No. 18 (277), issue 12Pages 112 - 120

Development of a parallel Database Management System on the Basis of Open-Source POSTGRESQL DBMS

C.S. Pan, M.L. Zymbler
The paper describes the architecture and implementation of PargreSQL parallel database management system (DBMS) for distributed memory multiprocessors. PargreSQL is based upon PostgreSQL open-source DBMS and exploits partitioned parallelism. The paper is devoted to development of a parallel database management system (DBMS) by means of embedding of the parallel query execution techniques based on partitioning parallelism concept into open-source PostgreSQL DBMS. The architecture and implementation principles of the parallel DBMS for cluster computing systems are described. PostgreSQL is a subsystem of PargreSQL. The necessary modifications of the PostgreSQL subsystems are described. These modifications suppose minimal changes in the source code. The changes in data structures and algorithms are encapsulated into separate source code files that are included into the original project file structure. The usage of PargreSQL is transparent for applications. It demands minimal modifications of an application's source code. PargreSQL running on one computing node works like PostgreSQL.
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Keywords
parallel DBMS, partitioned parallelism, PostgreSQL.
References
1. Stonebraker M., Kemnitz G. The POSTGRES Next-generation Database Danagement System. Communications of the ACM. Oct. 1991, vol. 34, no. 10, pp. 78 - 92.
2. Sokolinsky L., Axenov O., Gutova S. Omega: The Highly Parallel Database System Project. Proceedings of the First East-European Symposium on Advances in Database and Information Systems (ADBIS'97), St.-Petersburg, September 2 - 5, 1997, vol. 2, pp. 88 - 90.
3. Sokolinsky L.B. Organization of Parallel Query Processing in Multiprocessor Database Machines with Hierarchical Architecture. Programming and Computer Software, 2001, vol. 27, no. 6, pp. 297 - 308.
4. Samokhvalov N. XML Support in PostgreSQL. SYRCoDIS, CEUR Workshop Proceedings, 2007, vol. 256, pp. 1 - 6.
5. Havinga Y., Dijkstra W., de Keijzer A. Adding HL7 Version 3 Data Types to PostgreSQL. Computing Research Repository, 2010, vol. abs/1003.3370.
6. Guliato D., de Melo E.V., Rangayyan R.M., Soares R.C. POSTGRESQL-IE: An Image-handling Extension for PostgreSQL. Journal of Digital Imaging, 2009, vol. 22, no. 2, pp. 149 - 165.
7. Levshin D.V., Markov A.S. Algorithms for Integrating PostgreSQL with the Semantic Web. Programming and Computer Software, 2009, vol. 35, no. 3, pp. 136 - 144.
8. Lee R., Zhou M. Extending PostgreSQL to Support Distributed/Heterogeneous Query Processing. Database Systems for Advanced Applications. Lecture Notes in Computer Science. 2007, vol. 4443, pp. 1086 - 1097.
9. Paes M., Lima A.A.B., Valduriez P., Mattoso M. High-Performance Query Processing of a Real-World OLAP Database with ParGRES. VECPAR, Lecture Notes in Computer Science, 2008, vol. 5336, pp. 188-200.
10. Kotowski N., Lima A.A.B, Pacitti E., Valduriez P., Mattoso M. Parallel Query Processing for OLAP in Grids. Concurrency and Computation: Practice and Experience, 2008, vol. 20, no. 17, pp. 2039 - 2048.
11. DeWitt D.J., Gray J. Parallel Database Systems: The Future of High Performance Database Systems. Communications of the ACM, 1992, vol. 35, no. 6, pp. 85 - 98.
12. Sokolinsky L.B. Organization of Parallel Query Processing in Multiprocessor Database Machines with Hierarchical Architecture. Programming and Computer Software, 2001, vol. 27, no. 6, pp. 297 - 308.
13. Lepikhov A.V., Sokolinsky L.B. Query Processing in a DBMS for Cluster Systems. Programming and Computer Software, 2010, vol. 36, no. 4, pp. 205 - 215.