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Designing a multi-petabyte database for LSST

机译:为LSST设计一个多宠物数据库

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摘要

The 3.2 giga-pixel LSST camera will produce approximately half a petabyte of archive images every month. These data need to be reduced in under a minute to produce real-time transient alerts, and then added to the cumulative catalog for further analysis. The catalog is expected to grow about three hundred terabytes per year. The data volume, the real-time transient alerting requirements of the LSST, and its spatio-temporal aspects require innovative techniques to build an efficient data access system at reasonable cost. As currently envisioned, the system will rely on a database for catalogs and metadata. Several database systems are being evaluated to understand how they perform at these data rates, data volumes, and access patterns. This paper describes the LSST requirements, the challenges they impose, the data access philosophy, results to date from evaluating available database technologies against LSST requirements, and the proposed database architecture to meet the data challenges.
机译:3.2 Giga-Pixel LSST相机每月将产生大约半个档案图像的Petabyte。这些数据需要在一分钟内减少以产生实时瞬态警报,然后添加到累积目录中以进行进一步分析。目录预计每年将生长约三百八十次。数据量,LSST的实时瞬态警报要求及其时空方面需要创新的技术以合理的成本构建高效的数据访问系统。如目前所想,系统将依赖于目录和元数据的数据库。正在评估几个数据库系统以了解它们在这些数据速率,数据卷和访问模式下执行的方式。本文介绍了LSST要求,它们施加的挑战,数据访问理念,迄今为止评估可用数据库技术的可用数据库技术,以及所提出的数据库架构,以满足数据挑战。

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