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Tesi etd-09162019-220730


Thesis type
Tesi di laurea magistrale
Author
FAIS, ALESSANDRA
URN
etd-09162019-220730
Title
Benchmarking Data Stream Processing Frameworks on Multicores
Struttura
INFORMATICA
Corso di studi
INFORMATICA E NETWORKING
Commissione
relatore Dott. Mencagli, Gabriele
Parole chiave
  • data stream processing
  • parallel computing
  • benchmarking
  • performance
  • Apache Storm
  • Apache Flink
  • WindFlow
Data inizio appello
04/10/2019;
Consultabilità
secretata d'ufficio
Riassunto analitico
In recent years, the need for continuous processing and real-time analysis of data streams has increased rapidly. In order to achieve high-throughput and low-latency requirements, a stream application can be implemented choosing one of the various Data Stream Processing frameworks that offer suitable abstractions for operator parallelization and distribution.
This work shows a comparison in terms of performance (bandwidth and latency) between traditional Data Stream Processing systems (Apache Storm and Flink) and the WindFlow C++17 library, which is an efficient streaming library developed by the Parallel Programming Models group at the Department of Computer Science of the University of Pisa.
Four real-world Data Stream Processing applications have been implemented using Storm, Flink and WindFlow. Experiments are conducted on a single multi-core machine showing a significant throughput improvement and latency reduction by using the C++ solution with respect to the state-of-the-art frameworks.
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