ACM Turing award lectures
Clustera: an integrated computation and data management system
Proceedings of the VLDB Endowment
Extend UDF Technology for Integrated Analytics
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Cooperating SQL Dataflow Processes for In-DB Analytics
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
Query engine grid for executing SQL streaming process
Globe'11 Proceedings of the 4th international conference on Data management in grid and peer-to-peer systems
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SFL (pronounced as Sea-Flow) is an analytics system that supports a declarative language that extends SQL for specifying the dataflow of data-intensive analytics. The extended SQL language is motivated by providing a top-level representation of the converged platform for analytics and data management. Due to fast data access and reduced data transfer, such convergence has become the key to speed up and scale up data intensive BI applications. A SFL query is constructed from conventional queries in terms of Function Forms (FFs). While a conventional SQL query represents a dataflow tree, a SFL query represents a more general dataflow graph. We support SFL query execution by tightly integrating it with the evaluation of its component queries to minimize the overhead of data retrieval, copying, moving and buffering, which actually turns a query engine to a generalized dataflow engine. The experimental results based on a prototype built by extending the PostgreSQL engine are discussed.