@Configuration
@EnableCaching
public class RedisCacheConfig {
    @Bean
    public RedisCacheManagerBuilderCustomizer redisCacheManagerBuilderCustomizer() {
        return (builder) -> {
            for (Map.Entry<String, Duration> entry : RedisCacheName.getCacheMap().entrySet()) {
                builder.withCacheConfiguration(entry.getKey(),
                        RedisCacheConfiguration.defaultCacheConfig().entryTtl(entry.getValue()));
            }
        };
    }
 
    public static class RedisCacheName { 
        public static final String CACHE_10MIN = "CACHE_10MIN"; 
        @Getter
        private static final Map<String, Duration> cacheMap; 
        static {
            cacheMap = ImmutableMap.<String, Duration>builder().put(CACHE_10MIN, Duration.ofSeconds(10L)).build();
        } 
    } 
 
}

老版本配置

interface CacheNames{
    String CACHE_15MINS = "sssss:cache:15m";
        /** 30分鐘緩存組 */
    String CACHE_30MINS = "sssss:cache:30m";
        /** 60分鐘緩存組 */
    String CACHE_60MINS = "sssss:cache:60m";
        /** 180分鐘緩存組 */
    String CACHE_180MINS = "sssss:cache:180m";
}
 
@Component
 public class RedisCacheCustomizer
            implements CacheManagerCustomizer<RedisCacheManager> {
        /** CacheManager緩存自定義初始化比較早，盡量不要@autowired 其他spring 組件 */
        @Override
        public void customize(RedisCacheManager cacheManager) {
            // 自定義緩存名對應的過期時間
            Map<String, Long> expires = ImmutableMap.<String, Long>builder()
                    .put(CacheNames.CACHE_15MINS, TimeUnit.MINUTES.toSeconds(15))
                    .put(CacheNames.CACHE_30MINS, TimeUnit.MINUTES.toSeconds(30))
                    .put(CacheNames.CACHE_60MINS, TimeUnit.MINUTES.toSeconds(60))
                    .put(CacheNames.CACHE_180MINS, TimeUnit.MINUTES.toSeconds(180)).build();
            // spring cache是根據(jù)cache name查找緩存過期時長的，如果找不到，則使用默認值
            cacheManager.setDefaultExpiration(TimeUnit.MINUTES.toSeconds(30));
            cacheManager.setExpires(expires);
        }
    } 
 
  @Cacheable(key = "key", cacheNames = CacheNames.CACHE_15MINS)
    public String demo2(String key) {
        return "abc" + key;
  }

@Cacheable緩存失效時間策略默認實現(xiàn)及擴展

之前對Spring緩存的理解是每次設置緩存之后，重復請求會刷新緩存時間，但是問題排查閱讀源碼發(fā)現(xiàn)，跟自己的理解大相徑庭。所有的你以為都僅僅是你以為?。。?！

背景

目前項目使用的spring緩存，主要是CacheManager、Cache以及@Cacheable注解，Spring現(xiàn)有的緩存注解無法單獨設置每一個注解的失效時間，Spring官方給的解釋：Spring Cache是一個抽象而不是一個緩存實現(xiàn)方案。

因此對于緩存失效時間（TTL）的策略依賴于底層緩存中間件，官方給舉例：ConcurrentMap是不支持失效時間的，而Redis是支持失效時間的。

Spring Cache Redis實現(xiàn)

Spring緩存注解@Cacheable底層的CacheManager與Cache如果使用Redis方案的話，首次設置緩存數(shù)據(jù)之后，每次重復請求相同方法讀取緩存并不會刷新失效時間，這是Spring的默認行為（受一些緩存影響，一直以為每次讀緩存也會刷新緩存失效時間）。

可以參見源碼：

org.springframework.cache.interceptor.CacheAspectSupport#execute(org.springframework.cache.interceptor.CacheOperationInvoker, java.lang.reflect.Method, org.springframework.cache.interceptor.CacheAspectSupport.CacheOperationContexts)

private Object execute(final CacheOperationInvoker invoker, Method method, CacheOperationContexts contexts) {
		// Special handling of synchronized invocation
		if (contexts.isSynchronized()) {
			CacheOperationContext context = contexts.get(CacheableOperation.class).iterator().next();
			if (isConditionPassing(context, CacheOperationExpressionEvaluator.NO_RESULT)) {
				Object key = generateKey(context, CacheOperationExpressionEvaluator.NO_RESULT);
				Cache cache = context.getCaches().iterator().next();
				try {
					return wrapCacheValue(method, cache.get(key, () -> unwrapReturnValue(invokeOperation(invoker))));
				}
				catch (Cache.ValueRetrievalException ex) {
					// The invoker wraps any Throwable in a ThrowableWrapper instance so we
					// can just make sure that one bubbles up the stack.
					throw (CacheOperationInvoker.ThrowableWrapper) ex.getCause();
				}
			}
			else {
				// No caching required, only call the underlying method
				return invokeOperation(invoker);
			}
		} 
 
		// Process any early evictions
		processCacheEvicts(contexts.get(CacheEvictOperation.class), true,
				CacheOperationExpressionEvaluator.NO_RESULT);
 
		// Check if we have a cached item matching the conditions
		Cache.ValueWrapper cacheHit = findCachedItem(contexts.get(CacheableOperation.class));
 
		// Collect puts from any @Cacheable miss, if no cached item is found
		List<CachePutRequest> cachePutRequests = new LinkedList<>();
		if (cacheHit == null) {
			collectPutRequests(contexts.get(CacheableOperation.class),
					CacheOperationExpressionEvaluator.NO_RESULT, cachePutRequests);
		} 
		Object cacheValue;
		Object returnValue;
 
		if (cacheHit != null && !hasCachePut(contexts)) {
			// If there are no put requests, just use the cache hit
			cacheValue = cacheHit.get();
			returnValue = wrapCacheValue(method, cacheValue);
		}
		else {
			// Invoke the method if we don't have a cache hit
			returnValue = invokeOperation(invoker);
			cacheValue = unwrapReturnValue(returnValue);
		}
 
		// Collect any explicit @CachePuts
		collectPutRequests(contexts.get(CachePutOperation.class), cacheValue, cachePutRequests);
 
		// Process any collected put requests, either from @CachePut or a @Cacheable miss
		for (CachePutRequest cachePutRequest : cachePutRequests) {
			cachePutRequest.apply(cacheValue);
		}
 
		// Process any late evictions
		processCacheEvicts(contexts.get(CacheEvictOperation.class), false, cacheValue); 
		return returnValue;
	}

因此如果我們需要自行控制緩存失效策略，就可能需要一些開發(fā)工作，具體如下。