计算机应用与软件2017，Vol.34Issue(7)：66-73,84,9.DOI:10.3969/j.issn.1000-386x.2017.07.014
基于信息网模型的分布并行多连接查询优化
DISTRIBUTED PARALLEL MULTI-JOIN QUERY OPTIMIZATION IN INFORMATION NETWORK MODEL
摘要
Abstract
In the distributed cluster system, data is partitioned in different nodes according to data partition algorithm, which causes expensive network communication expense for the complex multi-join query.To solve the problem, the Minimum Traffic Query Split Algorithm(MTQS) and the Multi-Objective Query Optimization Algorithm (MOQO) based on the Information Network Model are proposed.Among these two algorithms, MTQS is aimed at splitting query into several parallelizable without communication (PWOC) sub-queries, which guarantees every sub-query parallels approximately without communication.MOQO takes sub-query as the basic operation, which puts the parallelism and communication cost as goal driven and builds the query plan tree combining the traditional Multi-Objective weighted algorithm with the greedy algorithm as the assessing accordance.In the end, the system generates test data by TPC-H benchmark and conducts a comparative experiment between the previous and optimal algorithm, the result proves that the optimal algorithm improves the efficiency of complex query significantly.关键词
查询优化/分布并行处理/多连接/信息网模型(INM)Key words
Query optimization/ Distributed parallel processing/ Multi-join Information/ Network Model(INM)分类
信息技术与安全科学引用本文复制引用
徐晶,刘梦赤..基于信息网模型的分布并行多连接查询优化[J].计算机应用与软件,2017,34(7):66-73,84,9.基金项目
国家自然科学基金项目(61672389,61202100) （61672389,61202100）
软件工程国家重点实验室开放基金项目(SKLSE2012-09-20). （SKLSE2012-09-20）
