An overview of data warehousing and OLAP technology
ACM SIGMOD Record
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
New sampling-based summary statistics for improving approximate query answers
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Approximate computation of multidimensional aggregates of sparse data using wavelets
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Congressional samples for approximate answering of group-by queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Large-Sample and Deterministic Confidence Intervals for Online Aggregation
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Adding a Performance-Oriented Perspective to Data Warehouse Design
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
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This paper presents an approach to implement large data warehouses on an arbitrary number of computers, achieving very high query execution performance and scalability. The data is distributed and processed in a potentially large number of autonomous computers using our technique called data warehouse striping (DWS). The major problem of DWS technique is that it would require a very expensive cluster of computers with fault tolerant capabilities to prevent a fault in a single computer to stop the whole system. In this paper, we propose a radically different approach to deal with the problem of the unavailability of one or more computers in the cluster, allowing the use of DWS with a very large number of inexpensive computers. The proposed approach is based on approximate query answering techniques that make it possible to deliver an approximate answer to the user even when one or more computers in the cluster are not available. The evaluation presented in the paper shows both analytically and experimentally that the approximate results obtained this way have a very small error that can be negligible in most of the cases.