2023年Q2用戶偏好榜：12+256G版本成新主流
3月份的性能榜、性價比榜和好評榜之后，就要輪到2023年的第二季度偏好榜了，上半年的新機潮已經過去，最明顯的肯定就是大內存和存儲的機型了，另外部分中端機也取消了屏幕塑料支架
Caffeine緩存是一個高性能、可擴展、內存優化的 Java 緩存庫，基于 Google 的 Guava Cache演進而來并提供了接近最佳的命中率。
Caffeine 緩存包含以下特點：
正是因為Caffeine具備的上述特性，Caffeine作為項目中本地緩存的不二選擇，越來越多的項目集成了Caffeine的功能，進而衍生了一系列的業務視角的需求。
日常使用的需求之一希望能夠實時評估Caffeine實例的內存占用情況并能夠提供動態調整緩存參數的能力，但是已有的內存分析工具MAT需要基于dump的文件進行分析無法做到實時，這也是整個事情的起因之一。
基于上述的需求背景，結合caffeine的已有功能和定制的部分源碼開發，整體作為caffeine可視化的技術項目進行推進和落地。
Caffeine可視化項目目前已支持功能包括：
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Caffeine框架功能整合
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Caffeine可視化框架
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業務層-緩存對象的管理
static Cache<String, List<String>> accountWhiteCache = Caffeine.newBuilder() .expireAfterWrite(VivoConfigManager.getInteger("trade.account.white.list.cache.ttl", 10), TimeUnit.MINUTES) .recordStats().maximumSize(VivoConfigManager.getInteger("trade.account.white.list.cache.size", 100)).build();常規的Caffeine實例的創建方式 static Cache<String, List<String>> accountWhiteCache = Caffeine.newBuilder().applyName("accountWhiteCache") .expireAfterWrite(VivoConfigManager.getInteger("trade.account.white.list.cache.ttl", 10), TimeUnit.MINUTES) .recordStats().maximumSize(VivoConfigManager.getInteger("trade.account.white.list.cache.size", 100)).build();支持實例命名的Caffeine實例的創建方式說明：
public final class Caffeine<K, V> { /** * caffeine的實例名稱 */ String instanceName; /** * caffeine的實例維護的Map信息 */ static Map<String, Cache> cacheInstanceMap = new ConcurrentHashMap<>(); @NonNull public <K1 extends K, V1 extends V> Cache<K1, V1> build() { requireWeightWithWeigher(); requireNonLoadingCache(); @SuppressWarnings("unchecked") Caffeine<K1, V1> self = (Caffeine<K1, V1>) this; Cache localCache = isBounded() ? new BoundedLocalCache.BoundedLocalManualCache<>(self) : new UnboundedLocalCache.UnboundedLocalManualCache<>(self); if (null != localCache && StringUtils.isNotEmpty(localCache.getInstanceName())) { cacheInstanceMap.put(localCache.getInstanceName(), localCache); } return localCache; }}說明：
業務層-內存占用的預估
import jdk.nashorn.internal.ir.debug.ObjectSizeCalculator; public abstract class BoundedLocalCache<K, V> extends BLCHeader.DrainStatusRef<K, V> implements LocalCache<K, V> { final ConcurrentHashMap<Object, Node<K, V>> data; @Override public long getMemoryUsed() { // 預估內存占用 return ObjectSizeCalculator.getObjectSize(data); }}說明：
業務層-數據上報機制
public static StatsData getCacheStats(String instanceName) { Cache cache = Caffeine.getCacheByInstanceName(instanceName); CacheStats cacheStats = cache.stats(); StatsData statsData = new StatsData(); statsData.setInstanceName(instanceName); statsData.setTimeStamp(System.currentTimeMillis()/1000); statsData.setMemoryUsed(String.valueOf(cache.getMemoryUsed())); statsData.setEstimatedSize(String.valueOf(cache.estimatedSize())); statsData.setRequestCount(String.valueOf(cacheStats.requestCount())); statsData.setHitCount(String.valueOf(cacheStats.hitCount())); statsData.setHitRate(String.valueOf(cacheStats.hitRate())); statsData.setMissCount(String.valueOf(cacheStats.missCount())); statsData.setMissRate(String.valueOf(cacheStats.missRate())); statsData.setLoadCount(String.valueOf(cacheStats.loadCount())); statsData.setLoadSuccessCount(String.valueOf(cacheStats.loadSuccessCount())); statsData.setLoadFailureCount(String.valueOf(cacheStats.loadFailureCount())); statsData.setLoadFailureRate(String.valueOf(cacheStats.loadFailureRate())); Optional<Eviction> optionalEviction = cache.policy().eviction(); optionalEviction.ifPresent(eviction -> statsData.setMaximumSize(String.valueOf(eviction.getMaximum()))); Optional<Expiration> optionalExpiration = cache.policy().expireAfterWrite(); optionalExpiration.ifPresent(expiration -> statsData.setExpireAfterWrite(String.valueOf(expiration.getExpiresAfter(TimeUnit.SECONDS)))); optionalExpiration = cache.policy().expireAfterAccess(); optionalExpiration.ifPresent(expiration -> statsData.setExpireAfterAccess(String.valueOf(expiration.getExpiresAfter(TimeUnit.SECONDS)))); optionalExpiration = cache.policy().refreshAfterWrite(); optionalExpiration.ifPresent(expiration -> statsData.setRefreshAfterWrite(String.valueOf(expiration.getExpiresAfter(TimeUnit.SECONDS)))); return statsData;}說明：
public static void sendReportData() { try { if (!VivoConfigManager.getBoolean("memory.caffeine.data.report.switch", true)) { return; } // 1、獲取所有的cache實例對象 Method listCacheInstanceMethod = HANDLER_MANAGER_CLASS.getMethod("listCacheInstance", null); List<String> instanceNames = (List)listCacheInstanceMethod.invoke(null, null); if (CollectionUtils.isEmpty(instanceNames)) { return; } String appName = System.getProperty("app.name"); String localIp = getLocalIp(); String localPort = String.valueOf(NetPortUtils.getWorkPort()); ReportData reportData = new ReportData(); InstanceData instanceData = new InstanceData(); instanceData.setAppName(appName); instanceData.setIp(localIp); instanceData.setPort(localPort); // 2、遍歷cache實例對象獲取緩存監控數據 Method getCacheStatsMethod = HANDLER_MANAGER_CLASS.getMethod("getCacheStats", String.class); Map<String, StatsData> statsDataMap = new HashMap<>(); instanceNames.stream().forEach(instanceName -> { try { StatsData statsData = (StatsData)getCacheStatsMethod.invoke(null, instanceName); statsDataMap.put(instanceName, statsData); } catch (Exception e) { } }); // 3、構建上報對象 reportData.setInstanceData(instanceData); reportData.setStatsDataMap(statsDataMap); // 4、發送Http的POST請求 HttpPost httpPost = new HttpPost(getReportDataUrl()); httpPost.setConfig(requestConfig); StringEntity stringEntity = new StringEntity(JSON.toJSONString(reportData)); stringEntity.setContentType("application/json"); httpPost.setEntity(stringEntity); HttpResponse response = httpClient.execute(httpPost); String result = EntityUtils.toString(response.getEntity(),"UTF-8"); EntityUtils.consume(response.getEntity()); logger.info("Caffeine 數據上報成功 URL {} 參數 {} 結果 {}", getReportDataUrl(), JSON.toJSONString(reportData), result); } catch (Throwable throwable) { logger.error("Caffeine 數據上報失敗 URL {} ", getReportDataUrl(), throwable); }}說明：
業務層-配置動態下發
public static ExecutionResponse dispose(ExecutionRequest request) { ExecutionResponse executionResponse = new ExecutionResponse(); executionResponse.setCmdType(CmdTypeEnum.INSTANCE_CONFIGURE.getCmd()); executionResponse.setInstanceName(request.getInstanceName()); String instanceName = request.getInstanceName(); Cache cache = Caffeine.getCacheByInstanceName(instanceName); // 設置緩存的最大條目 if (null != request.getMaximumSize() && request.getMaximumSize() > 0) { Optional<Eviction> optionalEviction = cache.policy().eviction(); optionalEviction.ifPresent(eviction ->eviction.setMaximum(request.getMaximumSize())); } // 設置寫后過期的過期時間 if (null != request.getExpireAfterWrite() && request.getExpireAfterWrite() > 0) { Optional<Expiration> optionalExpiration = cache.policy().expireAfterWrite(); optionalExpiration.ifPresent(expiration -> expiration.setExpiresAfter(request.getExpireAfterWrite(), TimeUnit.SECONDS)); } // 設置訪問過期的過期時間 if (null != request.getExpireAfterAccess() && request.getExpireAfterAccess() > 0) { Optional<Expiration> optionalExpiration = cache.policy().expireAfterAccess(); optionalExpiration.ifPresent(expiration -> expiration.setExpiresAfter(request.getExpireAfterAccess(), TimeUnit.SECONDS)); } // 設置寫更新的過期時間 if (null != request.getRefreshAfterWrite() && request.getRefreshAfterWrite() > 0) { Optional<Expiration> optionalExpiration = cache.policy().refreshAfterWrite(); optionalExpiration.ifPresent(expiration -> expiration.setExpiresAfter(request.getRefreshAfterWrite(), TimeUnit.SECONDS)); } executionResponse.setCode(0); executionResponse.setMsg("success"); return executionResponse;}說明：
業務層-緩存數據清空
/** * 失效緩存的值 * @param request * @return */ public static ExecutionResponse invalidate(ExecutionRequest request) { ExecutionResponse executionResponse = new ExecutionResponse(); executionResponse.setCmdType(CmdTypeEnum.INSTANCE_INVALIDATE.getCmd()); executionResponse.setInstanceName(request.getInstanceName()); try { // 查找對應的cache實例 String instanceName = request.getInstanceName(); Cache cache = Caffeine.getCacheByInstanceName(instanceName); // 處理清空指定實例的所有緩存 或 指定實例的key對應的緩存 Object cacheKeyObj = request.getCacheKey(); // 清除所有緩存 if (Objects.isNull(cacheKeyObj)) { cache.invalidateAll(); } else { // 清除指定key對應的緩存 if (Objects.equals(request.getCacheKeyType(), 2)) { cache.invalidate(Long.valueOf(request.getCacheKey().toString())); } else if (Objects.equals(request.getCacheKeyType(), 3)) { cache.invalidate(Integer.valueOf(request.getCacheKey().toString())); } else { cache.invalidate(request.getCacheKey().toString()); } } executionResponse.setCode(0); executionResponse.setMsg("success"); } catch (Exception e) { executionResponse.setCode(-1); executionResponse.setMsg("fail"); } return executionResponse; }}業務層-緩存數據查詢
public static ExecutionResponse inspect(ExecutionRequest request) { ExecutionResponse executionResponse = new ExecutionResponse(); executionResponse.setCmdType(CmdTypeEnum.INSTANCE_INSPECT.getCmd()); executionResponse.setInstanceName(request.getInstanceName()); String instanceName = request.getInstanceName(); Cache cache = Caffeine.getCacheByInstanceName(instanceName); Object cacheValue = cache.getIfPresent(request.getCacheKey()); if (Objects.equals(request.getCacheKeyType(), 2)) { cacheValue = cache.getIfPresent(Long.valueOf(request.getCacheKey().toString())); } else if (Objects.equals(request.getCacheKeyType(), 3)) { cacheValue = cache.getIfPresent(Integer.valueOf(request.getCacheKey().toString())); } else { cacheValue = cache.getIfPresent(request.getCacheKey().toString()); } if (Objects.isNull(cacheValue)) { executionResponse.setData(""); } else { executionResponse.setData(JSON.toJSONString(cacheValue)); } return executionResponse;}說明：
通信層-監聽服務
public class ServerManager { private Server jetty; /** * 創建jetty對象 * @throws Exception */ public ServerManager() throws Exception { int port = NetPortUtils.getAvailablePort(); jetty = new Server(port); ServletContextHandler context = new ServletContextHandler(ServletContextHandler.NO_SESSIONS); context.setContextPath("/"); context.addServlet(ClientServlet.class, "/caffeine"); jetty.setHandler(context); } /** * 啟動jetty對象 * @throws Exception */ public void start() throws Exception { jetty.start(); }} public class ClientServlet extends HttpServlet { private static final Logger logger = LoggerFactory.getLogger(ClientServlet.class); @Override protected void doGet(HttpServletRequest req, HttpServletResponse resp) throws ServletException, IOException { super.doGet(req, resp); } @Override protected void doPost(HttpServletRequest req, HttpServletResponse resp) throws ServletException, IOException { ExecutionResponse executionResponse = null; String requestJson = null; try { // 獲取請求的相關的參數 String contextPath = req.getContextPath(); String servletPath = req.getServletPath(); String requestUri = req.getRequestURI(); requestJson = IOUtils.toString(req.getInputStream(), StandardCharsets.UTF_8); // 處理不同的命令 ExecutionRequest executionRequest = JSON.parseObject(requestJson, ExecutionRequest.class); // 通過反射來來處理類依賴問題 executionResponse = DisposeCenter.dispatch(executionRequest); } catch (Exception e) { logger.error("vivo-memory 處理請求異常 {} ", requestJson, e); } if (null == executionResponse) { executionResponse = new ExecutionResponse(); executionResponse.setCode(-1); executionResponse.setMsg("處理異常"); } // 組裝相應報文 resp.setContentType("application/json; charset=utf-8"); PrintWriter out = resp.getWriter(); out.println(JSON.toJSONString(executionResponse)); out.flush(); }}說明：
通信層-心跳設計
/** * 發送心跳數據 */public static void sendHeartBeatData() { try { if (!VivoConfigManager.getBoolean("memory.caffeine.heart.report.switch", true)) { return; } // 1、構建心跳數據 String appName = System.getProperty("app.name"); String localIp = getLocalIp(); String localPort = String.valueOf(NetPortUtils.getWorkPort()); HeartBeatData heartBeatData = new HeartBeatData(); heartBeatData.setAppName(appName); heartBeatData.setIp(localIp); heartBeatData.setPort(localPort); heartBeatData.setTimeStamp(System.currentTimeMillis()/1000); // 2、發送Http的POST請求 HttpPost httpPost = new HttpPost(getHeartBeatUrl()); httpPost.setConfig(requestConfig); StringEntity stringEntity = new StringEntity(JSON.toJSONString(heartBeatData)); stringEntity.setContentType("application/json"); httpPost.setEntity(stringEntity); HttpResponse response = httpClient.execute(httpPost); String result = EntityUtils.toString(response.getEntity(),"UTF-8"); EntityUtils.consume(response.getEntity()); logger.info("Caffeine 心跳上報成功 URL {} 參數 {} 結果 {}", getHeartBeatUrl(), JSON.toJSONString(heartBeatData), result); } catch (Throwable throwable) { logger.error("Caffeine 心跳上報失敗 URL {} ", getHeartBeatUrl(), throwable); }}說明：
vivo技術團隊在Caffeine的使用經驗上曾有過多次分享，可參考公眾號文章《如何把 Caffeine Cache 用得如絲般順滑》，此篇文章在使用的基礎上基于使用痛點進行進一步的定制。
目前Caffeine可視化的項目已經在相關核心業務場景中落地并發揮作用，整體運行平穩。使用較多的功能包括項目維度的caffeine實例的全局管控，單實例維度的內存占用評估和緩存命中趨勢評估。
如通過單實例的內存占用評估功能能夠合理評估緩存條目設置和內存占用之間的關系；通過分析緩存命中率的整體趨勢評估緩存的參數設置合理性。
期待此篇文章能夠給業界緩存使用和監控帶來一些新思路。
本文鏈接：http://m.www897cc.com/showinfo-26-103570-0.html緩存框架 Caffeine 的可視化探索與實踐
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