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Parallel database management refers to the management of data in a multiprocessor computer and is done by a parallel database system, i.e., a full-fledge DBMS implemented on a multiprocessor computer. The basic principle employed by parallel DBMS is to partition the data across multiprocessor nodes, in order to increase performance through parallelism and availability through replication. This enables supporting very large databases with very high query or transaction loads.
Parallel database systems can exploit distributed database techniques. In particular, database partitioning is somewhat similar to database fragmentation. Essentially, the solutions for transaction management, i.e., distributed concurrency control, reliability, atomicity, and replication, can be reused. However, the critical issues for parallel database systems are data placement, parallel query processing (including optimization and execution) and load...
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DeWitt D.J. and Gray J. Parallel database systems: the future of high performance database systems. Commun. ACM, 35(6):85–98, 1992.
Özsu T. and Valduriez P. Distributed and parallel database systems – Technology and current state-of-the-art. ACM Comput. Surv., 28(1):125–128, 1996.
Özsu M.T. and Valduriez P. Principles of Distributed Database Systems, 3rd edition. Prentice Hall, 2009.
Valduriez P. Parallel database systems: the case for shared-something. In Proc. 9th Int. Conf. on Data Engineering, 1993, pp. 460–465.
Valduriez P. and Pacitti E. Parallel Database Systems. In Handbook of Database Technology, J. Hammer, M. Scheider (eds.). CRC Press, Boca Raton, FL, 2007.
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Valduriez, P. (2009). Parallel Database Management. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1074
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DOI: https://doi.org/10.1007/978-0-387-39940-9_1074
Publisher Name: Springer, Boston, MA
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