An implementation model for reasoning with complex objects
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Nested relation based database knowledge representation
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Parallel database systems: the future of high performance database systems
Communications of the ACM
Communications of the ACM
Integration of Data Mining with Database Technology
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Inter-Enterprise Collaborative Business Process Management
Proceedings of the 17th International Conference on Data Engineering
A Distributed OLAP Infrastructure for E-Commerce
COOPIS '99 Proceedings of the Fourth IECIS International Conference on Cooperative Information Systems
A Data-Warehouse/OLAP Framework for Scalable Telecommunication Tandem Traffic Analysis
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Scientific data management in the coming decade
ACM SIGMOD Record
Experiences with MapReduce, an abstraction for large-scale computation
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
Inside Microsoft SQL Server 2005: T-SQL Querying
Inside Microsoft SQL Server 2005: T-SQL Querying
Building a scalable web query system
DNIS'07 Proceedings of the 5th international conference on Databases in networked information systems
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A key issue in supporting the synthesis of data intensive computation and data management is to liberate users from low-level parallel programming, by specifying applications functionally independent of the underlying server infrastructure, and further, by providing high-level primitives to express the control flow of applying functions to data partitions. Currently only few such primitives, e.g. Map-Reduce and Cross-Apply, are available, and their expressive power is limited to "flat parallel computing". To deal with "structured parallel computing" where a function is applied to multiple objects with execution order dependencies, a general framework for creating and combining such primitives is required.We propose the SQL-FCF framework as the database centric solution to the above problem. We embed into SQL queries the Function Controlling Forms (FCFs) to specify the flow control of applying Table Valued Functions (TVFs) to multiple data partitions. We further support the extensibility of this framework by allowing new FCFs to be defined from existing ones with SQL phrases. Based on this approach, we provided a SQL based high-level interface for "structured parallel computing" in architecting a hydrologic scientific computation platform. Envisioning that the simple parallel computing primitives will evolve and form a general framework, our effort is a step towards that goal.