Finding a Needle in Haystack: Facebook's Photo Storage

D. Beaver, Sanjeev Kumar, Harry C. Li, J. Sobel, Peter Vajgel
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引用次数: 493

Abstract

This paper describes Haystack, an object storage system optimized for Facebook's Photos application. Facebook currently stores over 260 billion images, which translates to over 20 petabytes of data. Users upload one billion new photos (∼60 terabytes) each week and Facebook serves over one million images per second at peak. Haystack provides a less expensive and higher performing solution than our previous approach, which leveraged network attached storage appliances over NFS. Our key observation is that this traditional design incurs an excessive number of disk operations because of metadata lookups. We carefully reduce this per photo metadata so that Haystack storage machines can perform all metadata lookups in main memory. This choice conserves disk operations for reading actual data and thus increases overall throughput.
大海捞针:Facebook的照片存储
本文描述了Haystack,一个针对Facebook照片应用优化的对象存储系统。Facebook目前存储了超过2600亿张图片,相当于超过20pb的数据。用户每周上传10亿张新照片(约60tb), Facebook在最高峰时每秒提供100万张以上的照片。与之前的方法相比,Haystack提供了一种成本更低、性能更高的解决方案,之前的方法利用了NFS上的网络附加存储设备。我们的主要观察结果是,由于元数据查找,这种传统设计会导致过多的磁盘操作。我们小心地减少了每张照片元数据的开销,以便Haystack存储机器可以在主内存中执行所有元数据查找。这种选择节省了读取实际数据的磁盘操作,从而提高了总体吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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