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On the memory requirements of XPath evaluation over XML streams
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Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems table of contents
Paris, France
SESSION: Query execution and optimization table of contents
Pages: 177 - 188  
Year of Publication: 2004
ISBN:158113858X
Authors
Ziv Bar-Yossef  IBM Almaden, San Jose, CA
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): 2,   Downloads (12 Months): 28,   Citation Count: 17
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ABSTRACT

The important challenge of evaluating XPath queries over XML streams has sparked much interest in the past two years, A number of algorithms have been proposed, supporting wider fragments of the query language, and exhibiting better performance and memory utilization. Nevertheless, all the algorithms known to date use a prohibitively large amount of memory for certain types of queries. A natural question then is whether this memory bottleneck is inherent or just an artifact of the proposed algorithms.In this paper we initiate the first systematic and theoretical study of lower bounds on the amount of memory required to evaluate XPath queries over XML streams. We present a general lower bound technique, which given a query, specifies the minimum amount of memory that any algorithm evaluating the query on a stream would need to incur. The lower bounds are stated in terms of new graph-theoretic properties of queries. The proof is based on tools from communication complexity.We then exploit insights learned from the lower bounds to obtain a new algorithm for XPath evaluation on streams. The algorithm uses space close to the optimum. Our algorithm deviates from the standard paradigm of using automata or transducers, thereby avoiding the need to store large transition tables.


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  17
Collaborative Colleagues:
Ziv Bar-Yossef: colleagues
Marcus Fontoura: colleagues
Vanja Josifovski: colleagues