Autor/Autorin: Sakr Sherif
Dr. Sherif Sakr is a Research Scientist in the Software Systems Research Group at National ICT Australia (NICTA), ATP lab, Sydney, Australia. He received his PhD degree in Computer Science in 2007. In 2011, Sherif held a Visiting Researcher position in Microsoft Research Laboratories, Redmond, WA, USA.
XQuery is the standard XML query language, significa t effort has been made in developing efficient implementations of XQuery query processor.This thesis describes a purely relational implementation of an XQuery processor which exploits the well-known maturity and performance acceleration techniques of the relational database technology to translate XQuery expressions into their equivalent SQL evaluationillegalscripts. The generated SQL evaluationillegalscripts can be executed on any conventional relational database management systems with no need for any changes in its kernel or any other special requirements. In addition, this thesis presents a novel framework for estimating the cardinality of XQuery expressions as well as its sub-expressions. Although cardinality size estimation is very important on its own, it is also very crucial for an effective query optimization process. This thesis presents an integrated framework for exploiting the available estimated cardinality information to provide the RDBMS query optimizers with hints for selecting the best alternative execution plan for the SQL evaluationillegalscripts of the input XQuery expression.
XQuery is the standard XML query language, significa t effort has been made in developing efficient implementations of XQuery query processor.This thesis describes a purely relational implementation of an XQuery processor which exploits the well-known maturity and performance acceleration techniques of the relational database technology to translate XQuery expressions into their equivalent SQL evaluationillegalscripts. The generated SQL evaluationillegalscripts can be executed on any conventional relational database management systems with no need for any changes in its kernel or any other special requirements. In addition, this thesis presents a novel framework for estimating the cardinality of XQuery expressions as well as its sub-expressions. Although cardinality size estimation is very important on its own, it is also very crucial for an effective query optimization process. This thesis presents an integrated framework for exploiting the available estimated cardinality information to provide the RDBMS query optimizers with hints for selecting the best alternative execution plan for the SQL evaluationillegalscripts of the input XQuery expression.
Dr. Sherif Sakr is a Research Scientist in the Software Systems Research Group at National ICT Australia (NICTA), ATP lab, Sydney, Australia. He received his PhD degree in Computer Science in 2007. In 2011, Sherif held a Visiting Researcher position in Microsoft Research Laboratories, Redmond, WA, USA.
Über den Autor
Dr. Sherif Sakr is a Research Scientist in the Software Systems Research Group at National ICT Australia (NICTA), ATP lab, Sydney, Australia. He received his PhD degree in Computer Science in 2007. In 2011, Sherif held a Visiting Researcher position in Microsoft Research Laboratories, Redmond, WA, USA.
Klappentext
XQuery is the standard XML query language, significa t effort has been made in developing efficient implementations of XQuery query processor.This thesis describes a purely relational implementation of an XQuery processor which exploits the well-known maturity and performance acceleration techniques of the relational database technology to translate XQuery expressions into their equivalent SQL evaluationillegalscripts. The generated SQL evaluationillegalscripts can be executed on any conventional relational database management systems with no need for any changes in its kernel or any other special requirements. In addition, this thesis presents a novel framework for estimating the cardinality of XQuery expressions as well as its sub-expressions. Although cardinality size estimation is very important on its own, it is also very crucial for an effective query optimization process. This thesis presents an integrated framework for exploiting the available estimated cardinality information to provide the RDBMS query optimizers with hints for selecting the best alternative execution plan for the SQL evaluationillegalscripts of the input XQuery expression.
