On Reconfiguring Query Execution Plans in Distributed Object-Relational DBMS

Massive database sizes and growing demands for decision support and data mining result in long-running queries in extensible Object-Relational DBMS, particularly in decision support and data warehousing analysis applications. Parallelization of query evaluation is often required for acceptable performance. Yet queries are frequently processed suboptimally due to (1) only coarse or inaccurate estimates of the query characteristics and database statistics available prior to query evaluation; (2) changes in system connguration and resource availability during query evaluation. In a distributed environment, dynamically reconnguring query execution plans (QEPs), which adapts QEPs to the environment as well as the query characteristics, is a promising means to signiicantly improve query evaluation performance. Based on an operator classiication, we propose an algorithm to coordinate the steps in a reconnguration and introduce alternatives for execution context checkpointing and restoring. A syntactic extension of SQL to expose the relevant characteristics of user deened functions in support of dynamic reconngu-ration is proposed. An example from the experimental system is presented.