A Performance Evaluation of Online Warehouse Update Algorithms
A Performance Evaluation of Online Warehouse Update Algorithms
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Date
1998-11-18
Authors
Labrinidis, Alexandros
Roussopoulos, Nick
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Abstract
Data warehouse maintenance algorithms usually work off-line, making
the warehouse unavailable to users. However, since most organizations
require continuous operation, we need be able to perform the updates
online, concurrently with user queries. To guarantee that user queries
access a consistent view of the warehouse, online update algorithms
introduce redundancy in order to store multiple versions of the data
objects that are being changed. In this paper, we present an online
warehouse update algorithm, that stores multiple versions of data as
separate rows (vertical redundancy). We compare our algorithm to
another online algorithm that stores multiple versions within each
tuple by extending the table schema (horizontal redundancy). We have
implemented both algorithms on top of an Informix Dynamic Server and
measured their performance under varying workloads, focusing on their
impact on query response times. Our experiments show that, except for
a limited number of cases, vertical redundancy is a better choice,
with respect to storage, implementation overhead, and query
performance.
(Also cross-referenced as UMIACS TR-98-66)