Amr El-Helw, K. A. Ross, Bishwaranjan Bhattacharjee, Christian A. Lang, G. Mihaila
{"title":"Column-oriented query processing for row stores","authors":"Amr El-Helw, K. A. Ross, Bishwaranjan Bhattacharjee, Christian A. Lang, G. Mihaila","doi":"10.1145/2064676.2064689","DOIUrl":null,"url":null,"abstract":"Column-oriented DBMSs have gained increasing interest due to their superior performance for analytical workloads. Prior efforts tried to determine the possibility of simulating the query processing techniques of column-oriented systems in row-oriented databases, in a hope to improve their performance, especially for OLAP and data warehousing applications. In this paper, we show that column-oriented query processing can significantly improve the performance of row-oriented DBMSs. We introduce new operators that take into account the unique characteristics of data obtained from indexes, and exploit new technologies such as flash SSDs and multi-core processors to boost the performance. We demonstrate our approach with an experimental study using a prototype built on a commercial row-oriented DBMS.","PeriodicalId":335396,"journal":{"name":"International Workshop on Data Warehousing and OLAP","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Data Warehousing and OLAP","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2064676.2064689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Column-oriented DBMSs have gained increasing interest due to their superior performance for analytical workloads. Prior efforts tried to determine the possibility of simulating the query processing techniques of column-oriented systems in row-oriented databases, in a hope to improve their performance, especially for OLAP and data warehousing applications. In this paper, we show that column-oriented query processing can significantly improve the performance of row-oriented DBMSs. We introduce new operators that take into account the unique characteristics of data obtained from indexes, and exploit new technologies such as flash SSDs and multi-core processors to boost the performance. We demonstrate our approach with an experimental study using a prototype built on a commercial row-oriented DBMS.