A Fast Algorithm for Classifying Seismic Events Using Distributed Computations in Apache Spark Framework

Autor:	S. E. Popov, R. Yu. Zamaraev
Rok vydání:	2020
Předmět:	Set (abstract data type) Software Computer science business.industry Computation Spark (mathematics) Process (computing) Context (language use) Parallel computing business Adaptation (computer science) Massively parallel
Zdroj:	Programming and Computer Software. 46:35-48
ISSN:	1608-3261 0361-7688
DOI:	10.1134/s0361768820010053
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c52d92c0d27dda3a8d7e9e38149b6d93 https://doi.org/10.1134/s0361768820010053 Zobrazit plný text záznamu Full text from SpringerLink