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A Dynamic Compression Method for Database Backup Files in Cloud Environments

  • Dongjie Zhu
  • , Yulan Zhou
  • , Shaozai Yu*
  • , Tianyu Wang
  • , Yang Wu
  • , Hao Hu
  • , Haiwen Du
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Kingsoft Cloud
  • School of Astronautics, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the progress of society and the improvement of the degree of information technology, the data storage capacity of enterprise business is becoming larger. More and more enterprises choose to hand over the storage business to specialized cloud manufacturers. Generally, for the security and reliability of user data, cloud service providers (CSP) will conduct incremental or full backups of user data frequently. However, with the expansion of business and the increase of user data volume, the burden of data backup required by CSPs is becoming heavier. At present, most CSPs use open-source Xtrabackup for hot database backup and recovery, but Xtrabackup has shortcomings in compression rate and decompression speed. To better improve Xtrabackup, we analyzed the backup and recovery process of Xtrabackup and fully explored the factors that affect its compression rate and decompression speed. Finally, an optimization strategy is proposed to optimize the original Xtrabackup. Experiments show that the proposed optimization scheme can increase the compression rate by 30%–50%, reduce the recovery time by 40%, and the total compression time by 25%.

Original languageEnglish
Title of host publicationData Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings
EditorsYing Tan, Yuhui Shi, Albert Zomaya, Hongyang Yan, Jun Cai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages316-327
Number of pages12
ISBN (Print)9789811675010
DOIs
StatePublished - 2021
Externally publishedYes
Event6th International Conference on Data Mining and Big Data, DMBD 2021 - Guangzhou, China
Duration: 20 Oct 202122 Oct 2021

Publication series

NameCommunications in Computer and Information Science
Volume1454 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference6th International Conference on Data Mining and Big Data, DMBD 2021
Country/TerritoryChina
CityGuangzhou
Period20/10/2122/10/21

Keywords

  • Compression rate
  • Decompression speed
  • Double buffering model
  • Dynamic assignment

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