基于统计的无阻塞连接算法

数据流上的关系查询处理技术是数据库研究领域的一大热点。优化无阻塞连接算法的关键在于提高内存连接阶段的效率。当内存空间满时，需要将内存数据刷新到外存相应分区，良好的刷新策略对于改进算法的性能至关重要。利用数据分布的特征，对关系连接的输出流，使用基于统计的方法，查找使用频率最低的元组，将使用频率较低的元组刷新到外存，以提高内存数据的效率。基于统计分析策略提高了刷新策略的准确性和效率及算法的适用范围。

Non-blocking Join Algorithm Based on Statistics

Data stream query processing technology becomes a new and popular topic in database research area.The critical of improving non-blocking join algorithm is to improve the efficiency of memory join stage. If there are no more space for the coming tuple, some old tuples have to be flushed from memory to disk. A good refresh strategy is very helpful to increase join algorithm performance. The lowest frequently used tuples are searched from the result streams, then flush such tuples from memory to disk so that the tuples that arc stayed in the memory would generate more results. Statistics join algorithm performance is increased obviously and it expands the adaptability of the data stream relation join algorithm.