论文标题
Palpatine：在NOSQL分布式钥匙值商店中预取数据的频繁序列
Palpatine: Mining Frequent Sequences for Data Prefetching in NoSQL Distributed Key-Value Stores
论文作者
论文摘要
本文介绍了Palpatine，这是第一个用于分布式键值（DKV）数据存储的内存应用程序级缓存，能够预取数据可能在不久的将来访问。为了预测数据访问，Palpatine通过数据挖掘技术不断捕获频繁的访问模式。借助这些模式，帕尔帕廷构建了访问项目的随机图，并根据其做出预取决策。 实验评估表明，帕尔帕廷可以提高特定DKV存储的潜伏期，而更多的数量级。
This paper presents PALPATINE, the first in-memory application-level cache for Distributed Key-Value (DKV) data stores, capable of prefetching data that is likely to be accessed in an immediate future. To predict data accesses, PALPATINE continuously captures frequent access patterns to the back store by means of data mining techniques. With these patterns, PALPATINE builds a stochastic graph of accessed items, and makes prefetching decisions based on it. Experimental evaluation indicates that PALPATINE can improve the latency of a specific DKV store by more that an order of magnitude.
