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Buffering in query evaluation over XML streams
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Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems table of contents
Baltimore, Maryland
SESSION: Research session 6: complexity & performance evaluation / data stream management table of contents
Pages: 216 - 227  
Year of Publication: 2005
ISBN:1-59593-062-0
Authors
Ziv Bar-Yossef  Technion, Haifa, Israel
Marcus Fontoura  IBM Almaden, San Jose, CA
Vanja Josifovski  IBM Almaden, San Jose, CA
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGMOD: ACM Special Interest Group on Management of Data
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 42,   Citation Count: 14
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ABSTRACT

All known algorithms for evaluating advanced XPath queries (e.g., ones with predicates or with closure axes) on XML streams employ buffers to temporarily store fragments of the document stream. In many cases, these buffers grow very large and constitute a major memory bottleneck. In this paper, we identify two broad classes of evaluation problems that independently necessitate the use of large memory buffers in evaluation of queries over XML streams: (1) full-fledged evaluation (as opposed to just filtering) of queries with predicates; (2) evaluation (whether full-fledged or filtering) of queries with "multi-variate" predicates.We prove quantitative lower bounds on the amount of memory required in each of these scenarios. The bounds are stated in terms of novel document properties that we define. We show that these scenarios, in combination with query evaluation over recursive documents, cover the cases in which large buffers are required. Finally, we present algorithms that match the lower bounds for an important fragment of XPath.


REFERENCES

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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CITED BY  14
Collaborative Colleagues:
Ziv Bar-Yossef: colleagues
Marcus Fontoura: colleagues
Vanja Josifovski: colleagues