使用SpringBoot实现Redis多数据库缓存
作者:是行东啊
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,所以本文给大家介绍了使用SpringBoot实现Redis多数据库缓存,需要的朋友可以参考下
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
@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
@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
@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(); } }
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