April 2025
Intermediate to advanced
310 pages
9h 20m
Italian
Content preview from Elaborazione di flussi con Apache Flink
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Capitolo 6. Operatori a tempo e a Windows
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In questo capitolo tratteremo i metodi dell'API DataStream per la gestione del tempo e gli operatori basati sul tempo, come Windows. Come hai appreso in "Semantica del tempo", gli operatori basati sul tempo di Flink possono essere applicati con diverse nozioni di tempo.
Innanzitutto, impareremo a definire le caratteristiche temporali, i timestamp e le filigrane. Poi, ci occuperemo delle funzioni di processo, trasformazioni di basso livello che consentono di accedere a timestamp e watermark e di registrare i timer. Poi useremo l'API di Flink per le finestre, che fornisce implementazioni integrate dei tipi di finestre più comuni. Verranno inoltre introdotte le operazioni di finestra personalizzate e definite dall'utente e i principali costrutti di finestra, come gli assegnatori, i trigger e gli evictor. Infine, parleremo di come unire gli stream in tempo e delle strategie per gestire gli eventi in ritardo.
Configurazione delle caratteristiche temporali
Per definire le operazioni temporali in un'applicazione di elaborazione distribuita dei flussi, è importante capire il significato di tempo. Quando specifichi una finestra per raccogliere eventi in bucket di un minuto, quali eventi conterrà esattamente ogni bucket? Nell'API DataStream di, puoi utilizzare la caratteristica time per indicare a Flink come ...
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