面向单记录的混合负载下物化视图异步增量维护任务生成

针对已有的混合负载（HTAP）下物化视图异步增量维护任务生成算法主要面向多记录，无法面向单记录生成HTAP物化视图异步增量维护任务，导致磁盘IO开销的增加，进而降低HTAP物化视图异步增量维护性能的问题，提出面向单记录的HTAP物化视图异步增量维护任务的生成方法。首先，建立面向单记录的HTAP物化视图异步增量维护任务生成的效益模型；然后，基于Q-learning设计面向单记录的HTAP物化视图异步增量维护任务的生成算法。实验结果表明，所提算法在实现面向单记录生成HTAP物化视图异步增量维护任务的基础上，将平均每秒读写操作次数（IOPS）、平均CPU利用率（2核）和平均CPU利用率（4核）至少分别降低了8.49次、1.85个百分点和0.97个百分点。

Materialized view asynchronous incremental maintenance task generation under hybrid transaction/analytical processing for single record

Existing materialized view asynchronous incremental maintenance task generation algorithms under Hybrid Transaction/Analytical Processing （HTAP） are mainly used for multiple records and unable to generate materialized view asynchronous incremental maintenance task under HTAP for single record， which results in the increase of disk IO overhead and the performance degradation of materialized view asynchronous incremental maintenance under HTAP. Therefore， a materialized view asynchronous incremental maintenance task generation method under HTAP for single record was proposed. Firstly， the benefit model of materialized view asynchronous incremental maintenance task generation under HTAP for single record was established. Then， the materialized view asynchronous incremental maintenance task generation under HTAP for single record algorithm was designed on the basis of Q-learning. Experimental results show that materialized view asynchronous incremental maintenance task generation under HTAP for single record is realized by the proposed algorithm， and the proposed algorithm decreases the average IOPS （Input/output Operations Per Second）， average CPU utilization （2-core） and average CPU utilization （4-core） at least by 8.49 times， 1.85 percentage points and 0.97 percentage points respectively.