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Boosting heapsort performance of processing Big Data streams

机译:促进处理大数据流的大量性能

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Real-time processing is one aspect of the Big Data situation, and it requires an unconventional approach to solve the recent problems that appear at both software and hardware levels. The continuous increase of data velocity has placed a tremendous pressure on the existing systems, and the current volumes of Big Data limit the efforts of storing everything at a pre-processing stage. Hence, on-the-fly processing is necessary more than before in order to support the collective efforts towards Big Data advancement.
机译:实时处理是大数据情况的一个方面,它需要一个非常规方法来解决软件和硬件级别出现的最近问题。数据速度的连续增长对现有系统施加了巨大的压力,并且目前的大数据量限制了在预处理阶段存储所有内容的努力。因此,在飞行过程中比以前需要更多,以支持对大数据进步的集体努力。

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