Cos’è lo Streaming di Eventi in Apache Kafka?

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Oleksii K.

Ingegnere DevOps

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Gennaio 06, 2025 · 3 min di lettura

Cos’è lo Streaming di Eventi in Apache Kafka?

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Lo streaming di eventi è un potente paradigma di elaborazione dei dati in cui gli eventi – piccoli pezzi di dati immutabili – vengono continuamente prodotti, acquisiti ed elaborati in tempo reale. Apache Kafka, una piattaforma open-source di streaming di eventi distribuita, è diventata la soluzione di riferimento per implementare lo streaming di eventi nei sistemi moderni.

Comprendere Eventi e Flussi

Un evento è un registro di un’occorrenza, come un utente che clicca un pulsante, un sensore di temperatura che riporta una lettura o una piattaforma di e-commerce che registra un acquisto. Questi eventi vengono acquisiti e memorizzati in Kafka come messaggi.
A flusso è una sequenza illimitata di questi eventi, organizzati in topic in Kafka. Ogni topic serve come un canale logico per eventi correlati (ad esempio, un topic per i registri di attività utente o transazioni finanziarie).

Come Kafka Abilita lo Streaming di Eventi

Produttori e Consumatori:
- I produttori di Kafka scrivono eventi nei topic.
- I consumatori di Kafka leggono questi eventi, spesso in tempo reale, per ulteriore elaborazione o memorizzazione.
Architettura Distribuita: L’architettura di Kafka distribuisce i topic su più server (broker), garantendo scalabilità e tolleranza ai guasti.
Conservazione: Kafka può conservare i dati degli eventi per un periodo configurabile, permettendo ai consumatori di rielaborare gli eventi se necessario.
Elaborazione del Flusso: Con Kafka Streams o strumenti come Apache Flink, puoi elaborare e trasformare flussi di eventi mentre attraversano Kafka.

Perché Usare lo Streaming di Eventi?

Elaborazione dei Dati in Tempo Reale: Elabora i dati mentre accadono, ideale per casi d’uso come rilevamento delle frodi o monitoraggio.
Decoupling: I produttori e i consumatori sono indipendenti, consentendo un design del sistema flessibile.
Scalabilità: Gestisci milioni di eventi al secondo con il design distribuito di Kafka.
Affidabilità: Kafka garantisce la consegna dei messaggi anche in caso di guasti.

Applicazioni dello Streaming di Eventi con Kafka

Analisi in Tempo Reale: Analizza gli eventi mentre si verificano per ottenere intuizioni azionabili.
Architetture Basate su Eventi: Costruisci microservizi che reagiscono agli eventi, migliorando la modularità.
Integrazione dei Dati: Trasmette dati tra database, applicazioni e altri sistemi in tempo reale.

Lo streaming di eventi con Apache Kafka ha trasformato il modo in cui le organizzazioni gestiscono i dati. Catturando e elaborando continuamente eventi, Kafka consente alle aziende di prendere decisioni più rapide e intelligenti e di costruire sistemi scalabili e resilienti.

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tuuid_last_update	Collects anonymous data related to the user's visits to the website, such as the number of visits, average time spent on the website and what pages have been loaded.
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dpm	Via a unique ID that is used for semantic content analysis, the user's navigation on the website is registered and linked to offline data from surveys and similar registrations to display targeted ads.
acs	Collects anonymous data related to the user's visits to the website, such as the number of visits, average time spent on the website and what pages have been loaded, with the purpose of displaying targeted ads.
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AFFICHE_W	Used by the advertising platform Weborama to determine the visitor's interests based on pages visits, content clicked and other actions on the website.
B	Collects anonymous data related to the user's website visits, such as the number of visits, average time spent on the website and what pages have been loaded. The registered data is used to categorise the users' interest and demographical profiles with the purpose of customising the website content depending on the visitor.
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khaos	Registers anonymised user data, such as IP address, geographical location, visited websites, and what ads the user has clicked, with the purpose of optimising ad display based on the user's movement on websites that use the same ad network.
put_#	Registers anonymised user data, such as IP address, geographical location, visited websites, and what ads the user has clicked, with the purpose of optimising ad display based on the user's movement on websites that use the same ad network.
rpb	Registers anonymised user data, such as IP address, geographical location, visited websites, and what ads the user has clicked, with the purpose of optimising ad display based on the user's movement on websites that use the same ad network.
rpx	Registers anonymised user data, such as IP address, geographical location, visited websites, and what ads the user has clicked, with the purpose of optimising ad display based on the user's movement on websites that use the same ad network.
tap.php	Registers anonymised user data, such as IP address, geographical location, visited websites, and what ads the user has clicked, with the purpose of optimising ad display based on the user's movement on websites that use the same ad network.

Cos’è lo Streaming di Eventi in Apache Kafka?

Comprendere Eventi e Flussi

Come Kafka Abilita lo Streaming di Eventi

Perché Usare lo Streaming di Eventi?

Applicazioni dello Streaming di Eventi con Kafka

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Cos’è lo Streaming di Eventi in Apache Kafka?

Comprendere Eventi e Flussi

Come Kafka Abilita lo Streaming di Eventi

Perché Usare lo Streaming di Eventi?

Applicazioni dello Streaming di Eventi con Kafka

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