[ "陈世敏(1973-),男,中国科学院计算技术研究所研究员,中国计算机学会大数据专家委员会委员和数据库专家委员会委员,分别于1997年和1999年获得清华大学计算机系学士和硕士学位,于2005年在美国卡耐基梅隆大学获得计算机科学博士学位。曾担任期刊《PVLDB》2017年的副主编,国际会议ICDE 2018、ICDCS 2016、CIKM 2014的PC领域主席。主要研究方向为数据库系统和大数据处理。" ]
网络首发:2018-07,
纸质出版:2018-07-15
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陈世敏. 树状结构大数据类型的高效支持[J]. 大数据, 2018,4(4):2018038.
HEN Shimin C. Efficient support of tree-structured data types[J]. Big Data Research, 2018, 4(4): 2018038.
陈世敏. 树状结构大数据类型的高效支持[J]. 大数据, 2018,4(4):2018038. DOI: 10.11959/j.issn.2096-0271.2018038.
HEN Shimin C. Efficient support of tree-structured data types[J]. Big Data Research, 2018, 4(4): 2018038. DOI: 10.11959/j.issn.2096-0271.2018038.
传统的关系数据模型难以满足大数据应用日益丰富的数据表达和处理的需求,因此实践中涌现了多种非传统的大数据类型。其中,以JSON为代表的树状结构大数据类型被广泛应用,具有重要的理论意义和实用价值。系统介绍了树状结构大数据类型,并探讨如何高效支持树状结构大数据的分析运算。
Traditional relational data model cannot meet the demand of big data applications for expressing and processing wide varieties of data.As a result
a number of non-relational data types have become popular in practice
among which JSONlike tree-structured data types have been widely adopted.Tree-structured data types have important theoretical and practical values.A systematic description of tree-structured data types was provided
and the way to efficiently support data analysis operations on tree-structured data was investigated.
MELNIK S , GUBAREV A , LONG J J , et al . Dremel:interactive analysis of web-scale datasets [J ] . PVLDB , 2010 , 3 ( 1 ): 330 - 339 .
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LIU Z H , HAMMERSCHMIDT B , MCMAHON D . Json data management:supporting schema-less development in rdbms [C ] // 2014 ACM SIGMOD International Conference on Management of Data,June 22-27,2014,Snowbird,USA . New York:ACM Press , 2014 .
WANG Z Y , CHEN S M . Exploitingcommon patterns for tree-structured data [C ] // 2017 ACM SIGMOD International Conference on Management of Data,May 14-19,2017,Chicago,USA . New York:ACM Press , 2017 .
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