Abstract: A system and methodology for parallel query optimization using semantic-based partitioning is described. In one embodiment, for example, in a database system comprising a database storing data in database tables, a method is described for improving query performance by dynamically partitioning the data, the method comprises steps of: receiving a query requesting data from the database; generating a plurality of subplans for executing the query, each subplan including one or more operators for performing relational operations; adding operators for partitioning data and performing a given relational operation in parallel to at least some of the plurality of subplans; and building a plan for execution of the query based, at least in part, upon selecting subplans having favorable execution costs.

Abstract: A database system with methodology for parallel schedule generation in a query optimizer is described. In one embodiment, for example, in a database system, a method is described for parallel optimization of a query, the method comprises steps of: generating a plurality of parallel plans for obtaining data requested by the query, the parallel plans including parallel operators for executing portions of the query in parallel; adjusting parallel operators of each parallel plan if necessary based on resources available for executing the query; creating a schedule for each parallel plan indicating a sequence for execution of operators of each parallel plan; determining execution cost of each parallel plan based on its schedule; and selecting a particular parallel plan having lowest execution cost for obtaining data requested by the query.