Research on Automatic Configuration Optimization of Big Data Processing Framework Based on Sample Selection and Heuristic Search Algorithm
This research addresses the problems of high data processing cost for automatic configuration of big data framework and insufficient performance of automatic configuration algorithms,and proposes an optimization model for automatic configuration of big data framework based on sample selection and heuristic search algorithms,and the new model is able to perform heuristic search in the configuration space of big data framework through genetic algorithms to realize automatic configuration of the framework.It also a-chieves the optimization of the automatic configuration of big data.The results of the study show that the use of sample selection and heuristic search algorithms can improve the performance of the model,in the optimal configuration of the model,the configuration op-timization speed of the genetic algorithm is significantly higher than other algorithmic models,and the use of sample selection can also reduce the error value of the algorithmic model.In summary,the use of this method can improve the efficiency of the model and reduce the cost of using the model.
big data frameworkautomatic configurationsample selectionheuristic search algorithm