Towards materialized view selection for distributed databases

Materialized views (MV) can significantly improve the query performance of relational databases. In this paper, we consider MVs to optimize complex scenarios where many heterogeneous nodes with different resource constraints (e.g., CPU, IO and network bandwidth) query and update numerous tables on different nodes. Such problems are typical for large enterprises, e.g., global retailers storing thousands of relations on hundreds of nodes at different subsidiaries. Choosing which views to materialize in a distributed, complex scenario is NP-hard. Furthermore, the solution space is huge, and the large number of input factors results in non-monotonic cost models. This prohibits the straightforward use of brute-force algorithms, greedy approaches or proposals from organic computing. For the same reason, all solutions for choosing MVs we are aware of do not consider either distributed settings or update costs. In this paper we describe an algorithmic framework which restricts the sets of...

• Type: Conference
• Year: 2009
• Where: EDBT
• Authors: Leonardo Weiss Ferreira Chaves, Erik Buchmann, Fabian Hueske, Klemens Böhm
• Keywords: Complex Scenario, Database, EDBT 2009, Genetic Algorithm, Solution Space