Essays about: "FlinkNDB"

Found 3 essays containing the word FlinkNDB.

  1. 1. Improving Availability of Stateful Serverless Functions in Apache Flink

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Christopher Gustafson; [2022]
    Keywords : Function-as-a-Service; Stateful Serverless Functions; Apache Flink StateFun; Availability; RonDB; RocksDB; Function-as-a-Service; Tillståndsbaserade ServerlösaFunktioner; ApacheFlink StateFun; Tillgänglighet; RonDB; RocksDB;

    Abstract : Serverless computing and Function-as-a-Service are rising in popularity due to their ease of use, provided scalability and cost-efficient billing model. One such platform is Apache Flink Stateful Functions. READ MORE

  3. 2. External Streaming State Abstractions and Benchmarking

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Sruthi Sree Kumar; [2021]
    Keywords : Apache Flink; Distributed Systems; NDB; FlinkNDB; State; State Backends; External State; Stream Processing Systems; Benchmarking; Caching; Apache Flink; Distributed Systems; NDB; FlinkNDB; State; State Backends; External State; Stream Processing Systems; Benchmarking; Caching;

    Abstract : Distributed data stream processing is a popular research area and is one of the promising paradigms for faster and efficient data management. Application state is a first-class citizen in nearly every stream processing system. Nowadays, stream processing is, by definition, stateful. READ MORE

  4. 3. FlinkNDB : Guaranteed Data Streaming Using External State

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Muhammad Haseeb Asif; [2021]
    Keywords : Apache Flink; NDB; Flink State Backend; RocksDB State Backend; State management; Large State Applications; Apache Flink; NDB; Flink State Backend; RocksDB State Backend; State management; Large State Applications;

    Abstract : Apache Flink is a stream processing framework that provides a unified state management mechanism which, at its core, treats stream processing as a sequence of distributed transactions. Flink handles failures, re-scaling and reconfiguration seamlessly via a form of a two-phase commit protocol that periodically commits all past side effects consistently into the state backends. READ MORE