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LINVIEW: incremental view maintenance for complex analytical queries (2014)
| Content Provider | CiteSeerX |
|---|---|
| Author | Nikolic, Milos Elseidy, Mohammed Koch, Christoph Lausanne, Fédérale |
| Description | In SIGMOD Many analytics tasks and machine learning problems can be naturally expressed by iterative linear algebra programs. In this paper, we study the incremental view maintenance problem for such complex analytical queries. We develop a framework, called Linview, for capturing deltas of linear al-gebra programs and understanding their computational cost. Linear algebra operations tend to cause an avalanche effect where even very local changes to the input matrices spread out and infect all of the intermediate results and the final view, causing incremental view maintenance to lose its per-formance benefit over re-evaluation. We develop techniques based on matrix factorizations to contain such epidemics of change. As a consequence, our techniques make incremen-tal view maintenance of linear algebra practical and usually substantially cheaper than re-evaluation. We show, both an-alytically and experimentally, the usefulness of these tech-niques when applied to standard analytics tasks. Our evalu-ation demonstrates the efficiency of Linview in generating parallel incremental programs that outperform re-evaluation techniques by more than an order of magnitude. 1. |
| File Format | |
| Language | English |
| Publisher Date | 2014-01-01 |
| Access Restriction | Open |
| Subject Keyword | Input Matrix Iterative Linear Algebra Program Incremental View Maintenance Problem Computational Cost Incremental View Maintenance Parallel Incremental Program Re-evaluation Technique Matrix Factorization Many Analytics Task Avalanche Effect Linear Algebra Operation Machine Learning Problem Analytics Task Final View Local Change Linear Al-gebra Program Per-formance Benefit Complex Analytical Query Incremen-tal View Maintenance Intermediate Result |
| Content Type | Text |
| Resource Type | Article |
