Transaction Processing Method for NoSQL Based Column

Jeong-Joon Kim, Journal of Information Processing Systems Vol. 13, No. 6, pp. 1575-1584, Dec. 2017  

Keywords: BigData, HBase, Multi-Row Transaction, NoSQL


As interest in big data has increased recently, NoSQL, a solution for storing and processing big data, is getting attention. NoSQL supports high speed, high availability, and high scalability, but is limited in areas where data integrity is important because it does not support multiple row transactions. To overcome these drawbacks, many studies are underway to support multiple row transactions in NoSQL. However, existing studies have a disadvantage that the number of transactions that can be processed per unit of time is low and performance is degraded. Therefore, in this paper, we design and implement a multi-row transaction system for data integrity in big data environment based on HBase, a column-based NoSQL which is widely used recently. The multi- row transaction system efficiently performs multi-row transactions by adding columns to manage transaction information for every user table. In addition, it controls the execution, collision, and recovery of multiple row transactions through the transaction manager, and it communicates with HBase through the communication manager so that it can exchange information necessary for multiple row transactions. Finally, we performed a comparative performance evaluation with HAcid and Haeinsa, and verified the superiority of the multirow transaction system developed in this paper.

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Cite this article
[APA Style]
Kim, J. (2017). Transaction Processing Method for NoSQL Based Column. Journal of Information Processing Systems, 13(6), 1575-1584. DOI: 10.3745/JIPS.04.0052.

[IEEE Style]
J. Kim, "Transaction Processing Method for NoSQL Based Column," Journal of Information Processing Systems, vol. 13, no. 6, pp. 1575-1584, 2017. DOI: 10.3745/JIPS.04.0052.

[ACM Style]
Jeong-Joon Kim. 2017. Transaction Processing Method for NoSQL Based Column. Journal of Information Processing Systems, 13, 6, (2017), 1575-1584. DOI: 10.3745/JIPS.04.0052.