云环境下的突发关键字查询算法

Algorithm for Bursty Term Query in Cloud Computing

基于Spark Streaming计算框架下的分布式突发关键字查询是监测流数据中关键字突发时间的热点研究问题。多数研究方法存储统计所有的关键字,并未考虑热点关键字。在数据呈爆炸式增长的背景下,获取热点关键字的突发时间更具有价值。针对这个问题,提出一种分布式突发关键字查询算法,该算法采用动态的更新策略,通过设置检查点的方法提取热点关键字,并在线性的时间内查询突发的时间范围。实验结果表明,该算法的性能比现有算法更优。

Distributed bursty term query under the framework of Spark Streaming is a hot research issue. It aims to de- tect bursty terms in data streams. Most studies of bursty term query count and save all terms without consideration of hot terms. Under the background of exploding in the data scale, it makes more sense to get bursty time of hot terms. To solve this problem, we presented a distributed bursty term query algorithm. The algorithm uses dynamic update strategy and a checkpoint mechanism to extract hot terms. Also it finds the bursty time range in linear time Experimental results show that the proposed algorithm has better performance.