S. Padmanabhan, Timothy Malkemus, R. Agarwal, A. Jhingran
{"title":"Block oriented processing of relational database operations in modern computer architectures","authors":"S. Padmanabhan, Timothy Malkemus, R. Agarwal, A. Jhingran","doi":"10.1109/ICDE.2001.914871","DOIUrl":null,"url":null,"abstract":"Database systems are not well-tuned to take advantage of modern superscalar processor architectures. In particular, the clocks per instruction (CPI) for rather simple database queries are quite poor compared to scientific kernels or SPEC benchmarks. The lack of performance of database systems has been attributed to poor utilization of caches and processor function units as well as higher branching penalties. In this paper, we argue that a block-oriented processing strategy for database operations can lead to better utilization of the processors and caches, generating significantly higher performance. We have implemented the block-oriented processing technique for aggregation expression evaluation and sorting operations as a feature in the DB2 Universal Database (UDB) system. We present results from representative queries on a 30-GB TPC-H (Transaction Processing Council Benchmark H) database to show the value of this technique.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"101","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 17th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2001.914871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 101
Abstract
Database systems are not well-tuned to take advantage of modern superscalar processor architectures. In particular, the clocks per instruction (CPI) for rather simple database queries are quite poor compared to scientific kernels or SPEC benchmarks. The lack of performance of database systems has been attributed to poor utilization of caches and processor function units as well as higher branching penalties. In this paper, we argue that a block-oriented processing strategy for database operations can lead to better utilization of the processors and caches, generating significantly higher performance. We have implemented the block-oriented processing technique for aggregation expression evaluation and sorting operations as a feature in the DB2 Universal Database (UDB) system. We present results from representative queries on a 30-GB TPC-H (Transaction Processing Council Benchmark H) database to show the value of this technique.