# Data Structure - Tree-Based Structures, and Hash Tables – Coursework Example

The paper “ Data Structure - Tree-Based Structures, and Hash Tables” is a spectacular variant of coursework on logic & programming. The data  structure is the central element of databases. It is the product of the application of certain tools and techniques developed to link data items within records and between records of the same file and between records of various files. The right choice and design of data structure facilitate efficient and effective access and manipulation of records in a database (Panneerselvam 40). The data structures connecting records of various files and connecting the records of a file for a given record of a different file can be categorized as stack data structure, queue data structure, sorted list data structure, ring data structure, inverted list data structure, multi-list data structure, and tree data structure.

Although some provide multidimensional data structures such as variants of quadtrees and R-trees and a few also support bit-vectors and multi-table join indexes, most database systems support B-Trees and Hash tables. In practice, these two data structures are most often used in databases (Shasha and Bonnet 82).   The Tree StructureA ‘ Tree’ is a unique breed of the network in which there is no cycle.

It is helpful in organizing data, particularly in circumstances when there is a hierarchical relationship between several entities. The tree structure is, in fact, the inverted image of an actual tree where the root, at the top, is at level zero. Except for terminal nodes, there are a set or ‘ filial set’ of offspring or siblings at every node in the tree, and each terminal node is considered a ‘ leaf’ . When an access path in a tree structure commenced from the root node, it constantly moves downward until it encounters a terminal node.

When a database employs a tree structure, the set of nodes at each level will correspond to a segment thus the number of segments in a tree will be similar to the number of levels in a simple tree. Since multiple trees may have one or more than one segment at some levels of the tree, there are more segments in multiple trees. Every path beginning from the root node to each terminal node or leaf is regarded as a record in the tree data structure since every segment of the tree symbolizes an entity of a real-life system.

However, the number of files in a tree-based database is only one. There are two types of tree data structures, a binary tree, and a B-tree or a Balanced Tree. The maximum number of siblings in the binary tree for a non-leaf node is two. This means that the maximum number of branches originating from any non-leaf node is two. The number of branches originating from a node in a B-Tree is limitless.

However, on average, the number is roughly similar for non-leaf nodes, which allow access to any record in a tree within a specified number of accesses. In reality, to retrieve all keys in one of the terminal nodes, a user can resolve the size of the filial set and the number of levels of the B-Tree for a given number of accesses backward (Panneerselvam 61).

References

5. Reference

Cormen Thomas. Introduction to Algorithms.U.S: MIT Press, 2003

D'Hollander, Joubert G. R., Völpel R., Peters F. J., and Trottenberg U. Parallel Computing: Fundamentals, Applications, and New Directions. Netherlands: Elsevier, 1998

Grand Mark and Merrill Brad. Visual Basic Design Patterns: Reusable Design Patterns Illustrated. U.S.: John Wiley and Sons, 2005

Gudukbay U. Advances in Computer and Information Sciences '98. Turkey: IOS Press, 1998

Haines Steven and Potts Stephen. Java 2 Primer Plus. U.S.: Sams Publishing, 2002

Keogh James and Davidson Ken. Data Structures Demystified: A Self-Teaching Guide. U.S.: McGraw-Hill Professional, 2004

Khosrowpour Mehdi. Innovations Through Information Technology: 2004 Information Resources Management Association International Conference, New Orleans, Louisiana, USA, May 23-26, 2004, U.S.: Idea Group Inc (IGI), 2004

McBee Jim and Gerber Barry. Microsoft Exchange Server 2003: 24 Seven. U.S.: Wiley, 2004

Mehta Dinesh and Sahni Sartaj. Handbook of Data Structures and Applications. U.S.: CRC Press, 2005

Panneerselvam R. Database Management Systems. India: PHI Learning Pvt. Ltd., 2004

Petkovic Dušan. SQL Server 2000: A Beginner's Guide. U.S.: McGraw-Hill Professional, 2000

Roman Steven. Access Database Design and Programming. U.S.: O'Reilly, 2002

Shasha Elliott Dennis and Bonnet Philippe. Database Tuning: Principles, Experiments, and Troubleshooting Techniques. U.S.: Morgan Kaufmann, 2003

Tucker Allen. Computer Science Handbook: Handbook. U.S.: CRC Press, 2004

Williams Ross Neil. Adaptive Data Compression. U.S.: Springer, 1990

Zawodny Jeremy and Balling Derek. High-Performance MySQL: Optimization, Backups, Replication, and Load Balancing. U.S.: O'Reilly, 2004