Data is at the heart of almost everything we encounter in our daily lives, from shopping, banking, transport, and travel to social networking that often requires real-time processing to meet the never-ending demand of human beings in this competitive world.This kind of real-time processing can be achieved through various stream processing platforms that help applications respond to users with the results as soon as they occur. In our thesina we are going focus on Apache Kafka, an open-source platform that supports data streaming and work on Kafka Streams to focus on the relationship that partions in Kafka Server has with the overall throughput of the system.
I dati sono al centro di quasi tutto ciò che incontriamo nella nostra vita quotidiana, da acquisti, operazioni bancarie, trasporti e viaggi ai social network che spesso richiedono un'elaborazione in tempo reale per soddisfare la domanda infinita degli esseri umani in questo mondo competitivo. tipo di elaborazione in tempo reale può essere ottenuto attraverso varie piattaforme di elaborazione del flusso che aiutano le applicazioni a rispondere agli utenti con i risultati non appena si verificano. Nella nostra tesi ci concentreremo su Apache Kafka, una piattaforma open source che supporta lo streaming di dati e lavoriamo su Kafka Streams per concentrarci sulla relazione che le partizioni in Kafka Server hanno con il throughput complessivo del sistema.
Nexmark benchmarking analysis using Apache Kafka
DE, SUDARSHAN
2020/2021
Abstract
Data is at the heart of almost everything we encounter in our daily lives, from shopping, banking, transport, and travel to social networking that often requires real-time processing to meet the never-ending demand of human beings in this competitive world.This kind of real-time processing can be achieved through various stream processing platforms that help applications respond to users with the results as soon as they occur. In our thesina we are going focus on Apache Kafka, an open-source platform that supports data streaming and work on Kafka Streams to focus on the relationship that partions in Kafka Server has with the overall throughput of the system.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/179015