Tyr: Blob storage systems meet Built-In transactions

Matri, Pierre, Costan, Alexandru, Antoniu, Gabriel, Montes Sánchez, Jesús and Pérez Hernández, María de los Santos ORCID: https://orcid.org/0000-0003-2949-3307 (2016). Tyr: Blob storage systems meet Built-In transactions. En: "International Conference for High Performance Computing, Networking, Storage and Analysis", 13-18 Nov 2016, Salt Lake City, Utah, Estados Unidos. ISBN 978-1-4673-8815-3. pp. 573-584. https://doi.org/10.1109/SC.2016.48.

Descripción

Título: Tyr: Blob storage systems meet Built-In transactions
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: International Conference for High Performance Computing, Networking, Storage and Analysis
Fechas del Evento: 13-18 Nov 2016
Lugar del Evento: Salt Lake City, Utah, Estados Unidos
Título del Libro: SC16: International Conference for High Performance Computing, Networking, Storage and Analysis (SC) (2016)
Fecha: Noviembre 2016
ISBN: 978-1-4673-8815-3
Volumen: 1
Materias:
ODS:
Escuela: E.T.S. de Ingenieros Informáticos (UPM)
Departamento: Arquitectura y Tecnología de Sistemas Informáticos
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Concurrent Big Data applications often require high-performance storage, as well as ACID (Atomicity, Consistency, Isolation, Durability) transaction support. Although blobs (binary large objects) are an increasingly popular storage model for such applications, state-of-the-art blob storage systems offer no transaction semantics. This demands users to coordinate data access carefully in order to avoid race conditions, inconsistent writes, overwrites and other problems that cause erratic behavior. We argue there is a gap between existing storage solutions and application requirements, which limits the design of transactionoriented applications. We introduce T¿yr, the first blob storage system to provide built-in, multiblob transactions, while retaining sequential consistency and high throughput under heavy access concurrency. T¿yr offers fine-grained random write access to data and in-place atomic operations. Large-scale experiments with a production application from CERN LHC show T¿yr throughput outperforming state-of-the-art solutions by more than 75%.

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Horizonte 2020
642963
BigStorage
Universidad Politécnica de Madrid
BigStorage: Storage-based Convergence between HPC and Cloud to handle Big Data

Más información

ID de Registro: 45072
Identificador DC: https://oa.upm.es/45072/
Identificador OAI: oai:oa.upm.es:45072
Identificador DOI: 10.1109/SC.2016.48
URL Oficial: https://www.computer.org/csdl/proceedings/sc/2016/...
Depositado por: Memoria Investigacion
Depositado el: 09 Mar 2017 15:52
Ultima Modificación: 21 May 2021 09:57