3 "Great" Data Structures in DBMS Enviornment

The Three “Great” Data Structures: It has become popular to classify DBMS’s to three groups based upon the underlying data structure class. The understanding of each type is based upon a particular system or proposal. Language is associated with these examples of each data structure class.

It is a common mistake to evaluate the data structure by the language available for processing that structure. Comparing the low level languages of IMS and the CODAYSL DML to the high level languages defined on the relational data model incorrectly creates a biased judgment of the underlying data structure. These three classes do not constitute a good taxonomy.

With this brief introduction to taxonomy of data structures, the following sections define each basic data structure class beginning with the single flat file. Each data structure class is explained using a common example relating to personal and organizational data.

 

Single Flat File Data Structure:
A file is a collection of data bout a set of entities which possess some common characteristics. By possessing some common characteristics the entities constitute an entity class. Proper interpretation of the file centers on the type of entity it describes. A flat file is conceptually a two dimensional array. An attribute is a named characteristic of entity class. The file describes an entity by the values of the attributes in its row. A single row of attribute values is called an entry or record of the file.

The definition of a single entry type defines all entries in the single file. The definition of a single entry type defines all entries in the single. An entry in the file describes an entity in the real world. Five characteristics serve to define a file. Each characteristic relates to a particular term or concept. Sometimes it is more convenient to represent only the type of data in a particular flat file without showing the actual data. A schema representation does this.

At a minimum, the schema for a flat file is essentially just a list of the attributes used to describe each entity in the file. This minimum schema can be augmented with additional information about the flat file such as a description of the type of values for each attribute, the size of each value, the value domain for each attribute either as a range declaration or an enumeration, and a description of the attribute. In general, schema information is any information about the file which can be stated in terms of all the entries in the file. It is the constant or invariant information factored out of each entry. Such information then need only be stored once for the whole file- as the schema.

 

Homogenous Flat File:
A homogenous flat file is a special case of the flat file in which every entry contains the same set of data items and each value appears in a fixed relative position in each entry instance. A homogeneous flat file is generally easier for a user to comprehend and easier for the system to process.

 

Composite Flat File:
A composite flat file results when a user attempts to define a flat file to contain data pertaining to multiple types of entities. The main symptom of a composite flat file is the existence of many irrelevant item values in the entries. Rather than associate each entry with one specific entity type, each entry could describe a person along with the data pertaining to the organization in which that person works. This results in redundant data since the same organizational data is repeated for each person working in the same organizational unit. This can also present some problems on retrieval.

For example, it is no longer possible to sum the BUDGET data item to obtain the total budget for the organization in which that person works. This results in redundant data since the same organizational data is repeated for each person working in the same organizational unit. This can also present some problems on retrieval. For example, it is no longer possible to sum the BUDGET data item to obtain the total budget for the organization. One alternative is to store the budget data only with the HEAD person of each organizational unit. Note that the schema representation of these two variants is the same, indicating that additional information is necessary to properly define the semantics of the flat file data structure.

 

The schema or definition of a single flat file is essentially a list of the attributes used to describe each entity instance in the class of entities. In other words, the schema is a list of data items contained in each entry or record in the file. The schema can also include additional information which is common across all entries in the file, such as item value type and size.




| Regression Analysis Data - Different From The Rest | Learn About Data Collection Methodology | Is Primary Data Collection Right For Your Business | Automated Data Collection Systems – Its Uses | Data Collection Methods Set A Guideline For The Nowise | Free Data Collection Software: A Good Start For Starters | | Are You Looking For The Best Data Collection Software | Updating Your Data Collection Tools | Role Of Computers In Maintenance Data Collection System Reports | Online Data Collection And Your Business In The Long Run | Choosing The Right Steps For Planning Your Project Research | Understanding What Survey Data Collection Is |















FREE Subscription

Stay Current With the Latest Trends & Developments Realted to Management. Signup for Our Newsletter and Receive New Articles Through Email

Note: We never rent, trade, or sell our email lists to anyone. We assure that your privacy is respected and protected.