
doi: 10.1147/sj.332.0349
In order to provide real-time responses to complex queries involving large volumes of data, it has become necessary to exploit parallelism in query processing. This paper addresses the issues and solutions relating to intraquery parallelism in a relational database management system (DBMS). We provide a broad framework for the study of the numerous issues that need to be addressed in supporting parallelism efficiently and flexibly. The alternatives for a parallel architecture system are discussed, followed by the focus on how a query can be parallelized and how that affects load balancing of the different tasks created. The final part of the paper contains information about how the IBM DATABASE 2™ (DB2®) Version 3 product provides support for I/O parallelism to reduce response time for data-intensive queries.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
