Parallelizing user-defined functions in distributed object-relational DBMS

Full support of parallelism in object-relational database systems (ORDBMSs) is desired. The parallelization techniques developed for relational database systems are not adequate for ORDBMS because of the introduction of complex abstract data types and operations on ordered domains. In this paper, we consider a data stream paradigm and develop a query parallelization framework that exploits characteristics of user-defined functions in a ORDBMS during query optimization. By introducing the concept of windows and abstract data type orderings, we develop a novel approach for parallelizing user-defined functions in a distributed ORDBMS environment. The implementation issues in providing query services in ordered domains are also discussed.

[1]  Miron Livny,et al.  The Case for Enhanced Abstract Data Types , 1997, VLDB.

[2]  Michael Stonebraker,et al.  Object-Relational DBMSs: The Next Great Wave , 1995 .

[3]  Praveen Seshadri,et al.  PREDATOR: an OR-DBMS with enhanced data types , 1997, SIGMOD '97.

[4]  Richard R. Muntz,et al.  Scalable Exploratory Data Mining of Distributed Geoscientific Data , 1996, KDD.

[5]  Mark Levene,et al.  OSQL: An Extension to SQL to Manipulate Ordered Relational Databases , 1997, NGITS.

[6]  F NaughtonJeffrey,et al.  Query execution techniques for caching expensive methods , 1996 .

[7]  Kenneth Salem,et al.  A Language for Manipulating Arrays , 1997, VLDB.

[8]  Jeffrey D. Uuman Principles of database and knowledge- base systems , 1989 .

[9]  Douglas Stott Parker,et al.  SQL/LPP: A Time Series Extension of SQL Based on Limited Patience Patterns , 1999, DEXA.

[10]  Goetz Graefe,et al.  The Volcano optimizer generator: extensibility and efficient search , 1993, Proceedings of IEEE 9th International Conference on Data Engineering.

[11]  Guy M. Lman Grammar-like Functional Rules for Representing Query Optimization Alternatives , 1998 .

[12]  Hamid Pirahesh,et al.  Starburst Mid-Flight: As the Dust Clears , 1990, IEEE Trans. Knowl. Data Eng..

[13]  Jeffrey D. Ullman,et al.  Principles of database and knowledge-base systems, Vol. I , 1988 .

[14]  Bernhard Mitschang,et al.  On parallel processing of aggregate and scalar functions in object-relational DBMS , 1998, SIGMOD '98.

[15]  Jeffrey F. Naughton,et al.  Query execution techniques for caching expensive methods , 1996, SIGMOD '96.

[16]  Goetz Graefe,et al.  Extensible Query Optimization and Parallel Execution in Volcano , 1991, Query Processing for Advanced Database Systems.

[17]  Miron Livny,et al.  Sequence query processing , 1994, SIGMOD '94.

[18]  Richard R. Muntz,et al.  On reconfiguring query execution plans in distributed object-relational DBMS , 1998, Proceedings 1998 International Conference on Parallel and Distributed Systems (Cat. No.98TB100250).

[19]  Michael Stonebraker,et al.  Predicate migration: optimizing queries with expensive predicates , 1992, SIGMOD Conference.

[20]  R. Muntz,et al.  Optimization of User-De ned Functions in Distributed Object-Relational DBMS , 1999 .

[21]  Ting Yu Leung,et al.  Query processing and optimization in temporal database systems , 1992 .

[22]  Michael Stonebraker,et al.  Object-Relational DBMSs, Second Edition , 1998 .

[23]  Patrick Valduriez,et al.  Principles of Distributed Database Systems , 1990 .

[24]  Richard R. Muntz,et al.  Query processing for temporal databases , 1990, [1990] Proceedings. Sixth International Conference on Data Engineering.