A Semantic++ MapReduce: A Preliminary Report

2014 IEEE International Conference on Semantic Computing Pub Date : 2014-06-16 DOI:10.1109/ICSC.2014.63

Guigang Zhang, Jian Wang, Weixing Huang, C. Li, Yong Zhang, Chunxiao Xing

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引用次数: 2

Abstract

Big data processing is one of the hot scientific issues in the current social development. MapReduce is an important foundation for big data processing. In this paper, we propose a semantic++ MapReduce. This study includes four parts. (1) Semantic++ extraction and management for big data. We will do research about the automatically extracting, labeling and management methods for big data's semantic++ information. (2) SMRPL (Semantic++ MapReduce Programming Language). It is a declarative programming language which is close to the human thinking and be used to program for big data's applications. (3) Semantic++ MapReduce compilation methods. (4) Semantic++ MapReduce computing technology. It includes three parts. 1) Analysis of semantic++ index information of the data block, the description of the semantic++ index structure and semantic++ index information automatic loading method. 2) Analysis of all kinds of semantic++ operations such as semantic++ sorting, semantic++ grouping, semantic+++ merging and semantic++ query in the map and reduce phases. 3) Shuffle scheduling strategy based on semantic++ techniques. This paper's research will optimize the MapReduce and enhance its processing efficiency and ability. Our research will provide theoretical and technological accumulation for intelligent processing of big data.

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语义++ MapReduce:初步报告

大数据处理是当前社会发展中的热点科学问题之一。MapReduce是大数据处理的重要基础。在本文中，我们提出了一个语义++ MapReduce。本研究包括四个部分。(1)大数据语义++提取与管理。研究大数据语义++信息的自动提取、标注和管理方法。(2) SMRPL (Semantic++ MapReduce Programming Language)。它是一种接近人类思维的声明式编程语言，可用于大数据应用的编程。(3) Semantic++ MapReduce编译方法。(4) Semantic++ MapReduce计算技术。它包括三个部分。1)分析了数据块的语义++索引信息，描述了语义++索引结构和语义++索引信息自动加载方法。2)分析map和reduce阶段的各种语义++操作，如语义++排序、语义++分组、语义++合并、语义++查询。3)基于语义++技术的Shuffle调度策略。本文的研究将对MapReduce进行优化，提高其处理效率和处理能力。我们的研究将为大数据的智能处理提供理论和技术积累。

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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2014 IEEE International Conference on Semantic Computing

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