
Цель наÑтоÑщей работы - Ñпроектировать и реализовать набор вÑпомогательных инÑтрументов Ð´Ð»Ñ Ð·Ð°ÐºÐ°Ð·Ñ‡Ð¸ÐºÐ°, работодателÑ, архитектора решений и любого заинтереÑованного лица в Ñфере IT. Ð’ рамках данной выпуÑкной квалификационной работы были проанализированы Ñ‚Ñ€ÐµÐ±Ð¾Ð²Ð°Ð½Ð¸Ñ Ð·Ð°ÐºÐ°Ð·Ñ‡Ð¸ÐºÐ°, выбраны технологии, поÑтроена архитектура проекта, а также проведен анализ ÑущеÑтвующих на рынке альтернатив, на оÑновании которого было принÑто решение Ñпроектировать и реализовать ÑервиÑ, позволÑющий отÑлеживать Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð² трендах по технологиÑм в реальном времени. Ð¡ÐµÑ€Ð²Ð¸Ñ Ð¸Ð¼ÐµÐµÑ‚ набор решений, оÑнованных на BigData технологиÑÑ… Ñ Ð¿Ñ€Ð¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ Каппа-архитектуры Ð´Ð»Ñ Ñ€Ð°Ñпределенной обработки больших объемов данных Ñ Ð¿Ð¾Ð¼Ð¾Ñ‰ÑŒÑŽ фреймворка Spark на Ñзыке Scala, а также клиент-Ñерверное приложение, напиÑанное на Ñзыке Java Ñ Ð¸Ñпользованием Spring.
The main purpose of this thesis is to design and develop the set of tools for customer, employer, solution architect and any interested person in IT. Customer’s requirements have been analyzed, technologies have been selected, the architecture have been created and the analysis of competitors has been performed in the course of this graduation work, on the basis of which it was decided to design and implement a service, that allows to track trends in technology trends in real time. The service has a set of solutions based on BigData technologies with the use of Kappa architecture for distributed processing of large amounts of data using the Spark framework in Scala and a client-server application written in Java using the Spring framework.
Spark, machine learning, framework, client-server application, BigData, маÑинное обÑÑение, ÑÑеймвоÑк, клиенÑ-ÑеÑвеÑное пÑиложение, Java
Spark, machine learning, framework, client-server application, BigData, маÑинное обÑÑение, ÑÑеймвоÑк, клиенÑ-ÑеÑвеÑное пÑиложение, Java
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