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Lawsuits of the thirtieth Annual foreign convention on Very huge info Bases held in Toronto, Canada on August 31 - September three 2004. equipped through the VLDB Endowment, VLDB is the preferable overseas convention on database know-how.

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Extra resources for Proceedings 2004 VLDB Conference: The 30th International Conference on Very Large Databases

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The incremental benefit of adding a page will be very high until \A\ pages, and then one can expect to see a change in the slope at this point. By allocating at least 1^1 pages, we avoid the penalty of operating in the initial high miss-rate region. The TDD heuristic chooses to allocate a minimum of \A\ pages to Suffixes and Temp first. We suggest allocating two pages to the Tree array. Two pages allow a parent node, possibly written to a previous page and then pushed onto the stack for later processing, to be accessed without replacing the current active page.

An illustrative graph of the buffer cache miss pattern for each data structure is shown in Figure 4. In this figure, the X-axis represents the number of pages allocated to the buffer as a percentage of the total size of the data structure. 40 String LJ Suffix I Temp I 4 Analysis Tree In this section, we analyze the advantages and the disadvantages of using the TDD technique for various types and sizes of string data. We also describe how the design choices we have made in TDD overcome the performance bottlenecks present in other proposed techniques.

TDD is a better bet in all other cases. 4 5 Experimental Evaluation In this section, we present the results of an extensive experimental evaluation of the different suffix tree construction techniques. In addition to TDD, we compare Ukkonen's algorithm [32] for in-memory construction performance, and Hunt's algorithm [18] for disk-based construction performance. Ukkonen's and Hunt's algorithms are considered the best known suffix tree construction algorithms for the in-memory case and the disk based case respectively.

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