An adaptive strategy for statistics collecting in distributed database  

作　　者：Jintao Gao Wenjie Liu Zhanhuai Li 

机构地区：[1]School of Computer Science,Northwestern Polytechnical University,Xi’an,710072,China

出　　处：《Frontiers of Computer Science》2020年第5期199-211,共13页中国计算机科学前沿（英文版）

基　　金：This project was supported by Key Research and Development Program(2018YFB1003403);the National Natural Science Foundation of China(Grant Nos.61732014,61672432,61672434);Natural Science Basic Research Plan in Shaanxi Province of China(2017JM6104).

摘　　要：Collecting statistics is a time-and resource-consuming operation in database systems.It is even more challenging to efficiently collect statistics without affecting system performance,meanwhile keeping correctness in distributed database.Traditional strategies usually consider one dimension during collecting statistics,which is lack of adaptiveness.In this paper,we propose an adaptive strategy for statistics collecting(ASC),which well balances collecting efficiency,correctness of statistics and effect to system performance.We formally define the procedure of collecting statistics and abstract the relationships among collecting efficiency,correctness of statistics and effect to system performance,and introduce an elastic structure(ESI)storing necessary information generated during proceeding our strategy.ASC can pick appropriate time to trigger collecting action and filter unnecessary tasks,meanwhile reasonably allocating collecting tasks to appropriate executing locations with right executing models through the information stored at ESI.We implement and evaluate our strategy in a distributed database.Experiments show that our solutions generally improve the efficiency and correctness of collecting statistics,moreover,reduce the negative effect to system performance comparing with other strategies.

关 键 词：statistics collecting distributed database adaptive strategy query optimization 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]