Sökning: "NDB"

Visar resultat 1 - 5 av 14 uppsatser innehållade ordet NDB.

  1. 1. External Streaming State Abstractions and Benchmarking

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Sruthi Sree Kumar; [2021]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  3. 2. A comparison of Data Stores for the Online Feature Store Component : A comparison between NDB and Aerospike

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Alexander Volminger; [2021]
    Nyckelord :Feature Stores; Data Stores; NDB; Aerospike; NoSQL; Online Feature Stores; Feature Stores; Datalagringsystem; NDB; Aerospike; NoSQL; Online Feature Stores;

    Sammanfattning : This thesis aimed to investigate what Data Stores would fit to be implemented as an Online Feature Store. This is a component in the Machine Learning infrastructure that needs to be able to handle low latency Reads at high throughput with high availability. LÄS MER

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

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Muhammad Haseeb Asif; [2021]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  5. 4. Dynamic First Match : Reducing Resource Consumption of First Match Queries in MySQL NDB Cluster

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Hara Kumar; [2020]
    Nyckelord :“Query Optimization”; “Distributed Databases”; “First Match Query”; Frågaoptimering; ”distribuerad databas”; “första match frågor”;

    Sammanfattning : Dynamic First Match is a learned heuristic that reduces the resource consumption of first match queries in a multi-threaded, distributed relational database, while having a minimal effect on latency. Traditional first match range scans occur in parallel across all data fragments simultaneously. This could potentially return many redundant results. LÄS MER

  7. 5. S3-HopsFS: A Scalable Cloud-native Distributed File System

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Joel Stenkvist; [2019]
    Nyckelord :;

    Sammanfattning : Data has been regarded as the new oil in today’s modern world. Data is generated everywhere from how you do online shopping to where you travel. Companies rely on analyzing this data to make informed business decisions and improve their products and services. However, storing this massive amount of data can be very expensive. LÄS MER