In many planning situations, computation itself becomes a resource to be planned and scheduled. We model such computational resources as conventional resources which are used by control-flow actions, e.g., to direc...In many planning situations, computation itself becomes a resource to be planned and scheduled. We model such computational resources as conventional resources which are used by control-flow actions, e.g., to direct the planning process. Control-flow actions and conventional actions are planned/scheduled in an integrated way and can interact with each other. Control-flow actions are then executed by the planning engine itself. The approach is illustrated by examples, e.g., for hierarchical planning, in which tasks that are temporally still far away impose only rough constraints on the current schedule, and control-flow tasks ensure that these tasks are refined as they approach the current time. Using the same mechanism, anytime algorithms can change appropriate search methods or parameters over time, and problems like scheduling critical time-outs for garbage collection can be made part of the planning itself.展开更多
This work aims to reduce queries on big data to computations on small data,and hence make querying big data possible under bounded resources.A query Q is boundedly evaluable when posed on any big dataset D,there exist...This work aims to reduce queries on big data to computations on small data,and hence make querying big data possible under bounded resources.A query Q is boundedly evaluable when posed on any big dataset D,there exists a fraction DQ of D such that Q(D)=Q(DQ),and the cost of identifying DQ is independent of the size of D.It has been shown that with an auxiliary structure known as access schema,many queries in relational algebra(RA)are boundedly evaluable under the set semantics of RA.This paper extends the theory of bounded evaluation to RAaggr,i.e.,RA extended with aggregation,under the bag semantics.(1)We extend access schema to bag access schema,to help us identify DQ for RAaggr queries Q.(2)While it is undecidable to determine whether an RAaggr query is boundedly evaluable under a bag access schema,we identify special cases that are decidable and practical.(3)In addition,we develop an effective syntax for bounded RAaggr queries,i.e.,a core subclass of boundedly evaluable RAaggr queries without sacrificing their expressive power.(4)Based on the effective syntax,we provide efficient algorithms to check the bounded evaluability of RAaggr queries and to generate query plans for bounded RAaggr queries.(5)As proof of concept,we extend PostgreSQL to support bounded evaluation.We experimentally verify that the extended system improves performance by orders of magnitude.展开更多
文摘In many planning situations, computation itself becomes a resource to be planned and scheduled. We model such computational resources as conventional resources which are used by control-flow actions, e.g., to direct the planning process. Control-flow actions and conventional actions are planned/scheduled in an integrated way and can interact with each other. Control-flow actions are then executed by the planning engine itself. The approach is illustrated by examples, e.g., for hierarchical planning, in which tasks that are temporally still far away impose only rough constraints on the current schedule, and control-flow tasks ensure that these tasks are refined as they approach the current time. Using the same mechanism, anytime algorithms can change appropriate search methods or parameters over time, and problems like scheduling critical time-outs for garbage collection can be made part of the planning itself.
基金supported in part by Royal Society YVolfson Research Merit Award WRM/R1/180014,ERC 652976,EPSRC EP/M025268/1,Shenzhen Institute of Computing Sciences,and Beijing Advanced Innovation Center for Big Data and Brain Computing.
文摘This work aims to reduce queries on big data to computations on small data,and hence make querying big data possible under bounded resources.A query Q is boundedly evaluable when posed on any big dataset D,there exists a fraction DQ of D such that Q(D)=Q(DQ),and the cost of identifying DQ is independent of the size of D.It has been shown that with an auxiliary structure known as access schema,many queries in relational algebra(RA)are boundedly evaluable under the set semantics of RA.This paper extends the theory of bounded evaluation to RAaggr,i.e.,RA extended with aggregation,under the bag semantics.(1)We extend access schema to bag access schema,to help us identify DQ for RAaggr queries Q.(2)While it is undecidable to determine whether an RAaggr query is boundedly evaluable under a bag access schema,we identify special cases that are decidable and practical.(3)In addition,we develop an effective syntax for bounded RAaggr queries,i.e.,a core subclass of boundedly evaluable RAaggr queries without sacrificing their expressive power.(4)Based on the effective syntax,we provide efficient algorithms to check the bounded evaluability of RAaggr queries and to generate query plans for bounded RAaggr queries.(5)As proof of concept,we extend PostgreSQL to support bounded evaluation.We experimentally verify that the extended system improves performance by orders of magnitude.
