A Performance Evaluation of Online Warehouse Update Algorithms

Abstract

Data warehouse maintenance algorithms usually work off-line, making the warehouse unavailable tousers. However, since most organizations require continuous operation, we need to be able to performthe updates online, concurrently with user queries. To guarantee that user queries access a consistentview of the warehouse, online update algorithms introduce redundancy in order to store multipleversions of the data objects that are being changed. In this paper, we present an online warehouseupdate algorithm that stores multiple versions of data as separate rows (vertical redundancy). Wecompare our algorithm to another online algorithm that stores multiple versions within each tuple byextending the table schema (horizontal redundancy). We have implemented both algorithms on top ofan Informix Dynamic Server and measured their performance under varying workloads, focusing ontheir impact on query response times. Our experiments show that, except for a limited number ofcases, vertical redundancy is a better choice, with respect to storage, implementation overhead, andquery performance.