This paper focuses on Real-Time Data Warehousing systems, a relevant class of Data Warehouses where the main requirement consists in executing classical data warehousing operations (e.g., loading, aggregation, indexing, OLAP query answering, and so forth) under real-time constraints. This makes classical DW architectures not suitable to this goal, and puts the basis for a novel research area which has tight relationship with emerging Cloud architectures. Inspired by this motivation, in this paper we proposed a novel framework for supporting Real-Time Data Warehousing which makes use of a rewrite/merge approach. We also provide an extensive experimental campaign that confirms the benefits deriving from our framework.
Real-time data warehousing: A rewrite/merge approach
Cuzzocrea Alfredo;
2014-01-01
Abstract
This paper focuses on Real-Time Data Warehousing systems, a relevant class of Data Warehouses where the main requirement consists in executing classical data warehousing operations (e.g., loading, aggregation, indexing, OLAP query answering, and so forth) under real-time constraints. This makes classical DW architectures not suitable to this goal, and puts the basis for a novel research area which has tight relationship with emerging Cloud architectures. Inspired by this motivation, in this paper we proposed a novel framework for supporting Real-Time Data Warehousing which makes use of a rewrite/merge approach. We also provide an extensive experimental campaign that confirms the benefits deriving from our framework.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
