Computer Science ›› 2016, Vol. 43 ›› Issue (7): 197-202.doi: 10.11896/j.issn.1002-137X.2016.07.036

Previous Articles     Next Articles

Efficient and Dynamic Data Management System for Cassandra Database

WANG Bo-qian, YU Qi, LIU Xin, SHEN Li, WANG Zhi-ying and CHEN Wei   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Cassandra is one of the universal databases,and it’s also specified as the top level project by the Apache.For the Cassandra distributed database system,a large number of write requests will cause excessive and dispersed SStable structures and high data redundancy,causing low efficiency to the user read requests.This problem can be solved by the local data consolidation mechanism triggered automatically by the system or by the overall data consolidation mechanism triggered by the human intervention.However,on one hand,the irrational timing automatical partial merger process will seriously reduce the performance of the read operation requested by the user;on the other hand,the long-time human overall data consolidation process will occupy a large number of system resources,which will severely restrict the overall performance of the corresponding system.To solve this problem,we presented an efficient and dynamic management mechanism.Firstly,appropriate implementation strategies are developed to the time of the merger,the file involved in the merger and the merge process by monitoring system environment and managing the data according to the time and size.Secondly,the impact of the consolidation process on system performance is reduced by reducing the data combination time through specific optimization methods.The final result shows that this data management system optimizes the Cassandra database consolidation process and ultimately enhances the response speed for the read request.

Key words: Cassandra database,Dynamic data management,Consolidation strategy,Response speed for the read request

[1] Ferdman M,Adileh A,Kocberber O,et al.Clearing the clouds:a study of emerging scale-out workloads on modern hardware[J].ACM SIGARCH Computer Architecture News,2012,40(1):37-48
[2] Lotfi-Kamran P,Grot B,Ferdman M,et al.Scale-out processors[J].IEEE Computer Society ACM SIGARCH Computer Architecture News,2012,40(3):500-511
[3] First the tick,now the tock:Next generation Intel microarchitecture (Nehalem).
[4] Rabl T,Sadoghi M,Jacobsen H A,et al.Solving Big Data Challenges for Enterprise Application Performance Management[J].PVLDB,2012,5(12):1724-1735
[5] DeCandia G,Hastorun D,Jampani M,et al.Dynamo:Amazon’s Highly Available Key-Value Store[J].ACM Sigops Oper.Syst.rev,2007,1(6):205-220
[6] Cartell R.Scalable SQL and NoSQL data stores[J].ACM Sigmod Record,2010,9(4):12-27
[7] Nguyen T T,Nguyen M H.Zing Database:high-performancekey-value store for large-scale storage service[J].Vietnam Journal of Computer Science,2015,2(1):13-23
[8] The Apache Cassandra Project.
[9] Chen C,Hsiao M.Bigtable:A distributed storage system forstructured data[J].Proceedings of Osdi,2006,26(2):205-218
[10] Cooper B F,Silberstein A,Tam E,et al.Benchmarking cloud serving systems with YCSB[C]∥SoCC.2010:143-154
[11] Bridges J T,Dieffenderfer J N,Sartorius T,et al.Caching memory attribute indicators with cached memory data field[P].US,US20070094475 A1,2005
[12] Spillane R P,Shetty P J,Zadok E,et al.An efficient multi-tier tablet server storage architecture[C]∥Acm Symposium on Cloud Computing Acm.2011:1-14

No related articles found!
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .