Affiliation:
1. Computer Science Department, Stanford University, Stanford, CA
Abstract
A warehouse is a repository of integrated information drawn from remote data sources. Since a warehouse effectively implements materialized views, we must maintain the views as the data sources are updated. This view maintenance problem differs from the traditional one in that the view definition and the base data are now decoupled. We show that this decoupling can result in anomalies if traditional algorithms are applied. We introduce a new algorithm, ECA (for "Eager Compensating Algorithm"), that eliminates the anomalies. ECA is based on previous incremental view maintenance algorithms, but extra "compensating" queries are used to eliminate anomalies. We also introduce two streamlined versions of ECA for special cases of views and updates, and we present an initial performance study that compares ECA to a view recomputation algorithm in terms of messages transmitted, data transferred, and I/O costs.
Publisher
Association for Computing Machinery (ACM)
Subject
Information Systems,Software
Reference18 articles.
1. Overview of multidatabase transaction management
2. Efficiently updating materialized views
3. Ashish Gupta and J. A. Blakeley. Updating materialized views using the view contents and the update. In unpublished document 1994. Ashish Gupta and J. A. Blakeley. Updating materialized views using the view contents and the update. In unpublished document 1994.
4. Maintaining views incrementally
Cited by
74 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Reactive Dataflow for Inflight Error Handling in ML Workflows;Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning;2024-06-09
2. Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques;Proceedings of the VLDB Endowment;2023-06
3. Saga: A Platform for Continuous Construction and Serving of Knowledge at Scale;Proceedings of the 2022 International Conference on Management of Data;2022-06-10
4. Efficient Answering of Historical What-if Queries;Proceedings of the 2022 International Conference on Management of Data;2022-06-10
5. A Review of Data Warehousing Using Feature Engineering;2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM);2022-02-23