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5. Record processing using tree methods

Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 59)

Abstract

A data structure has been defined to store trees and tries on a direct access storage device. It has been used to show how an internal tree searching algorithm can be modified to search trees on a direct access storage device. This data structure is simple and easier to manage that the B-tree and B*-tree structures.

The approximation introduced to calculate the number of accesses using binary search trees is close to the simulation results presented by Muntz and Uzgalis [50]. Muntz and Uzgalis assumed that after the first two pages each path requires a new page reference. This assumption is not used in the method presented in this monograph. For this reason the simulation results are lower than the calculated results of the new method. Figure 5.12 illustrates the new binary search tree results and compares them to those of Muntz and Uzgalis simulations.

The average number of accesses have been calculated for a trie stored on a direct access device to locate a symbol sequence. The performance measures calculated show that the method is efficient. Any efficiency desired is controlled by the user and the constraints of the direct access storage device.

Seidmore and Weinberg [62] calculated the mean search time for a trie stored as a linked structure in main memory. Modifying this method to store the list on a direct access storage device gives reasonable average search times. The method introduced in this chapter for the trie gives a more realistic average search time than the modified Seidmore and Weinberg method.

Keywords

Binary Search Tree Disk Address 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1978

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