Aimed　at　the　problems　of　data　stream　query　processing,　a　scheduling　strategy　based　on　operator　priority　is　presented.　In　the　paper,　a　PriOperator　Model　is　designed　which　comprehensively　takes　the　factors　related　to　the　operators　and　the　system　running　state　into　consideration.　Through　simulating　the　relationship　between　the　operator　factors　by　means　of　Linear　Regression,　the　priorities　can　be　acquired　by　the　linear　function,　and　the　operators　are　normally　scheduled.　For　the　purpose　of　dynamically　modifying　the　operator　priority,　the　artificial　neural　network　learning　(ANN)　algorithm　is　also　introduced.　It　gives　a　modification　towards　the　operator　priority　according　to　the　system　performance.　Therefore,　the　dynamical　scheduling　of　operators　can　be　realized.　The　applications　of　the　strategy　over　the　model　reveal　their　effectiveness　over　the　memory　consumption　and　output　latency.