.NODE

Summary

Disk storage has two advantages over memory storage: it persists between program runs, and it has greater capacity. On the other hand, accessing data on disk can take a million times as long as accessing data in memory. When the disk is accessed, it is not much more expensive to read many elements than to read one.

Java provides many classes for reading from and writing to disk. These include Scanner and PrintWriter for text and ObjectInputStream and ObjectOutputStream for binary data. Most of these classes are in the java.io package. We can write an instance of any class to disk if the class implements the Serializable interface.

Strings (and hence files) can be compressed by defining short codes for frequently occurring text. Huffman encoding takes advantage of the frequencies of individual characters. LempelZiv encoding creates codes for longer substrings.

Data too big to fit in memory can be sorted externally using an algorithm based on merge sort.

The B-tree data structure is useful for maintaining a set of data too large to fit in memory. Each node in a B-tree can contain many elements. The associated algorithms ensure that the tree stays balanced and very shallow, minimizing the number of disk accesses needed to find, insert, or delete an element.


Part I: Object-Oriented Programming

Encapsulation

Polymorphism

Inheritance

Part II: Linear Structures

Stacks and Queues

Array-Based Structures

Linked Structures

Part III: Algorithms

Analysis of Algorithms

Searching and Sorting

Recursion

Part IV: Trees and Sets

Trees

Sets

Part V: Advanced Topics

Advanced Linear Structures

Strings

Advanced Trees

Graphs

Memory Management

Out to the Disk

Part VI: Appendices

A. Review of Java

B. Unified Modeling Language

C. Summation Formulae

D. Further Reading

Index





Data Structures and Algorithms in Java
Data Structures and Algorithms in Java
ISBN: 0131469142
EAN: 2147483647
Year: 2004
Pages: 216
Authors: Peter Drake
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