{"title":"A non-blocking parallel spatial join algorithm","authors":"Gang Luo, J. Naughton, Curt J. Ellmann","doi":"10.1109/ICDE.2002.994786","DOIUrl":null,"url":null,"abstract":"Interest in incremental and adaptive query processing has led to the investigation of equijoin evaluation algorithms that are non-blocking. This investigation has yielded a number of algorithms, including the symmetric hash join, the XJoin, the Ripple Join, and their variants. However, to our knowledge no one has proposed a nonblocking spatial join algorithm. In this paper, we propose a parallel non-blocking spatial join algorithm that uses duplicate avoidance rather than duplicate elimination. Results from a prototype implementation in a commercial parallel object-relational DBMS show that it generates answer tuples steadily even in the presence of memory overflow, and that its rate of producing answer tuples scales with the number of processors. Also, when allowed to run to completion, its performance is comparable with the state-of-the-art blocking parallel spatial join algorithm.","PeriodicalId":191529,"journal":{"name":"Proceedings 18th International Conference on Data Engineering","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"58","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 18th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2002.994786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 58
Abstract
Interest in incremental and adaptive query processing has led to the investigation of equijoin evaluation algorithms that are non-blocking. This investigation has yielded a number of algorithms, including the symmetric hash join, the XJoin, the Ripple Join, and their variants. However, to our knowledge no one has proposed a nonblocking spatial join algorithm. In this paper, we propose a parallel non-blocking spatial join algorithm that uses duplicate avoidance rather than duplicate elimination. Results from a prototype implementation in a commercial parallel object-relational DBMS show that it generates answer tuples steadily even in the presence of memory overflow, and that its rate of producing answer tuples scales with the number of processors. Also, when allowed to run to completion, its performance is comparable with the state-of-the-art blocking parallel spatial join algorithm.