站点访问计数，用起来挺好，但出现较多次的响应很慢，再其次就是个人博客实在是访问太少，数据不好看...

前面一篇博文简单介绍了Spring中的RedisTemplate的配置与使用，那么这篇算是一个简单的应用case了,主要基于Redis的计数器来实现统计

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I. 设计

一个简单的访问计数器，主要利用redis的hash结构，对应的存储结构如下:

存储结构比较简单，为了扩展，每个应用（or站点）对应一个APP，然后根据path路径进行分页统计，最后有一个特殊的用于统计全站的访问计数

II. 实现

主要就是利用Redis的hash结构，然后实现数据统计，并没有太多的难度，Spring环境下搭建redis环境可以参考:

1. Redis封装类

针对几个常用的做了简单的封装，直接使用RedisTemplate的excute方法进行的操作，当然也是可以使用 template.opsForValue() 等便捷方式，这里采用JSON方式进行对象的序列化和反序列化

public class QuickRedisClient {    private static final Charset CODE = Charset.forName("UTF-8");    private static RedisTemplate
    
      template;    public static void register(RedisTemplate
     
       template) {        QuickRedisClient.template = template;    }    public static void nullCheck(Object... args) {        for (Object obj : args) {            if (obj == null) {                throw new IllegalArgumentException("redis argument can not be null!");            }        }    }    public static byte[] toBytes(String key) {        nullCheck(key);        return key.getBytes(CODE);    }    public static byte[][] toBytes(List
      
        keys) {        byte[][] bytes = new byte[keys.size()][];        int index = 0;        for (String key : keys) {            bytes[index++] = toBytes(key);        }        return bytes;    }    public static String getStr(String key) {        return template.execute((RedisCallback
       
        ) con -> {            byte[] val = con.get(toBytes(key));            return val == null ? null : new String(val);        });    }    public static void putStr(String key, String value) {        template.execute((RedisCallback
        
         ) con -> {            con.set(toBytes(key), toBytes(value));            return null;        });    }    public static Long incr(String key, long add) {        return template.execute((RedisCallback
         
          ) con -> { Long record = con.incrBy(toBytes(key), add); return record == null ? 0L : record; }); } public static Long hIncr(String key, String field, long add) { return template.execute((RedisCallback
          
           ) con -> { Long record = con.hIncrBy(toBytes(key), toBytes(field), add); return record == null ? 0L : record; }); } public static 
           
             T hGet(String key, String field, Class
            
              clz) { return template.execute((RedisCallback
             
              ) con -> { byte[] records = con.hGet(toBytes(key), toBytes(field)); if (records == null) { return null; } return JSON.parseObject(records, clz); }); } public static 
              
                Map
               
                 hMGet(String key, List
                
                  fields, Class
                 
                   clz) { List
                  
                    list = template.execute((RedisCallback
                   
                    
                     >) con -> con.hMGet(toBytes(key), toBytes(fields))); if (CollectionUtils.isEmpty(list)) { return Collections.emptyMap(); } Map
                     
                       result = new HashMap<>(); for (int i = 0; i < fields.size(); i++) { if (list.get(i) == null) { continue; } result.put(fields.get(i), JSON.parseObject(list.get(i), clz)); } return result; }}
                     
                    
                   
                  
                 
                
               
              
             
            
           
          
         
        
       
      
     
    

对应的配置类

package com.git.hui.story.cache.redis;import com.git.hui.story.cache.redis.serializer.DefaultStrSerializer;import org.springframework.cache.CacheManager;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;import org.springframework.context.annotation.PropertySource;import org.springframework.core.env.Environment;import org.springframework.data.redis.cache.RedisCacheManager;import org.springframework.data.redis.connection.RedisConnectionFactory;import org.springframework.data.redis.connection.RedisPassword;import org.springframework.data.redis.connection.lettuce.LettuceConnectionFactory;import org.springframework.data.redis.core.RedisTemplate;/** * Created by yihui in 18:45 18/6/11. */@Configuration@PropertySource(value = "classpath:application.yml")public class RedisConf {    private final Environment environment;    public RedisConf(Environment environment) {        this.environment = environment;    }    @Bean    public CacheManager cacheManager() {        return RedisCacheManager.RedisCacheManagerBuilder.fromConnectionFactory(redisConnectionFactory()).build();    }    @Bean    public RedisTemplate
    
      redisTemplate(RedisConnectionFactory redisConnectionFactory) {        RedisTemplate
     
       redisTemplate = new RedisTemplate<>();        redisTemplate.setConnectionFactory(redisConnectionFactory);        DefaultStrSerializer serializer = new DefaultStrSerializer();        redisTemplate.setValueSerializer(serializer);        redisTemplate.setHashValueSerializer(serializer);        redisTemplate.setKeySerializer(serializer);        redisTemplate.setHashKeySerializer(serializer);        redisTemplate.afterPropertiesSet();        QuickRedisClient.register(redisTemplate);        return redisTemplate;    }    @Bean    public RedisConnectionFactory redisConnectionFactory() {        LettuceConnectionFactory fac = new LettuceConnectionFactory();        fac.getStandaloneConfiguration().setHostName(environment.getProperty("spring.redis.host"));        fac.getStandaloneConfiguration().setPort(Integer.parseInt(environment.getProperty("spring.redis.port")));        fac.getStandaloneConfiguration()                .setPassword(RedisPassword.of(environment.getProperty("spring.redis.password")));        fac.afterPropertiesSet();        return fac;    }}
     
    

2. Controller 支持

首先是定义请求参数:

@Datapublic class WebCountReqDO implements Serializable {    private String appKey;    private String referer;}

其次是实现Controller接口，稍稍注意下，根据path进行计数的逻辑：

• 如果请求参数显示指定了referer参数，则用传入的参数进行统计
• 如果没有显示指定referer，则根据header获取referer
• 解析referer，分别对path和host进行统计+1，这样站点的统计计数就是根据host来的，而页面的统计计数则是根据path路径来的

@Slf4j@RestController@RequestMapping(path = "/count")public class WebCountController {    @RequestMapping(path = "cc", method = {RequestMethod.GET})    public ResponseWrapper
    
      addCount(WebCountReqDO webCountReqDO) {        String appKey = webCountReqDO.getAppKey();        if (StringUtils.isBlank(appKey)) {            return ResponseWrapper.errorReturnMix(Status.StatusEnum.ILLEGAL_PARAMS_MIX, "请指定APPKEY!");        }        String referer = ReqInfoContext.getReqInfo().getReferer();        if (StringUtils.isBlank(referer)) {            referer = webCountReqDO.getReferer();        }        if (StringUtils.isBlank(referer)) {            return ResponseWrapper.errorReturnMix(Status.StatusEnum.FAIL_MIX, "无法获取请求referer!");        }        return ResponseWrapper.successReturn(doUpdateCnt(appKey, referer));    }    private CountDTO doUpdateCnt(String appKey, String referer) {        try {            if (!referer.startsWith("http")) {                referer = "https://" + referer;            }            URI uri = new URI(referer);            String host = uri.getHost();            String path = uri.getPath();            long count = QuickRedisClient.hIncr(appKey, path, 1);            long total = QuickRedisClient.hIncr(appKey, host, 1);            return new CountDTO(count, total);        } catch (Exception e) {            log.error("get referer path error! referer: {}, e: {}", referer, e);            return new CountDTO(1L, 1L);        }    }}
    

3. 实例

针对这个简单的redis计数，目前在个人的mweb和zweb两个页面已经接入，在页脚处可以看到对应的计数，每次刷新计数会+1

• mweb:
• zweb:

III. 其他

0. 相关博文

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