Column-Oriented Replication Management for Large-Volume Data Storages
Keywords:Column-Data, Compression, Data Duplication, , Flash Replication, Mirroring, MLC SSD.
The column-based database repository is a highly advanced model for big data analysis systems with its superior I/O performance. In order to improve write operations, traditional database systems utilize a block-oriented storage in which records of column attributes are placed continuously on the hard disk. However, for read-intensive data warehouse, column-oriented storage becomes a more appropriate model to exploit its excellent performance. In addition, flash SSDs using MLC memory have recently been recognized as a most suitable storage medium for high-speed data analysis systems.
This paper introduces the column-oriented model and proposes a new storage management scheme that utilizes cross-compression method for high-speed data warehouses. The proposed storage management scheme is implemented on two MLC SSDs and provides excellent performance and reliability even in high CPU and I/O workloads. The results of our performance evaluation show that the proposed storage management scheme is better than the conventional scheme in terms of column update throughput and response time.
 Ahn S. & Kim. K. (2013), A Join Technique to Improve the Performance of Star Schema Queries in Column-Oriented Databases, Journal of Korean Institute of Information Scientist and Engineers 40:3, 209-219.
 Byun S. (2017), Design of Efficient Index Management for Column-based Big Databases, International Journal of Internet of Things and Big Data 2:1, 59-64.
 Abadi D., Boncz A. & Harizopoulos S., â€œColumn-oriented Database Systems,â€ Proceedings of the VLDB, (2009) Lyon, France, 24-28 .
 Harizopoulos S., Liang V., Abadi D. J., & Madden S., â€œPerformance tradeoffs in read-optimized databases, Proceedings of the VLDB, (2006), 487-498.
 Halverson A., Beckmann J., & Naughton J. (2006), A comparison of c-store and row-store in a common framework, Technical Report, UW Madison Department of CS, TR1566.
 Byun S. (2017), Shadow Indexing Scheme Using Hybrid Memory for Column-Based Datawarehouses, INFORMATION 20:11, 8125-8132.
 Kim H. & Noh H. (2015), Hybrid Main Memory Systems Using Next Generation Memories Based on their Access Characteristics, Journal of KIISE 42:2, 183-189.
 Li, Y. B. He, R. J. Yang, Luo Q., & Yi K., â€œTree indexing on solid state drives,â€ â€ Proceedings of the VLDB 3:1, (2010), 1195-1206.
 Lu, N., Choi I, & Kim S. (2012), A PRAM based block updating management for hybrid solid state disk, IEICE Electronics Express 9:4, 320-325.
 LZO, â€œLZO Professional data compressionâ€, (2018), available online: http://www.oberhumer.com/products/lzo-professional/
 Madhushree G, Kavitha V. N., Arpitha S. M., Latha S. S., & ArunBiradar (2018), ACO Technique for Reducing Energy Consumption in Wireless Sensor Network, International Journal of Computing, Communications and Networking 7:2, 42-47.
 Abadi D., Myers D., DeWitt D., & Madden S. (2006), Materialization strategies in a column-oriented DBMS, MIT CSAIL Technical Report, MIT-CSAIL-TR-2006-078.Csim, â€œGetting Started:CSIM 20 Simulation Engine (C Version)â€, (2018), available online: https://static1.squarespace.com/ statc/56eb309fe321407d6a06998a/t/5824f21c46c3c4041b461eeb/1478816285097/Getting_Started-C.pdf.
View Full Article:
How to Cite
LicenseAuthors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under aÂ Creative Commons Attribution Licensethat allows others to share the work with an acknowledgement of the work''s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal''s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (SeeÂ The Effect of Open Access).