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ABSTRACT
XML stream applications bring the challenge of efficiently
processing queries on sequentially accessible token-based data.
While the automata model is naturally suited for pattern matching
on tokenized XML streams, the algebraic model in contrast is a
well-established technique for set-oriented processing of
self-contained tuples. However, neither automata nor algebraic
models are well-equipped to handle both computation paradigms.
The goal of the Raindrop project is to accommodate these
two paradigms within one algebraic framework to take advantage of
both. In our query model, both tokenized data and self-contained
tuples are supported in a uniform manner. Query plans can be
flexibly rewritten using equivalence rules to change what
computation is done using tokenized data versus tuples. This paper
highlights the four abstraction levels in Raindrop, namely,
semantics-focused plan, stream logical plan, stream physical
plan and execution plan. Various optimization techniques
are provided at each level. The necessity of such a uniform and
layered plan is shown by experimental study
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Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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