Abstract
The main ideas of the development of the software implementation of an algorithm for the fast automatic classification of seismic signals based on diagnostic patterns are described. The process of adaptation and integration of this implementation into the distributed computations system Apache Spark is described in detail. A software solution for the preliminary processing of the signals and optimization of the mathematical model for parallel computations using broadcast variables is presented. Performance tests for the classification algorithm on a set of day-long signals are carried out. The execution time of the algorithm in the context of massively parallel computations was reduced tenfold compared with the sequential execution.
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