Polynomial Heuristics for Query Optimization
Research on query optimization has traditionally focused on exhaustive enumeration of an exponential number of candidate plans. Alternatively, heuristics for query optimization are restricted in several ways, such as by either focusing on join predicates only, ignoring the availability of indexes, or in...
The standard approach to join-query optimization is cost based, which requires developing a cost model, assigning an estimated cost to each query-processing plan, and searching in the space of all plans for a plan of minimal cost. But as the number of joins increases, the size of the ...
First, she experiments with parameter optimization to subsequently apply meta-learning and obtain rules for identifying which algorithm outperforms the rest under specific circumstances. In this case, she applied the C5.0 algorithm [41–43] as a meta-learner and employed 20 dataset characteristics as...
Discover the latest articles and news from researchers in related subjects, suggested using machine learning. Algorithms Clonal selection Learning algorithms Machine Learning Optimization Origin selection 1Introduction Search and optimisation methods such asmetaheuristics(see Blum and Roli2003) andhyper-heuristi...
may not be available in the C# bindings. 1. Identifying the reward function SelfTune's optimization algorithm(e.g., Bluefin) uses a reward to compute a gradient-ascent style update to the parameter values. This reward can be any health or utilization metric of the current state of the ...
The traveling salesman problem (TSP) is a well-known combinatorial optimization problem. In the TSP, given a set of locations (nodes) in a graph, we need to find the shortest tour that visits each location exactly once and returns to the departing location. The TSP is NP-hard [33] even...
Goffe et al., “Global Optimization of Statistical Functions with Simulated Annealing”, Journal of Econometrics, vol. 60, 1994, pp. 65-99. GoGrid, “Gogrid”, available online at, 2008. Goldberg, David E., “Genetic Algorithms in Search, Optimization, and Machine Learning”, Addison Wesley...
wherein each data packet in the group of data packets comprises a separate packet header group and a separate payload portion; inspecting payload portions of data packets in the data packet group to determine application layer messages that are collectively contained in one or more of the payload...
Joshi. Polynomial heuristics for query optimization. ICDE, pages 589-600, 2010.Bruno N.: Polynomial heuristics for query optimization. In: Proc. of Int. Conf. of Data Engineering. pp.589-600. IEEE,USA( 2010)Bruno, N., Galindo-Legaria, C.A., Joshi, M.: Polynomial heuris- tics for ...