Redis多数据库存储实现用户行为缓存
在我的系统中,为了优化用户行为数据的存储与访问效率,我引入了Redis缓存,并将数据分布在不同的Redis数据库中。通过这种方式,可以减少单一数据库的负载,提高系统的整体性能。
主要实现步骤
-
Redis配置
- 配置两个Redis连接工厂,分别用于存储Token和用户行为数据。
- 创建对应的RedisTemplate实例,指定不同的连接工厂及序列化方式。
-
用户行为服务
- 通过
UserBehaviorService
接口及其实现类UserBehaviorServiceImpl
,实现对用户点赞、收藏、评论、浏览行为的记录。 - 在操作数据库的同时,将用户行为数据存储到Redis中以提高读取效率。
- 通过
-
Token拦截器
- 使用
TokenInterceptor
类在每次请求前验证Token。 - 验证通过后,将用户信息存储到
ThreadLocal
中,供后续操作使用。
- 使用
代码实现
Redis配置类
java
@Configuration
public class RedisConfig {
@Value("${spring.data.redis.host}")
private String redisHost;
@Value("${spring.data.redis.port}")
private int redisPort;
@Value("${spring.data.redis.password}")
private String redisPassword;
@Bean(name = "tokenRedisConnectionFactory")
public RedisConnectionFactory tokenRedisConnectionFactory() {
RedisStandaloneConfiguration config = new RedisStandaloneConfiguration(redisHost, redisPort);
config.setPassword(redisPassword);
config.setDatabase(0);
return new LettuceConnectionFactory(config);
}
@Bean(name = "userBehaviorRedisConnectionFactory")
public RedisConnectionFactory userBehaviorRedisConnectionFactory() {
RedisStandaloneConfiguration config = new RedisStandaloneConfiguration(redisHost, redisPort);
config.setPassword(redisPassword);
config.setDatabase(1);
return new LettuceConnectionFactory(config);
}
@Bean(name = "redisTemplate")
public StringRedisTemplate redisTemplate(@Qualifier("tokenRedisConnectionFactory") RedisConnectionFactory redisConnectionFactory) {
StringRedisTemplate template = new StringRedisTemplate();
template.setConnectionFactory(redisConnectionFactory);
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(new StringRedisSerializer());
return template;
}
@Bean(name = "userBehaviorRedisTemplate")
public RedisTemplate<String, Map<String, Integer>> userBehaviorRedisTemplate(@Qualifier("userBehaviorRedisConnectionFactory") RedisConnectionFactory redisConnectionFactory) {
RedisTemplate<String, Map<String, Integer>> template = new RedisTemplate<>();
template.setConnectionFactory(redisConnectionFactory);
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(new Jackson2JsonRedisSerializer<>(Map.class));
return template;
}
}
用户行为服务实现类
java
@Service
public class UserBehaviorServiceImpl implements UserBehaviorService {
private static final long CACHE_EXPIRATION_DAYS = 1;
private static final String CACHE_PREFIX = "articleCounts:";
@Autowired
private UserBehaviorMapper userBehaviorMapper;
@Autowired
@Qualifier("userBehaviorRedisTemplate")
private RedisTemplate<String, Map<String, Integer>> userBehaviorRedisTemplate;
@Override
public void setLikeArticle(Likes likes) {
likes.setCreateTime(LocalDateTime.now());
Integer userId = ThreadLocalUtil.getUser("id");
if (userId != null) {
likes.setUserId(userId);
}
userBehaviorMapper.insertLike(likes);
}
@Override
public void setFavoriteArticle(Favorites favorites) {
favorites.setCreateTime(LocalDateTime.now());
Integer userId = ThreadLocalUtil.getUser("id");
if (userId != null) {
favorites.setUserId(userId);
}
userBehaviorMapper.insertFavorite(favorites);
}
@Override
public void setCommentArticle(Comments comments) {
comments.setCreateTime(LocalDateTime.now());
Integer userId = ThreadLocalUtil.getUser("id");
if (userId != null) {
comments.setUserId(userId);
}
userBehaviorMapper.insertComment(comments);
}
@Override
public void setViewArticle(Views views) {
views.setCreateTime(LocalDateTime.now());
Integer userId = ThreadLocalUtil.getUser("id");
if (userId != null) {
views.setUserId(userId);
}
userBehaviorMapper.insertView(views);
}
@Override
public Map<String, Integer> getArticleCounts(Integer articleId) {
String key = CACHE_PREFIX + articleId;
Map<String, Integer> counts = userBehaviorRedisTemplate.opsForValue().get(key);
if (counts == null) {
counts = fetchArticleCountsFromDB(articleId);
cacheArticleCounts(articleId, counts);
}
return counts;
}
private Map<String, Integer> fetchArticleCountsFromDB(Integer articleId) {
Map<String, Integer> counts = new HashMap<>();
counts.put("likesCount", userBehaviorMapper.selectLikesCount(articleId));
counts.put("favoritesCount", userBehaviorMapper.selectFavoritesCount(articleId));
counts.put("commentsCount", userBehaviorMapper.selectCommentsCount(articleId));
counts.put("viewsCount", userBehaviorMapper.selectViewsCount(articleId));
return counts;
}
private void cacheArticleCounts(Integer articleId, Map<String, Integer> counts) {
String key = CACHE_PREFIX + articleId;
userBehaviorRedisTemplate.opsForValue().set(key, counts, CACHE_EXPIRATION_DAYS, TimeUnit.DAYS);
}
}
Token拦截器
java
@Component
public class TokenInterceptor implements HandlerInterceptor {
@Autowired
private StringRedisTemplate redisTemplate;
@Override
public boolean preHandle(HttpServletRequest request, @NotNull HttpServletResponse response, @NotNull Object handler) throws Exception {
String token = request.getHeader("Authorization");
if (token == null || token.isEmpty()) {
response.setStatus(HttpStatus.UNAUTHORIZED.value());
return false;
}
try {
ValueOperations<String, String> operations = redisTemplate.opsForValue();
String redisToken = operations.get(token);
if (redisToken == null) {
response.setStatus(HttpStatus.UNAUTHORIZED.value());
return false;
}
Map<String, Object> claims = JwtUtil.parseToken(token);
ThreadLocalUtil.setUser(claims);
return true;
} catch (Exception e) {
response.setStatus(HttpStatus.UNAUTHORIZED.value());
return false;
}
}
@Override
public void postHandle(@NotNull HttpServletRequest request, @NotNull HttpServletResponse response, @NotNull Object handler, ModelAndView modelAndView) throws Exception {
}
@Override
public void afterCompletion(@NotNull HttpServletRequest request, @NotNull HttpServletResponse response, @NotNull Object handler, Exception ex) throws Exception {
ThreadLocalUtil.remove();
}
}