Interactive query processing partial query results dynamic user control during query execution adaptive query execution interactive data cleaning and transformation

 achieve interactive behavior by adapting the query execution  changing user interests  changing data source properties Adaptive query execution  S T R R S T R S T T S T R traditional query plan fine-granularity adaptation adaptive tuple ordering adaptive tuple and operator ordering

relational operators: logical abstractions –encapsulate multiple physical effects –inflexible in handling unexpected changes cannot gracefully adapt –access method/data source selection –join algorithm selection –resource allocation: e.g. memory –delays want to encapsulate at level of physical operators Granularity of Query Operators R Eddy P ind.jn hash jn S P RS

State Modules isolate (and share) state in State Modules (SteMs)  work sharing  query execution = routing thru sources, SteMs can adapt access methods, join algorithms gracefully  directly measure & adapt resource consumption P R Eddy P ind.j n hash jn R R Eddy P P