Benchmark Tests on Improved Merge for Big Data Processing

Z. Marszalek, M. Woźniak, G. Borowik, Raniyah Wazirali, Christian Napoli, G. Pappalardo, E. Tramontana
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引用次数: 17

Abstract

Computer scientists and engineers work with increasing amounts of information. These data are used for knowledge retrieval, data management decision support and so on. Sorting algorithms are important procedures that if efficiently composed and implemented can increase speed of data processing and decision correctness. Many various sorting algorithms and their modifications are applicable in large computer systems. However, as the computer architectures are more efficient with each release and the software is more complex with each version there is need to improve sorting methods applied for big data computation.
基于改进合并的大数据处理基准测试
计算机科学家和工程师需要处理越来越多的信息。这些数据用于知识检索、数据管理、决策支持等。排序算法是重要的过程,如果有效地组合和实现,可以提高数据处理速度和决策正确性。许多不同的排序算法及其修改适用于大型计算机系统。然而,由于每次发布的计算机架构都更加高效,软件也更加复杂,因此需要改进用于大数据计算的排序方法。
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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