Titlebook: Data-Intensive Text Processing with MapReduce; Jimmy Lin,Chris Dyer Book 2010 Springer Nature Switzerland AG 2010

情感

CULP

NGC (New General Catalogue) Objects,mapper, the reducer, and optionally, the combiner and the partitioner. All other aspects of execution are handled transparently by the execution framework—on clusters ranging from a single node to a few thousand nodes, over datasets ranging from gigabytes to petabytes. However, this also means that

織布機(jī)

狂熱語(yǔ)言

Special Provisions on Tortfeasorsnown as the web graph), social networks (manifest in the flow of email, phone call patterns, connections on social networking sites, etc.), and transportation networks (roads, bus routes, flights, etc.).Our very own existence is dependent on an intricate metabolic and regulatory network, which can b

Sinus-Rhythm

高射炮

https://doi.org/10.1007/978-3-319-07839-7, but there is consensus that great value lies buried in them, waiting to be unlocked by the right computational tools. In the commercial sphere, business intelligence—driven by the ability to gather data from a dizzying array of sources—promises to help organizations better understand their custome

抵消

Introduction,rocessing dating back several decades. MapReduce has since enjoyed widespread adoption via an open-source implementation called Hadoop, whose development was led by Yahoo (now an Apache project).Today, a vibrant software ecosystem has sprung up around Hadoop, with significant activity in both industry and academia.

Meager

Costume

Hippocampus

https://doi.org/10.1007/978-3-319-07839-7erious problems. They are brittle with respect to the natural variation found in language, and developing systems that can deal with inputs from diverse domains is very labor intensive. Furthermore, when these systems fail, they often do so catastrophically, unable to offer even a “best guess” as to what the desired analysis of the input might be.