Temporal support for persistent stored modules

Richard T. Snodgrass; Dengfeng Gao; Rui Zhang; Stephen W. Thomas

doi:10.1109/ICDE.2012.70

Temporal support for persistent stored modules

Richard T. Snodgrass, Dengfeng Gao, Rui Zhang, Stephen W. Thomas

Computer Science

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

We show how to extend temporal support of SQL to the Turing-complete portion of SQL, that of persistent stored modules (PSM). Our approach requires minor new syntax beyond that already in SQL/Temporal to define and to invoke PSM routines, thereby extending the current, sequenced, and non-sequenced semantics of queries to PSM routines. Temporal upward compatibility (existing applications work as before when one or more tables are rendered temporal) is ensured. We provide a transformation that converts Temporal SQL/PSM to conventional SQL/PSM. To support sequenced evaluation of PSM routines, we define two different slicing approaches, maximal slicing and per-statement slicing. We compare these approaches empirically using a comprehensive benchmark and provide a heuristic for choosing between them.

Original language	English (US)
Article number	6228077
Pages (from-to)	114-125
Number of pages	12
Journal	Proceedings - International Conference on Data Engineering
DOIs	https://doi.org/10.1109/ICDE.2012.70
State	Published - Jul 30 2012
Event	IEEE 28th International Conference on Data Engineering, ICDE 2012 - Arlington, VA, United States Duration: Apr 1 2012 → Apr 5 2012

ASJC Scopus subject areas

Software
Signal Processing
Information Systems

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10.1109/ICDE.2012.70

Cite this

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title = "Temporal support for persistent stored modules",

abstract = "We show how to extend temporal support of SQL to the Turing-complete portion of SQL, that of persistent stored modules (PSM). Our approach requires minor new syntax beyond that already in SQL/Temporal to define and to invoke PSM routines, thereby extending the current, sequenced, and non-sequenced semantics of queries to PSM routines. Temporal upward compatibility (existing applications work as before when one or more tables are rendered temporal) is ensured. We provide a transformation that converts Temporal SQL/PSM to conventional SQL/PSM. To support sequenced evaluation of PSM routines, we define two different slicing approaches, maximal slicing and per-statement slicing. We compare these approaches empirically using a comprehensive benchmark and provide a heuristic for choosing between them.",

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AU - Snodgrass, Richard T.

AU - Gao, Dengfeng

AU - Zhang, Rui

AU - Thomas, Stephen W.

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N2 - We show how to extend temporal support of SQL to the Turing-complete portion of SQL, that of persistent stored modules (PSM). Our approach requires minor new syntax beyond that already in SQL/Temporal to define and to invoke PSM routines, thereby extending the current, sequenced, and non-sequenced semantics of queries to PSM routines. Temporal upward compatibility (existing applications work as before when one or more tables are rendered temporal) is ensured. We provide a transformation that converts Temporal SQL/PSM to conventional SQL/PSM. To support sequenced evaluation of PSM routines, we define two different slicing approaches, maximal slicing and per-statement slicing. We compare these approaches empirically using a comprehensive benchmark and provide a heuristic for choosing between them.

AB - We show how to extend temporal support of SQL to the Turing-complete portion of SQL, that of persistent stored modules (PSM). Our approach requires minor new syntax beyond that already in SQL/Temporal to define and to invoke PSM routines, thereby extending the current, sequenced, and non-sequenced semantics of queries to PSM routines. Temporal upward compatibility (existing applications work as before when one or more tables are rendered temporal) is ensured. We provide a transformation that converts Temporal SQL/PSM to conventional SQL/PSM. To support sequenced evaluation of PSM routines, we define two different slicing approaches, maximal slicing and per-statement slicing. We compare these approaches empirically using a comprehensive benchmark and provide a heuristic for choosing between them.

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Temporal support for persistent stored modules

Abstract

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