基于Spring Cache实现Caffeine、jimDB多级缓存实战

作者: 京东零售 王震

背景

在早期参与涅槃氛围标签中台项目中,前台要求接口性能999要求50ms以下,通过设计Caffeine、ehcache堆外缓存、jimDB三级缓存,利用内存、堆外、jimDB缓存不同的特性提升接口性能, 内存缓存采用Caffeine缓存,利用W-TinyLFU算法获得更高的内存命中率;同时利用堆外缓存降低内存缓存大小,减少GC频率,同时也减少了网络IO带来的性能消耗;利用JimDB提升接口高可用、高并发;后期通过压测及性能调优999性能<20ms
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当时由于项目工期紧张,三级缓存实现较为臃肿、业务侵入性强、可读性差,在近期场景化推荐项目中,为B端商家场景化资源投放推荐,考虑到B端流量相对C端流量较小,但需保证接口性能稳定。采用SpringCache实现caffeine、jimDB多级缓存方案,实现了低侵入性、可扩展、高可用的缓存方案,极大提升了系统稳定性,保证接口性能小于100ms;

Spring Cache实现多级缓存

多级缓存实例MultilevelCache

/**
 * 分级缓存
 * 基于Caffeine + jimDB 实现二级缓存
 * @author wangzhen520
 * @date 2022/12/9
 */
public class MultilevelCache extends AbstractValueAdaptingCache {

    /**
     * 缓存名称
     */
    private String name;

    /**
     * 是否开启一级缓存
     */
    private boolean enableFirstCache = true;

    /**
     * 一级缓存
     */
    private Cache firstCache;

    /**
     * 二级缓存
     */
    private Cache secondCache;

    @Override
    protected Object lookup(Object key) {
        Object value;
        recordCount(getUmpKey(this.getName(), UMP_GET_CACHE, UMP_ALL));
        if(enableFirstCache){
            //查询一级缓存
            value = getWrapperValue(getForFirstCache(key));
            log.info("{}#lookup getForFirstCache key={} value={}", this.getClass().getSimpleName(), key, value);
            if(value != null){
                return value;
            }
        }
        value = getWrapperValue(getForSecondCache(key));
        log.info("{}#lookup getForSecondCache key={} value={}", this.getClass().getSimpleName(), key, value);
        //二级缓存不为空,则更新一级缓存
        boolean putFirstCache = (Objects.nonNull(value) || isAllowNullValues()) && enableFirstCache;
        if(putFirstCache){
            recordCount(getUmpKey(this.getName(), UMP_FIRST_CACHE, UMP_NO_HIT));
            log.info("{}#lookup put firstCache key={} value={}", this.getClass().getSimpleName(), key, value);
            firstCache.put(key, value);
        }
        return value;
    }
    

    @Override
    public void put(Object key, Object value) {
        if(enableFirstCache){
            checkFirstCache();
            firstCache.put(key, value);
        }
        secondCache.put(key, value);
    }

    /**
     * 查询一级缓存
     * @param key
     * @return
     */
    private ValueWrapper getForFirstCache(Object key){
        checkFirstCache();
        ValueWrapper valueWrapper = firstCache.get(key);
        if(valueWrapper == null || Objects.isNull(valueWrapper.get())){
            recordCount(getUmpKey(this.getName(), UMP_FIRST_CACHE, UMP_NO_HIT));
        }
        return valueWrapper;
    }

    /**
     * 查询二级缓存
     * @param key
     * @return
     */
    private ValueWrapper getForSecondCache(Object key){
        ValueWrapper valueWrapper = secondCache.get(key);
        if(valueWrapper == null || Objects.isNull(valueWrapper.get())){
            recordCount(getUmpKey(this.getName(), UMP_SECOND_CACHE, UMP_NO_HIT));
        }
        return valueWrapper;
    }

    private Object getWrapperValue(ValueWrapper valueWrapper){
        return Optional.ofNullable(valueWrapper).map(ValueWrapper::get).orElse(null);
    }

}

多级缓存管理器抽象

/**
 * 多级缓存实现抽象类
 * 一级缓存
 * @see AbstractMultilevelCacheManager#getFirstCache(String)
 * 二级缓存
 * @see AbstractMultilevelCacheManager#getSecondCache(String)
 * @author wangzhen520
 * @date 2022/12/9
 */
public abstract class AbstractMultilevelCacheManager implements CacheManager {

    private final ConcurrentMap cacheMap = new ConcurrentHashMap<>(16);

    /**
     * 是否动态生成
     * @see MultilevelCache
     */
    protected boolean dynamic = true;
    /**
     * 默认开启一级缓存
     */
    protected boolean enableFirstCache = true;
    /**
     * 是否允许空值
     */
    protected boolean allowNullValues = true;

    /**
     * ump监控前缀 不设置不开启监控
     */
    private String umpKeyPrefix;


    protected MultilevelCache createMultilevelCache(String name) {
        Assert.hasLength(name, "createMultilevelCache name is not null");
        MultilevelCache multilevelCache = new MultilevelCache(allowNullValues);
        multilevelCache.setName(name);
        multilevelCache.setUmpKeyPrefix(this.umpKeyPrefix);
        multilevelCache.setEnableFirstCache(this.enableFirstCache);
        multilevelCache.setFirstCache(getFirstCache(name));
        multilevelCache.setSecondCache(getSecondCache(name));
        return multilevelCache;
    }


    @Override
    public Cache getCache(String name) {
        MultilevelCache cache = this.cacheMap.get(name);
        if (cache == null && dynamic) {
            synchronized (this.cacheMap) {
                cache = this.cacheMap.get(name);
                if (cache == null) {
                    cache = createMultilevelCache(name);
                    this.cacheMap.put(name, cache);
                }
                return cache;
            }
      }
      return cache;
    }

    @Override
    public Collection getCacheNames() {
        return Collections.unmodifiableSet(this.cacheMap.keySet());
    }

    /**
     * 一级缓存
     * @param name
     * @return
     */
    protected abstract Cache getFirstCache(String name);

    /**
     * 二级缓存
     * @param name
     * @return
     */
    protected abstract Cache getSecondCache(String name);

    public boolean isDynamic() {
        return dynamic;
    }

    public void setDynamic(boolean dynamic) {
        this.dynamic = dynamic;
    }

    public boolean isEnableFirstCache() {
        return enableFirstCache;
    }

    public void setEnableFirstCache(boolean enableFirstCache) {
        this.enableFirstCache = enableFirstCache;
    }

    public String getUmpKeyPrefix() {
        return umpKeyPrefix;
    }

    public void setUmpKeyPrefix(String umpKeyPrefix) {
        this.umpKeyPrefix = umpKeyPrefix;
    }
}

基于jimDB Caffiene缓存实现多级缓存管理器


/**
 * 二级缓存实现
 * caffeine + jimDB 二级缓存
 * @author wangzhen520
 * @date 2022/12/9
 */
public class CaffeineJimMultilevelCacheManager extends AbstractMultilevelCacheManager {

    private CaffeineCacheManager caffeineCacheManager;

    private JimCacheManager jimCacheManager;

    public CaffeineJimMultilevelCacheManager(CaffeineCacheManager caffeineCacheManager, JimCacheManager jimCacheManager) {
        this.caffeineCacheManager = caffeineCacheManager;
        this.jimCacheManager = jimCacheManager;
        caffeineCacheManager.setAllowNullValues(this.allowNullValues);
    }

    /**
     * 一级缓存实现
     * 基于caffeine实现
     * @see org.springframework.cache.caffeine.CaffeineCache
     * @param name
     * @return
     */
    @Override
    protected Cache getFirstCache(String name) {
        if(!isEnableFirstCache()){
            return null;
        }
        return caffeineCacheManager.getCache(name);
    }

    /**
     * 二级缓存基于jimDB实现
     * @see com.jd.jim.cli.springcache.JimStringCache
     * @param name
     * @return
     */
    @Override
    protected Cache getSecondCache(String name) {
        return jimCacheManager.getCache(name);
    }
}

缓存配置

/**
 * @author wangzhen520
 * @date 2022/12/9
 */
@Configuration
@EnableCaching
public class CacheConfiguration {

    /**
     * 基于caffeine + JimDB 多级缓存Manager
     * @param firstCacheManager
     * @param secondCacheManager
     * @return
     */
    @Primary
    @Bean(name = "caffeineJimCacheManager")
    public CacheManager multilevelCacheManager(@Param("firstCacheManager") CaffeineCacheManager firstCacheManager,
                                               @Param("secondCacheManager") JimCacheManager secondCacheManager){
        CaffeineJimMultilevelCacheManager cacheManager = new CaffeineJimMultilevelCacheManager(firstCacheManager, secondCacheManager);
        cacheManager.setUmpKeyPrefix(String.format("%s.%s", UmpConstants.Key.PREFIX, UmpConstants.SYSTEM_NAME));
        cacheManager.setEnableFirstCache(true);
        cacheManager.setDynamic(true);
        return cacheManager;
    }

    /**
     * 一级缓存Manager
     * @return
     */
    @Bean(name = "firstCacheManager")
    public CaffeineCacheManager firstCacheManager(){
        CaffeineCacheManager firstCacheManager = new CaffeineCacheManager();
        firstCacheManager.setCaffeine(Caffeine.newBuilder()
                .initialCapacity(firstCacheInitialCapacity)
                .maximumSize(firstCacheMaximumSize)
                .expireAfterWrite(Duration.ofSeconds(firstCacheDurationSeconds)));
        firstCacheManager.setAllowNullValues(true);
        return firstCacheManager;
    }

    /**
     * 初始化二级缓存Manager
     * @param jimClientLF
     * @return
     */
    @Bean(name = "secondCacheManager")
    public JimCacheManager secondCacheManager(@Param("jimClientLF") Cluster jimClientLF){
        JimDbCache jimDbCache = new JimDbCache<>();
        jimDbCache.setJimClient(jimClientLF);
        jimDbCache.setKeyPrefix(MultilevelCacheConstants.SERVICE_RULE_MATCH_CACHE);
        jimDbCache.setEntryTimeout(secondCacheExpireSeconds);
        jimDbCache.setValueSerializer(new JsonStringSerializer(ServiceRuleMatchResult.class));
        JimCacheManager secondCacheManager = new JimCacheManager();
        secondCacheManager.setCaches(Arrays.asList(jimDbCache));
        return secondCacheManager;
    }

接口性能压测

压测环境

廊坊4C8G * 3

压测结果

1、50并发时,未开启缓存,压测5min,TP99: 67ms,TP999: 223ms,TPS:2072.39笔/秒,此时服务引擎cpu利用率40%左右;订购履约cpu利用率70%左右,磁盘使用率4min后被打满;

2、50并发时,开启二级缓存,压测10min,TP99: 33ms,TP999: 38ms,TPS:28521.18.笔/秒,此时服务引擎cpu利用率90%左右,订购履约cpu利用率10%左右,磁盘使用率3%左右;

缓存命中分析

总调用次数:1840486/min 一级缓存命中:1822820 /min 二级缓存命中:14454/min
一级缓存命中率:99.04%
二级缓存命中率:81.81%

压测数据

未开启缓存

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开启多级缓存

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监控数据

未开启缓存

下游应用由于4分钟后磁盘打满,性能到达瓶颈

接口UMP

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服务引擎系统

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订购履约系统

image.png

开启缓存

上游系统CPU利用率90%左右,下游系统调用量明显减少,CPU利用率仅10%左右

接口UMP

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服务引擎系统

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订购履约系统:

image.png

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