Han-Sheng Huang
ABSTRACT
NoSQL database systems nowadays need to make trade-offs to optimize for their applications by considering consistency, availability, or partition tolerance. While a hybrid database system can use various kinds of database software and take advantage of their features for individual applications and workloads, how to make the database software work together to achieve the highest performance is still a challenging problem. In this paper, we propose Attila, a data-oriented load balancer that monitors the performance of each database node, dynamically detects the hot spots in a hybrid database system, and migrates data to improve the overall throughput. We also provide an extendable and flexible database interface for integrating NoSQL databases and adding database operations. Our experiment results show that, in average, the additional overhead of Attila is about 140--200 microseconds, residing in request transmission and parsing, which is acceptable, considering the improved throughput from the hybrid database system.
- Apache Hadoop. http://hadoop.apache.org/.Google Scholar
- Apache HBase. http://hbase.apache.org/.Google Scholar
- Ganglia. http://ganglia.sourceforge.net/.Google Scholar
- MongoDB. http://www.mongodb.org/.Google Scholar
- Redis. http://redis.io/.Google Scholar
- V. Abramova, J. Bernardino, and P. Furtado. Experimental evaluation of nosql databases. International Journal of Database Management Systems, 6(3), 2014.Google ScholarCross Ref
- Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, Russell Sears. Benchmarking cloud serving systems with YCSB. Proceedings of the 1st ACM symposium on Cloud computing, June 2010. Google ScholarDigital Library
- Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, Robert E. Gruber. Bigtable: A Distributed Storage System for Structured Data. ACM Trans. Comput. Syst., 26(2):4:1--4:26, June 2008. Google ScholarDigital Library
- Katarina Grolinger, Wilson A Higashino, Abhinav Tiwari, and Miriam AM Capretz. Data management in cloud environments: NoSQL and NewSQL data stores. Journal of Cloud Computing: Advances, Systems and Applications, 2(1):5:22, 2013.Google Scholar
- Konstantin Shvachko, Hairong Kuang, Sanjay Radia, and Robert Chansler. The Hadoop Distributed File System. In Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), MSST '10, pages 1--10, Washington, DC, USA, May 2010. IEEE Computer Society. Google ScholarDigital Library
- Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung. The Google File System. In Proceedings of the Nineteenth ACM Symposium on Operating Systems Principles, SOSP '03, pages 29--43, New York, NY, USA, October 2003. ACM. Google ScholarDigital Library
Index Terms
- Load balancing for hybrid NoSQL database management systems
Recommendations
Data adapter for querying and transformation between SQL and NoSQL database
As the growing of applications with big data in cloud computing become popular, many existing systems expect to expand their service to support the explosive increase of data. We propose a data adapter system to support hybrid database architecture ...
Load-Aware Fragment Allocation Strategy for NoSQL Database
ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and ServiceNoSQL databases are famed for the characteristics of high scalability, high availability and high fault-tolerance. So NoSQL databases are used in a lot of applications, especially in the Internet Applications. The computing model of the NoSQL database ...
Incorporating NoSQL into a database course
This article introduces the concepts of Big Data and NoSQL and describes a semester long web-based project that uses both a relational database (Oracle 11g) and a NoSQL (MongoDB) database for an undergraduate database course. The relational database ...
Comments