Обзор современных систем обработки временных рядов

Обзор современных систем обработки временных рядов

Автор: Иванова Елена Владимировна, Цымблер Михаил Леонидович

Журнал: Вестник Южно-Уральского государственного университета. Серия: Вычислительная математика и информатика @vestnik-susu-cmi

Статья в выпуске: 4 т.9, 2020 года.

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Временной ряд представляет собой последовательность хронологически упорядоченных числовых значений, отражающих течение некоторого процесса или явления. В настоящее время одним из наиболее актуальных классов задач обработки временных рядов являются приложения Индустрии 4.0 и Интернета вещей. В данных приложениях типичной является задача обеспечения умного управления и предиктивного технического обслуживания сложных машин и механизмов, которые оснащаются различными сенсорами. Такие сенсоры имеют высокую дискретность снятия показаний и за сравнительно короткое время продуцируют временные ряды длиной от десятков миллионов до миллиардов элементов. Получаемые с сенсоров данные накапливаются и подвергаются интеллектуальному анализу для принятия стратегически важных решений. Обработка временных рядов требует специфического системного программного обеспечения, отличного от имеющихся реляционных СУБД и NoSQL-систем. Системы обработки временных рядов должны обеспечивать, с одной стороны, эффективные операции добавления новых атомарных значений, поступающих в потоковом режиме, а с другой стороны, эффективные операции интеллектуального анализа, в рамках которых временной ряд рассматривается как единое целое. В статье рассмотрены особенности обработки временных рядов в сравнении с данными реляционной и нереляционной природы, и даны формальные определения основных задач интеллектуального анализа временных рядов. Представлен обзор основных возможностей трех наиболее популярных современных систем обработки временных рядов: InfluxDB, OpenTSDB, TimescaleDB.

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Обработка и анализ временных рядов, реляционная субд

Короткий адрес: https://sciup.org/147234285

IDR: 147234285   |   DOI: 10.14529/cmse200406

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