STRUCTURE OF DBMS or Components of DBMS

STRUCTURE OF DBMS or Components of DBMS

DBMS (Database Management System) acts as an interface between the user and the database. The user requests the DBMS to perform various operations (insert, delete, update and retrieval) on the database. The components of DBMS perform these requested operations on the database and provide necessary data to the users.

The various components of DBMS are shown below: -

1.      DDL Compiler - Data Description Language compiler processes schema definitions specified in the DDL. It includes metadata information such as the name of the files, data items, storage details of each file, mapping information and constraints etc.

2.      DML Compiler and Query optimizer - The DML commands such as insert, update, delete, retrieve from the application program are sent to the DML compiler for compilation into object code for database access. The object code is then optimized in the best way to execute a query by the query optimizer and then send to the data manager.

3.      Data Manager - The Data Manager is the central software component of the DBMS also knows as Database Control System.

The Main Functions Of Data Manager Are: –

• Convert operations in user's Queries coming from the application programs or combination of DML Compiler and Query optimizer which is known as Query Processor from user's logical view to physical file system.

• Controls DBMS information access that is stored on disk.

• It also controls handling buffers in main memory.

• It also enforces constraints to maintain consistency and integrity of the data.

• It also synchronizes the simultaneous operations performed by the concurrent users.

• It also controls the backup and recovery operations.

4. Data Dictionary - Data Dictionary is a repository of description of data in the database. It contains information about

• Data - names of the tables, names of attributes of each table, length of attributes, and number of rows in each table.

• Relationships between database transactions and data items referenced by them which is useful in determining which transactions are affected when certain data definitions are changed.

• Constraints on data i.e. range of values permitted.

• Detailed information on physical database design such as storage structure, access paths, files and record sizes.

• Access Authorization - is the Description of database users their responsibilities and their access rights.

• Usage statistics such as frequency of query and transactions.

Data dictionary is used to actually control the data integrity, database operation and accuracy. It may be used as a important part of the DBMS.

Importance of Data Dictionary –

Data Dictionary is necessary in the databases due to following reasons:

• It improves the control of DBA over the information system and user's understanding of use of the system.

• It helps in documenting the database design process by storing documentation of the result of every design phase and design decisions.

• It helps in searching the views on the database definitions of those views.

• It provides great assistance in producing a report of which data elements (i.e. data values) are used in all the programs.

• It promotes data independence i.e. by addition or modifications of structures in the database application program are not effected.

4.      Data Files - It contains the data portion of the database.

5.      Compiled DML - The DML complier converts the high level Queries into low level file access commands known as compiled DML.

6.      End Users - End users are the people whose jobs require access to the database for querying, updating, and generating reports;

    There are several categories of end users:

• Casual end users occasionally access the database, but they may need different information each time. They use a sophisticated database query interface
• Naive or parametric end users make up a sizable portion of database end users. Their main job function revolves around constantly querying and updating the database, using standard types of queries and updates
• Sophisticated end users include engineers, scientists, business analysts, and others who thoroughly familiarize themselves with the facilities of the DBMS in order to implement their own applications to meet their complex requirements.
• Standalone users maintain personal databases by using ready-made pro-gram packages that provide easy-to-use menu-based or graphics-based interfaces. An example is the user of a financial software package that stores a variety of personal financial data.

SQL Data Types

SQL Data Types

The data type of a column defines what value the column can hold: integer, character, money, date and time, binary, and so on.

Each column in a database table is required to have a name and a data type.

In MySQL there are three main data types: string, numeric, and date and time.

String data types:

Data type	Description
CHAR(size)	A FIXED length string (can contain letters, numbers, and special characters). The size parameter specifies the column length in characters - can be from 0 to 255. Default is 1
VARCHAR(size)	A VARIABLE length string (can contain letters, numbers, and special characters). The size parameter specifies the maximum column length in characters - can be from 0 to 65535
BINARY(size)	Equal to CHAR(), but stores binary byte strings. The size parameter specifies the column length in bytes. Default is 1
VARBINARY(size)	Equal to VARCHAR(), but stores binary byte strings. The size parameter specifies the maximum column length in bytes.
TINYBLOB	For BLOBs (Binary Large OBjects). Max length: 255 bytes
TINYTEXT	Holds a string with a maximum length of 255 characters
TEXT(size)	Holds a string with a maximum length of 65,535 bytes
BLOB(size)	For BLOBs (Binary Large OBjects). Holds up to 65,535 bytes of data
MEDIUMTEXT	Holds a string with a maximum length of 16,777,215 characters
MEDIUMBLOB	For BLOBs (Binary Large OBjects). Holds up to 16,777,215 bytes of data
LONGTEXT	Holds a string with a maximum length of 4,294,967,295 characters
LONGBLOB	For BLOBs (Binary Large OBjects). Holds up to 4,294,967,295 bytes of data
ENUM(val1, val2, val3, ...)	A string object that can have only one value, chosen from a list of possible values. You can list up to 65535 values in an ENUM list. If a value is inserted that is not in the list, a blank value will be inserted. The values are sorted in the order you enter them
SET(val1, val2, val3, ...)	A string object that can have 0 or more values, chosen from a list of possible values. You can list up to 64 values in a SET list

Numeric data types:

Data type	Description
BIT(size)	A bit-value type. The number of bits per value is specified in size. The size parameter can hold a value from 1 to 64. The default value for size is 1.
TINYINT(size)	A very small integer. Signed range is from -128 to 127. Unsigned range is from 0 to 255. The size parameter specifies the maximum display width (which is 255)
BOOL	Zero is considered as false, nonzero values are considered as true.
BOOLEAN	Equal to BOOL
SMALLINT(size)	A small integer. Signed range is from -32768 to 32767. Unsigned range is from 0 to 65535. The size parameter specifies the maximum display width (which is 255)
MEDIUMINT(size)	A medium integer. Signed range is from -8388608 to 8388607. Unsigned range is from 0 to 16777215. The size parameter specifies the maximum display width (which is 255)
INT(size)	A medium integer. Signed range is from -2147483648 to 2147483647. Unsigned range is from 0 to 4294967295. The size parameter specifies the maximum display width (which is 255)
INTEGER(size)	Equal to INT(size)
BIGINT(size)	A large integer. Signed range is from -9223372036854775808 to 9223372036854775807. Unsigned range is from 0 to 18446744073709551615. The size parameter specifies the maximum display width (which is 255)
FLOAT(size, d)	A floating point number. The total number of digits is specified in size. The number of digits after the decimal point is specified in the d parameter. This syntax is deprecated in MySQL 8.0.17, and it will be removed in future MySQL versions
FLOAT(p)	A floating point number. MySQL uses the p value to determine whether to use FLOAT or DOUBLE for the resulting data type. If p is from 0 to 24, the data type becomes FLOAT(). If p is from 25 to 53, the data type becomes DOUBLE()
DOUBLE(size, d)	A normal-size floating point number. The total number of digits is specified in size. The number of digits after the decimal point is specified in the d parameter
DOUBLE PRECISION(size, d)
DECIMAL(size, d)	An exact fixed-point number. The total number of digits is specified in size. The number of digits after the decimal point is specified in the d parameter. The maximum number for size is 65. The maximum number for d is 30. The default value for size is 10. The default value for d is 0.
DEC(size, d)	Equal to DECIMAL(size,d)

Date and Time data types:

Data type	Description
DATE	A date. Format: YYYY-MM-DD. The supported range is from '1000-01-01' to '9999-12-31'
DATETIME(fsp)	A date and time combination. Format: YYYY-MM-DD hh:mm:ss. The supported range is from '1000-01-01 00:00:00' to '9999-12-31 23:59:59'. Adding DEFAULT and ON UPDATE in the column definition to get automatic initialization and updating to the current date and time
TIMESTAMP(fsp)	A timestamp. TIMESTAMP values are stored as the number of seconds since the Unix epoch ('1970-01-01 00:00:00' UTC). Format: YYYY-MM-DD hh:mm:ss. The supported range is from '1970-01-01 00:00:01' UTC to '2038-01-09 03:14:07' UTC. Automatic initialization and updating to the current date and time can be specified using DEFAULT CURRENT_TIMESTAMP and ON UPDATE CURRENT_TIMESTAMP in the column definition
TIME(fsp)	A time. Format: hh:mm:ss. The supported range is from '-838:59:59' to '838:59:59'
YEAR	A year in four-digit format. Values allowed in four-digit format: 1901 to 2155, and 0000. MySQL 8.0 does not support year in two-digit format.

Client/server architecture

Client/server architecture

Client/server architecture is a computing model in which the server hosts, delivers and manages most of the resources and services to be consumed by the client. This type of architecture has one or more client computers connected to a central server over a network or internet connection. This system shares computing resources.

Client/server architecture is also known as a networking computing model or client/server network because all the requests and services are delivered over a network.

Client/server architecture works when the client computer sends a resource or process request to the server over the network connection, which is then processed and delivered to the client. A server computer can manage several clients simultaneously, whereas one client can be connected to several servers at a time, each providing a different set of services. In its simplest form, the internet is also based on client/server architecture where web servers serve many simultaneous users with website data.

Client Server Computing

In client server computing, the clients request a resource and the server provides that resource. A server may serve multiple clients at the same time while a client is in contact with only one server. Both the client and server usually communicate via a computer network but sometimes they may reside in the same system.

Characteristics of Client Server Computing

The salient points for client server computing are as follows:

• The client server computing works with a system of request and response. The client sends a request to the server and the server responds with the desired information.
• The client and server should follow a common communication protocol so they can easily interact with each other. All the communication protocols are available at the application layer.
• A server can only accommodate a limited number of client requests at a time. So it uses a system based to priority to respond to the requests.
• Denial of Service attacks hinder servers ability to respond to authentic client requests by inundating it with false requests.
• An example of a client server computing system is a web server. It returns the web pages to the clients that requested them.

The different advantages of client server computing are:

• All the required data is concentrated in a single place i.e. the server. So it is easy to protect the data and provide authorization and authentication.
• The server need not be located physically close to the clients. Yet the data can be accessed efficiently.
• It is easy to replace, upgrade or relocate the nodes in the client server model because all the nodes are independent and request data only from the server.
• All the nodes i.e clients and server may not be build on similar platforms yet they can easily facilitate the transfer of data.

Disadvantages of Client Server Computing

The different disadvantages of client server computing are:

• If all the clients simultaneously request data from the server, it may get overloaded. This may lead to congestion in the network.
• If the server fails for any reason, then none of the requests of the clients can be fulfilled. This leads of failure of the client server network.
• The cost of setting and maintaining a client server model are quite high.

Data Fragmentation

Data Fragmentation

The process of dividing the database into a smaller multiple parts is called as fragmentation. These fragments may be stored at different locations. The data fragmentation process should be carried out in such a way that the reconstruction of original database from the fragments is possible.

Fragmentation can be of three types: horizontal, vertical, and hybrid (combination of horizontal and vertical). Horizontal fragmentation can further be classified into two techniques: primary horizontal fragmentation and derived horizontal fragmentation.

Advantages of Fragmentation

·         Since data is stored close to the site of usage, efficiency of the database system is increased.

·         Local query optimization techniques are sufficient for most queries since data is locally available.

·         Since irrelevant data is not available at the sites, security and privacy of the database system can be maintained.

Disadvantages of Fragmentation

·         When data from different fragments are required, the access speeds may be very high.

·         In case of recursive fragmentations, the job of reconstruction will need expensive techniques.

·         Lack of back-up copies of data in different sites may render the database ineffective in case of failure of a site.

Vertical Fragmentation

In vertical fragmentation, the fields or columns of a table are grouped into fragments. In order to maintain reconstructiveness, each fragment should contain the primary key field(s) of the table. Vertical fragmentation can be used to enforce privacy of data.

For example, let us consider that a University database keeps records of all registered students in a Student table having the following schema.

STUDENT

Regd_No

Name

Course

Address

Semester

Fees

Marks

Now, the fees details are maintained in the accounts section. In this case, the designer will fragment the database as follows −

CREATE TABLE STD_FEES AS SELECT Regd_No, Fees  FROM STUDENT;

Horizontal Fragmentation

Horizontal fragmentation groups the tuples of a table in accordance to values of one or more fields. Horizontal fragmentation should also confirm to the rule of reconstructiveness. Each horizontal fragment must have all columns of the original base table.

For example, in the student schema, if the details of all students of Computer Science Course needs to be maintained at the School of Computer Science, then the designer will horizontally fragment the database as follows −

CREATE COMP_STD AS SELECT * FROM STUDENT WHERE COURSE = "Computer Science";

Hybrid Fragmentation

In hybrid fragmentation, a combination of horizontal and vertical fragmentation techniques are used. This is the most flexible fragmentation technique since it generates fragments with minimal extraneous information. However, reconstruction of the original table is often an expensive task.

Hybrid fragmentation can be done in two alternative ways −

• At first, generate a set of horizontal fragments; then generate vertical fragments from one or more of the horizontal fragments.
• At first, generate a set of vertical fragments; then generate horizontal fragments from one or more of the vertical fragments.

Data Replication

Data Replication 

Data replication is the process in which the data is copied at multiple locations (Different computers or servers) to improve the availability of data.

Data replication is done with an aim to:

• Increase the availability of data.
• Speed up the query evaluation.

There are two types of data replication:

1. Synchronous Replication:
In synchronous replication, the replica will be modified immediately after some changes are made in the relation table. So there is no difference between original data and replica.

2. Asynchronous replication:
In asynchronous replication, the replica will be modified after commit is fired on to the database.

The three replication schemes are as follows:

1. Full Replication

In full replication scheme, the database is available to almost every location or user in communication network.

Advantages of full replication

• High availability of data, as database is available to almost every location.
• Faster execution of queries.

Disadvantages of full replication

• Concurrency control is difficult to achieve in full replication.
• Update operation is slower.

2. No Replication

No replication means, each fragment is stored exactly at one location.

Advantages of no replication

• Concurrency can be minimized.
• Easy recovery of data.

Disadvantages of no replication

• Poor availability of data.
• Slows down the query execution process, as multiple clients are accessing the same server.

3. Partial replication

Partial replication means only some fragments are replicated from the database.

Advantages of partial replication
The number of replicas created for fragments depend upon the importance of data in that fragment.