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引用次数: 1

摘要

MapReduce应用程序的一种常见形式涉及发现某些输入对之间的关系。相似性连接是这类问题的一个很好的例子,我们称之为“某些对”问题。在[4]的框架中,算法是通过reducer大小(一个reducer可以处理的最大输入数量)和复制率(必须发送输入的reducer的平均数量)之间的权衡来衡量的。一般来说,有两种明显的方法来解决某些配对问题。我们表明,在最坏的情况下,没有通用MapReduce算法可以同时击败这两种算法。然后,我们探讨了解决若干对问题的递归算法和在若干对类问题的常见实例上击败下界的启发式算法。
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Some pairs problems
A common form of MapReduce application involves discovering relationships between certain pairs of inputs. Similarity joins serve as a good example of this type of problem, which we call a "some-pairs" problem. In the framework of [4], algorithms are measured by the tradeoff between reducer size (maximum number of inputs a reducer can handle) and the replication rate (average number of reducers to which an input must be sent. There are two obvious approaches to solving some-pairs problems in general. We show that no general-purpose MapReduce algorithm can beat both of these two algorithms in the worst case. We then explore a recursive algorithm for solving some-pairs problems and heuristics for beating the lower bound on common instances of the some-pairs class of problems.
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