Maguro, a system for indexing and searching over very large text collections

Knut Magne Risvik, Trishul M. Chilimbi, Henry Tan, Karthik Kalyanaraman, Chris Anderson
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引用次数: 26

Abstract

Maguro is a system for efficiently searching very large collections of text content of up to 1 trillion documents at low cost. Search engines span across content that is very dynamic and highly augmented with metadata to the tail content of the web. A long tail distribution of content calls for different trade-offs in the design space for good efficiency across the entire index range. Maguro is designed for the long tail of content with less dynamics and less metadata, but very good cost efficiency. Maguro is part of the serving stack in Bing and allows us to scale the index significantly better.
一个索引和搜索非常大的文本集合的系统
Maguro是一个能够以低成本高效搜索多达1万亿个文档的大量文本内容的系统。搜索引擎跨越的内容是非常动态的,并且通过元数据高度扩展到web的尾部内容。内容的长尾分布要求在设计空间中进行不同的权衡,以便在整个索引范围内获得良好的效率。Maguro专为内容的长尾而设计,具有较少的动态性和较少的元数据,但具有非常好的成本效率。Maguro是Bing服务栈的一部分,它允许我们更好地扩展索引。
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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