Column-Oriented Replication Management for Large-Volume Data Storages
DOI:
https://doi.org/10.14419/ijet.v7i4.16.27855Keywords:
Column-Data, Compression, Data Duplication, , Flash Replication, Mirroring, MLC SSD.Abstract
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.
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References
[1] 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.
[2] 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.
[3] Abadi D., Boncz A. & Harizopoulos S., “Column-oriented Database Systems,†Proceedings of the VLDB, (2009) Lyon, France, 24-28 .
[4] Harizopoulos S., Liang V., Abadi D. J., & Madden S., “Performance tradeoffs in read-optimized databases, Proceedings of the VLDB, (2006), 487-498.
[5] 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.
[6] Byun S. (2017), Shadow Indexing Scheme Using Hybrid Memory for Column-Based Datawarehouses, INFORMATION 20:11, 8125-8132.
[7] 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.
[8] Li, Y. B. He, R. J. Yang, Luo Q., & Yi K., “Tree indexing on solid state drives,††Proceedings of the VLDB 3:1, (2010), 1195-1206.
[9] 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.
[10] LZO, “LZO Professional data compressionâ€, (2018), available online: http://www.oberhumer.com/products/lzo-professional/
[11] 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.
[12] 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, “Getting Started:CSIM 20 Simulation Engine (C Version)â€, (2018), available online: https://static1.squarespace.com/ statc/56eb309fe321407d6a06998a/t/5824f21c46c3c4041b461eeb/1478816285097/Getting_Started-C.pdf.
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Received date: February 24, 2019
Accepted date: February 24, 2019
Published date: November 27, 2018