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The data partition strategy based on hybrid range consistent hash in NoSQL database

Published: 17 August 2013 Publication History

Abstract

With the development of Internet technology and Cloud Computing, more and more applications have to be confronted with the challenges of big data. NoSQL Database is fit to the management of big data because of the characteristics of high scalability, high availability and high fault-tolerance. The data partitioning strategy plays an important role in the NoSQL database. The existing data partitioning strategies will cause some problems such as low scalability, hot spot and low performance and so on. In this paper we proposed a new data partitioning strategy---HRCH, which can partitioning the data in a reasonable way. At last we use some experiments to verify the effectiveness of HRCH. It shows that the HRCH can improve the scalability of the system. It also can avoid the hot spot problem as far as possible. And it also can improve the parallel degree of processing to improve the system's performance in some processing.

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  • (2023)Design and Research of the Whole Process Non-blocking Technology in High Concurrency Scenario2023 8th International Conference on Computer and Communication Systems (ICCCS)10.1109/ICCCS57501.2023.10150980(49-55)Online publication date: 21-Apr-2023
  • (2022)Design of a Dynamic Horizontal Fragmentation Method for Multimedia DatabasesHandbook on Decision Making10.1007/978-3-031-08246-7_4(71-91)Online publication date: 27-Sep-2022
  • (2021)A Review of Horizontal Fragmentation Methods Considering Multimedia Data and Dynamic Access PatternsNew Perspectives in Software Engineering10.1007/978-3-030-89909-7_6(69-82)Online publication date: 17-Oct-2021

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  1. The data partition strategy based on hybrid range consistent hash in NoSQL database

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      cover image ACM Other conferences
      ICIMCS '13: Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
      August 2013
      419 pages
      ISBN:9781450322522
      DOI:10.1145/2499788
      • Conference Chair:
      • Tat-Seng Chua,
      • General Chairs:
      • Ke Lu,
      • Tao Mei,
      • Xindong Wu
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • NSF of China: National Natural Science Foundation of China
      • University of Sciences & Technology, Hefei: University of Sciences & Technology, Hefei
      • Beijing ACM SIGMM Chapter

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 17 August 2013

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      Author Tags

      1. NoSQL database
      2. big data
      3. data management
      4. data partition

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      ICIMCS '13
      Sponsor:
      • NSF of China
      • University of Sciences & Technology, Hefei

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      ICIMCS '13 Paper Acceptance Rate 20 of 94 submissions, 21%;
      Overall Acceptance Rate 163 of 456 submissions, 36%

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      View all
      • (2023)Design and Research of the Whole Process Non-blocking Technology in High Concurrency Scenario2023 8th International Conference on Computer and Communication Systems (ICCCS)10.1109/ICCCS57501.2023.10150980(49-55)Online publication date: 21-Apr-2023
      • (2022)Design of a Dynamic Horizontal Fragmentation Method for Multimedia DatabasesHandbook on Decision Making10.1007/978-3-031-08246-7_4(71-91)Online publication date: 27-Sep-2022
      • (2021)A Review of Horizontal Fragmentation Methods Considering Multimedia Data and Dynamic Access PatternsNew Perspectives in Software Engineering10.1007/978-3-030-89909-7_6(69-82)Online publication date: 17-Oct-2021

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