谷歌MapReduce经典论文翻译(中英对照)

Java65

MapReduce: Simplified Data Processing on Large Clusters(MapReduce: 简化大型集群下的数据处理)

作者:Jeffrey Dean and Sanjay Ghemawat

Abstract(摘要)

MapReduce is a programming model and an associated implementation for processing and generating large data sets.

Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs,
and a reduce function that merges all intermediate values associated with the same intermediate key.

Many real world tasks are expressible in this model, as shown in the paper.

MapReduce是一个关于实施大型数据集处理和生成的编程模型。
用户指定一个用于处理 k/v对并生成 中间态k/v对集合的映射(map)函数,以及一个用于合并所有具有相同中间态key的中间态value值的归约(reduce)函数。
正如本篇论文所展示的那样,很多现实世界中的任务都可以通过该模型(MapReduce)表达。

Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines.

The run-time system takes care of the details of partitioning the input data,scheduling the program's execution across a set of machines, handling machine failures,

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