Observatorio de I+D+i UPM

Memorias de investigación
Ponencias en congresos:
Towards a Unified Storage and Ingestion Architecture for Stream Processing
Año:2017
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Big Data applications are rapidly moving from a batch-oriented execution model to a streaming execution model in order to extract value from the data in real-time. However, processing live data alone is often not enough: in many cases, such applications need to combine the live data with previously archived data to increase the quality of the extracted insights. Current streaming-oriented runtimes and middlewares are not flexible enough to deal with this trend, as they address ingestion (collection and pre-processing of data streams) and persistent storage (archival of intermediate results) using separate services. This separation often leads to I/O redundancy (e.g., write data twice to disk or transfer data twice over the network) and interference (e.g., I/O bottlenecks when collecting data streams and writing archival data simultaneously). In this position paper, we argue for a unified ingestion and storage architecture for streaming data that addresses the aforementioned challenge. We identify a set of constraints and benefits for such a unified model, while highlighting the important architectural aspects required to implement it in real life. Based on these aspects, we briefly sketch our plan for future work that develops the position defended in this paper.
Internacional
Si
Nombre congreso
Second workshop on Real-time and stream processing in Big Data, IEEE International Conference on Big Data
Tipo de participación
960
Lugar del congreso
Boston, Estados Unidos de América
Revisores
Si
ISBN o ISSN
CDP08UPM
DOI
10.1109/BigData.2017.8258196
Fecha inicio congreso
11/12/2017
Fecha fin congreso
14/12/2017
Desde la página
2402
Hasta la página
2407
Título de las actas
Proceedings of the Second workshop on Real-time and stream processing in Big Data, IEEE International Conference on Big Data.
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Maria de los Santos Perez Hernandez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Arquitectura y Tecnología de Sistemas Informáticos
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