ASSIGN_01

HIERARCHICAL Vs. RELATIONAL


A hierarchy is an arrangement of items (objects, names, values, categories, etc.) in which the items are represented as being "above," "below," or "at the same level as" one another and with only one "neighbor" above and below each level. These classifications are made with regard to rank, importance, seniority, power status or authority. A hierarchy of power is called a power structure. Abstractly, a hierarchy is simply an ordered set or an acyclic graph.A hierarchy can link entities either directly or indirectly, and either vertically or horizontally. The only direct links in a hierarchy, insofar as they are hierarchical, are to one's immediate superior or to one of one's subordinates, although a system that is largely hierarchical can also incorporate other organizational patterns. Indirect hierarchical links can extend "vertically" upwards or downwards via multiple links in the same direction, following a path. All parts of the hierarchy which are not linked vertically to one another nevertheless can be "horizontally" linked through a path by traveling up the hierarchy to find a common direct or indirect superior, and then down again.



A relational database matches data by using common characteristics found within the data set. The resulting groups of data are organized and are much easier for people to understand.For example, a data set containing all the real-estate transactions in a town can be grouped by the year the transaction occurred; or it can be grouped by the sale price of the transaction; or it can be grouped by the buyer's last name; and so on.Relational databases are currently the predominant choice in storing financial records, manufacturing and logistical information, personnel data and much more.Strictly, a relational database is a collection of relations (frequently called tables). Other items are frequently considered part of the database, as they help to organize and structure the data, in addition to forcing the database to conform to a set of requirements.

MY_Idea_Is

PART II.
A. Discuss what you have learned and understood about what DBMS is,so far.

I have learned that DBMS is responsible in building up or managing database.
It is a collection of interrelated data together with a set of programs to access the data, also called database system, or simply database. The primary goal of such a system is to provide an environment that is both convenient and efficient to use in retrieving and storing information.A database management system (DBMS) is designed to manage a large body of information. Data management involves both defining structures for storing information and providing mechanisms for manipulating the information. In addition, the database system must provide for the safety of the stored information, despite system crashes or attempts at unauthorized access.



B.Define how each of the ff. fit and function within the framework or relational DBMS system.


*Data field- all area in a computer memory or program or screen.It is a place where you can store data. Commonly used to refer to a column in a database or a field in a data entry form or web form.The field may contain data to be entered as well as data to be displayed.

*Forms- a kind of specifications of which data types are you gonna use.

*Foreign key- the uniformity and simultaneous access for your datas.is a referential constraint between two tables. The foreign key identifies a column or a set of columns in one (referencing) table that refers to a column or set of columns in another (referenced) table. The columns in the referencing table must be the primary key or other candidate key in the referenced table. The values in one row of the referencing columns must occur in a single row in the referenced table. Thus, a row in the referencing table cannot contain values that don't exist in the referenced table (except potentially NULL). This way references can be made to link information together and it is an essential part of database normalization. Multiple rows in the referencing table may refer to the same row in the referenced table. Most of the time, it reflects the one (master table, or referenced table) to many (child table, or referencing table) relationship.

*Queries- Allow us to view data in different ways.is a form of questioning, in a line of inquiry.

*Records- The answered queries that you had put on or stored.

*Reports- Allow us to format a data.It is a document characterized by information or other content reflective of inquiry or investigation, which is tailored to the context of a given situation and audience.

MY_ASSINGMENT

Data Type is a set of data with values that have similar, predefined characteristics. Every variable and property value in Director is of a specific data type, and values returned by methods are of a specific data type.

A. What are they and what role do they play in database?

Abstract data types (ADT) or abstract data structure is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics. An ADT is defined indirectly, only by the operations that may be performed on it and by mathematical constraints on the effects (and possibly cost) of those operations .
Algebraic data types (sometimes also called a variant type[1]) is a datatype each of whose values is data from other datatypes wrapped in one of the constructors of the datatype. Any wrapped datum is an argument to the constructor. In contrast to other datatypes, the constructor is not executed and the only way to operate on the data is to unwrap the constructor using pattern matching.
Composite data types are data types which can be constructed in a program using its programming language's primitive data types and other composite types. The act of constructing a composite type is known as composition.


Primitive data types can refer to either of the following concepts.
a basic type is a data type provided by a programming language as a basic building block. Most languages allow more complicated composite types to be recursively constructed starting from basic types.
a built-in type is a data type for which the programming language provides built-in support.

B. Enumerate at least 3 DBMS Software.
Alpha Five is a relational database management system and Rapid Application Development system (RAD) for building Windows desktop and Web (including AJAX) applications.It is developed by Alpha Software, Inc., which has been continually producing end-user and developer database application software since 1982[1][2]. Alpha Five version 8 was a finalist in the Dr. Dobb's Jolt Awards for 2008 in the category of "Best Development environment"[3] and winner of the 2005 Product of the Year award for "Best Database" from CRN.com[4].
FileMaker Pro is a cross-platform relational database application from FileMaker Inc. (a subsidiary of Apple Inc.). It integrates a database engine with a GUI-based interface, allowing users to modify the database by dragging new elements into layouts/screens/forms.FileMaker evolved from a DOS application, but was then developed primarily for the Apple Macintosh. Since 1992 it has been available for Microsoft Windows as well as Mac OS, and can be used in a heterogeneous environment. It is available in desktop, server, and web-delivery configurations.
Firebird is an open source relational database management system that runs on GNU/Linux, Windows, and a variety of Unix platforms. The database forked from Borland's open source edition of InterBase in 2000, but since Firebird 1.5 the code has been largely rewritten.

MVvs.DATAF

Memory variable files are a way to store the status of memory variables that are currently stored in memory.A variable is a way of referring to a memory location used in a computer program. This memory location holds values- perhaps numbers or text or more complicated types of data like a payroll record.

Data field definition usually includes field structure (size of each field and whether it is a date, an integer, or a text field) and field organization (names and locations of data fields within a document record).A data field in a database that contains the date of the document.

MYCONTRAST

A. Data vs Information

* Data are pieces of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data (plural of "datum) are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and knowledge are derived.

* Information as a concept has a diversity of meanings, from everyday usage to technical settings. Generally speaking, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, and representation.

B. Computer Storage vs Data Storage

* Computer storage, often called storage or memory, refers to computer components, devices, and recording media that retain digital data used for computing for some interval of time. Computer data storage provides one of the core functions of the modern computer, that of information retention. It is one of the fundamental components of all modern computers, and coupled with a central processing unit (CPU, a processor), implements the basic computer model used since the 1940s.

C. Computer System vs Operating System

* A complete, working computer. The computer system includes not only the computer, but also any software and peripheral devices that are necessary to make the computer function. Every computer system, for example, requires an operating system.

* Operating system (commonly abbreviated to either OS or O/S) is an interface between hardware and user; it is responsible for the management and coordination of activities and the sharing of the resources of the computer. The operating system acts as a host for computing applications that are run on the machine. As a host, one of the purposes of an operating system is to handle the details of the operation of the hardware.

SORT

A.
1. Personal - Data Structure is a way of storing data in a computer. Their are many types of data structure like stacks, trees, lists, array, queues,graph and ect. It is an organization of mathematical and logical concepts of data. Data structure is a pit of information.

2. A data structure is a group of data elements grouped together under one name. These data elements, known as members, can have different types and different lengths.

3. Data structure is an organization of information, usually in memory, for better algorithm efficiency, such as queue, stack, linked list, heap, dictionary, and tree, or conceptual unity, such as the name and address of a person. It may include redundant information, such as length of the list or number of nodes in a subtree.

4. Data structure represent implementations or interfaces. A data structure can be viewed as an interface between two functions or as an implementations of methods to access storage that is organized according to the associated data type.

5. Data structure in programming refers to a scheme for organizing related pieces of information.

6. A data structure in computer science is a way of storing data in a computer so that it can be used efficiently. It is an organization of mathematical and logical concepts of data.

7. Data structure refers to a collection of facts usually collected as the result of experiences, observation of experiment, or processes within a computer system, or a set of premises.

8.Data structure may consist of numbers, words or images, particularly as measurements or observations of a set of variables.

9. Data structure is often viewed as a lowest level of abstraction from which information and knowledge are derived.

10. Data structure always refers to user and configuration. It is also a collection of processed information.

B.

1.Hash table

In computer science, a hash table, or a hash map, is a data structure that associates keys with values.The primary operation that hash functions support efficiently is a lookup: given a key (e.g., a person's name), find the corresponding value (e.g., that person's telephone number). It works by transforming the key using a hash function into a hash, a number that is used as an index in an array to locate the desired location ("bucket") where the values should be.In most cases the hash function is deliberately chosen to have pseudo-random properties, so that small changes of a key give a large and apparently random (although of course reproducible) effect on the hash returned. Because of this random effect, in some cases, the calculated index can be the same for two different keys (a "collision"); different hash table designs handle this issue in different ways.

Hash tables support the efficient lookup, insertion and deletion of elements in constant time on average (O(1)) that does not vary with the number of elements stored in the table; although may vary somewhat depending on how full the table is.

A hash table works by transforming the key using a hash function into a hash, a number that is used as an index in an array to locate the desired location ("bucket") where the values should be. The number is normally converted into the index by taking a modulo operation, or sometimes bit masking is used where the array size is a power of two. The optimal hash function for any given use of a hash table can vary widely, however, depending on the nature of the key.

Typical operations on a hash table include insertion, deletion and lookup (although some hash tables are precalculated so that no insertions or deletions, only lookups are done on a live system). These operations are all performed in amortized constant time, which makes maintaining and accessing a huge hash table very efficient.

An important property of a hash table is how "full" the table is, that is the ratio between the number of entries n and the size s of the hash table (i.e. the size of the array it uses to store values). The quotient n/s is therefore called the load factor of the hash table.Most hash table implementations only perform well if the load factor is kept in a certain range.

Hash tables store data in pseudo-random locations, so accessing the data in a sorted manner is a very time consuming operation. Other data structures such as self-balancing binary search trees generally operate more slowly (since their lookup time is O(log n)) and are rather more complex to implement than hash tables but maintain a sorted data structure at all times. See a comparison of hash tables and self-balancing binary search trees.

2. Files

A collection of data or information that has a name, called the filename. Almost all information stored in a computer must be in a file. There are many different types of files: data files, text files , program files, directory files, and so on. Different types of files store different types of information. For example, program files store programs, whereas text files store text.

A file information data structure (INFDS) can be defined for each file to make file exception/error and file feedback information available to the program. The file information data structure, which must be unique for each file, must be defined in the main source section. The same INFDS is used by all procedures using the files.

The INFDS contains the following feedback information:

• File Feedback (length is 80)
• Open Feedback (length is 160)
• Input/Output Feedback (length is 126)
• Device Specific Feedback (length is variable)
• Get Attributes Feedback (length is variable)

Note:

The get attributes feedback uses the same positions in the INFDS as the input/output feedback and device specific feedback. This means that if you have a get attributes feedback, you cannot have input/output feedback or device feedback, and vice versa.

The length of the INFDS depends on what fields you have declared in your INFDS. The minimum length of the INFDS is 80.

The file feedback information starts in position 1 and ends in position 80 in the file information data structure. The file feedback information contains data about the file which is specific to RPG. This includes information about the error/exception that identifies:

• The name of the file for which the exception/error occurred
• The record being processed when the exception/error occurred or the record that caused the exception/error
• The last operation being processed when the exception/error occurred
• The status code
• The RPG IV routine in which the exception/error occurred.

The fields from position 1 to position 66 in the file feedback section of the INFDS are always provided and updated even if INFDS is not specified in the program. The fields from position 67 to position 80 of the file feedback section of the INFDS are only updated after a POST operation to a specific device. If INFDS is not specified, the information in the file feedback section of the INFDS can be output using the DUMP operation. For more information see DUMP (Program Dump).

The location of some of the more commonly used subfields in the file feedback section of the INFDS is defined by special keywords.

3. Circular Buffer

A circular buffer or ring buffer is a data structure that uses a single, fixed-size buffer as if it were connected end-to-end. This structure lends itself easily to buffering data streams.

A circular buffer first starts empty and of some predefined length.If two elements are then removed from the buffer then they come from the end. The two elements removed.A consequence of the circular buffer is that when it is full then a subsequent write is performed then it starts overwriting the oldest data.Alternatively, the routines that manage the buffer could easily not allow data to be overwritten and return an error or raise an exception. Whether or not data is overwritten is up to the semantics of the buffer routines or the application using the circular buffer.

Tree data structure

A tree is a widely-used data structure that emulates a hierarchical tree structure with a set of linked nodes. It is an acyclic connected graph where each node has a set of zero or more children nodes, and at most one parent node.A node may contain a value or a condition or represent a separate data structure or a tree of its own. Each node in a tree has zero or more child nodes, which are below it in the tree (by convention, trees grow down, not up as they do in nature). A node that has a child is called the child's parent node (or ancestor node, or superior). A node has at most one parent.The height of a node is the length of the longest downward path to a leaf from that node. The height of the root is the height of the tree. The depth of a node is the length of the path to its root (i.e., its root path). This is commonly needed in the manipulation of the various self balancing trees, AVL Trees in particular. Conventionally, the value -1 corresponds to a subtree with no nodes, whereas zero corresponds to a subtree with one node.
The topmost node in a tree is called the root node. Being the topmost node, the root node will not have parents. It is the node at which operations on the tree commonly begin (although some algorithms begin with the leaf nodes and work up ending at the root). All other nodes can be reached from it by following edges or links. (In the formal definition, each such path is also unique). In diagrams, it is typically drawn at the top. In some trees, such as heaps, the root node has special properties. Every node in a tree can be seen as the root node of the subtree rooted at that node.
Nodes at the bottommost level of the tree are called leaf nodes. Since they are at the bottommost level, they do not have any children. They are also referred to as terminal nodes.
An internal node or inner node is any node of a tree that has child nodes and is thus not a leaf node.
A subtree is a portion of a tree data structure that can be viewed as a complete tree in itself. Any node in a tree T, together with all the nodes below it, comprise a subtree of T. The subtree corresponding to the root node is the entire tree; the subtree corresponding to any other node is called is a proper subtree (in analogy to the term proper subset).