Chisel: Reshaping Queries to Trim Latency in Key-Value Stores

Robert Birke, Juan F. Perez, Sonia Ben Mokhtar, Navaneeth Rameshan, Lydia Y. Chen

Resultado de la investigación: Capítulo en Libro/Reporte/ConferenciaContribución a la conferencia

1 Cita (Scopus)

Resumen

It is challenging for key-value data stores to trim user (tail) latency of requests as the workloads are observed to have skewed number of key-value pairs and commonly retrieved via multiget operation, i.e., all keys at the same time. In this paper we present Chisel, a novel client side solution to efficiently reshape the query size at the data store by adaptively splitting big requests into chunks to reap the benefits of parallelism and merge small requests into a single query to amortize latency overheads per request. We derive a novel layered queueing model that can quickly and approximately steer the decisions of Chisel. We extensively evaluate Chisel on memcached clusters hosted on a testbed, across a large number of scenarios with different workloads and system configurations. Our evaluation results show that Chisel can overturn the inherent high variability of requests into a judicious operational region, showcasing significant gains for the mean and 95th percentile of user perceived latency, compared to the state-of-art query processing policy.

Idioma originalInglés estadounidense
Título de la publicación alojadaProceedings - 2019 IEEE International Conference on Autonomic Computing, ICAC 2019
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas42-51
Número de páginas10
ISBN (versión digital)9781728124117
DOI
EstadoPublicada - jun 2019
Evento16th IEEE International Conference on Autonomic Computing, ICAC 2019 - Umea, Suecia
Duración: jun 16 2019jun 20 2019

Serie de la publicación

NombreProceedings - 2019 IEEE International Conference on Autonomic Computing, ICAC 2019

Conferencia

Conferencia16th IEEE International Conference on Autonomic Computing, ICAC 2019
País/TerritorioSuecia
CiudadUmea
Período6/16/196/20/19

All Science Journal Classification (ASJC) codes

  • Inteligencia artificial
  • Redes de ordenadores y comunicaciones
  • Hardware y arquitectura
  • Control y optimización

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