HCache: A Hash-based Hybrid Caching Model for Real-Time Streaming Data Analytics
HCache: A Hash-based Hybrid Caching Model for Real-Time Streaming Data Analytics
复制标题
HCache：用于实时流数据分析的基于哈希的混合缓存模型
DOI：
10.1109/tsc.2018.2874966
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Laurence T. Yang
中科院分区：
文献类型：
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作者：
Feng Zhao;Shaofeng Li;Bing Bing Zhou;Hai Jin;Laurence T. Yang
数据流分析中的最新结果很难获得，因为数据是快速顺序的，只能访问一次。由于流数据的确切交付性质，在线处理非常不稳定。保证理解
Up-to-date results in data stream analytics are difficult to obtain because the data are in rapid sequence and can be accessed only once. Due to the exactly-once delivery nature of streaming data, online processing is quite unstable. To guarantee comprehensive and accurate results, aggregating historical data is essential when processing streaming data. In this paper, we propose a hash-based hybrid cache model, namely, HCache, for fast data analytics covering real-time streaming data and historical data. The HCache model integrates the online cache and batch cache for hybrid online and batch processing and uses a hash structure to accelerate storage. When executing analytic tasks, the batch cache and online cache are accessed in parallel. Computed streaming data are stored in the online cache, which returns qualified results based on one-time visiting. The most recently visited historical data are stored in the batch cache, and they are also used to correct errors in the online cache. Efficient replacement strategies are used to keep the caches within a relatively stable size. To coordinate the online cache with the batch cache, an LRU-based selection strategy is designed to achieve comprehensive results. Experimental results show that the HCache model can quickly and efficiently execute analytic tasks with little additional overhead; moreover HCache is more stable and effective at data storage, access and query with less memory utilization than other models.