MCS-023 Solved Free Assignment 2024-25 Sem 3
Q1. a) What is SQL? Explain its important features.
b) Consider the following schemas:
BOOK (Book_ID, Title, Publisher_ID, Year_of Pub, Price)
AUTHOR (Author_ID, Book_ID, Author Name)
PUBLISHER (Publisher_ID, Book_ID, Address, Name_of Pub, No._of Copies)
Write a query in SQL for the following:
(i) Find the name of authors whose books are published by "ABC Press".
(ii) Find the name of the author and price of the book, whose Book_ID is '100'.
(iii) Find the title of the books which are published by Publisher_ID '20' and are published in year 2011.
(iv) Find the address of the publisher who has published Book_ID "500".
Make suitable assumptions, if any.
Ans:- **(a) What is SQL? Explain its important features.**
**SQL (Structured Query Language)** is a standard programming language used for managing and manipulating relational databases. It allows users to create, modify, query, and manage data stored in databases. SQL is used to interact with databases like MySQL, PostgreSQL, Oracle, and SQL Server.
**Important features of SQL:**
1. **Data Querying**: SQL allows users to retrieve specific data from large datasets using queries, such as `SELECT`, `WHERE`, `GROUP BY`, and `ORDER BY`.
2. **Data Manipulation**: SQL supports operations to modify data, like inserting, updating, and deleting records using `INSERT`, `UPDATE`, and `DELETE`.
3. **Data Definition**: SQL enables users to define and modify database structures like tables, indexes, and relationships through `CREATE`, `ALTER`, and `DROP` statements.
4. **Data Control**: SQL provides security by allowing access control through `GRANT` and `REVOKE`, ensuring that only authorized users can modify or view data.
5. **Transaction Control**: SQL allows users to manage transactions, ensuring data integrity using commands like `BEGIN`, `COMMIT`, and `ROLLBACK`.
---
**(b) Consider the following schemas:**
- **BOOK (Book_ID, Title, Publisher_ID, Year_of_Pub, Price)**
- **AUTHOR (Author_ID, Book_ID, Author_Name)**
- **PUBLISHER (Publisher_ID, Book_ID, Address, Name_of_Pub, No._of_Copies)**
SQL Queries:
**(i) Find the name of authors whose books are published by "ABC Press".**
```sql
SELECT a.Author_Name
FROM AUTHOR a
JOIN BOOK b ON a.Book_ID = b.Book_ID
JOIN PUBLISHER p ON b.Publisher_ID = p.Publisher_ID
WHERE p.Name_of_Pub = 'ABC Press';
```
**(ii) Find the name of the author and price of the book, whose Book_ID is '100'.**
```sql
SELECT a.Author_Name, b.Price
FROM AUTHOR a
JOIN BOOK b ON a.Book_ID = b.Book_ID
WHERE b.Book_ID = '100';
```
**(iii) Find the title of the books which are published by Publisher_ID '20' and are published in the year 2011.**
```sql
SELECT b.Title
FROM BOOK b
WHERE b.Publisher_ID = '20' AND b.Year_of_Pub = 2011;
```
**(iv) Find the address of the publisher who has published Book_ID "500".**
```sql
SELECT p.Address
FROM PUBLISHER p
WHERE p.Book_ID = '500';
```
Q2. a) With the help of a suitable example, discuss the insertion, deletion and updation anomalies that can
occur in a database. Briefly discuss the mechanism to remove such anomalies.
b) Write SQL commands for each of the following. Also illustrate the usage of each command through suitable example.
(i) Creation of views
(ii) Creation of sequences
(iii) Outer join
(iv) To give access permission to any user
Ans:- **(a) Insertion, Deletion, and Updation Anomalies in Databases (6 Marks)**
Anomalies in a database arise when the design is not normalized, often leading to data redundancy and inconsistencies. These can occur when multiple pieces of information are stored in a single table.
1. **Insertion Anomaly**:
- This occurs when certain data cannot be inserted into the database without the presence of other data.
- **Example**: Consider a table that stores employee and department details. If the department is not yet assigned but we need to add a new employee, the insertion is blocked because of the requirement for a department.
| Employee_ID | Employee_Name | Department_ID | Department_Name |
|-------------|---------------|---------------|-----------------|
| 1 | John | 101 | HR |
- **Anomaly**: If a new department needs to be added without an employee, it cannot be inserted unless we add a dummy employee.
2. **Deletion Anomaly**:
- This occurs when deletion of one piece of data leads to unintentional loss of other valuable data.
- **Example**: If an employee working in the only HR department leaves and is deleted from the table, the department information might be lost as well.
| Employee_ID | Employee_Name | Department_ID | Department_Name |
|-------------|---------------|---------------|-----------------|
| 1 | John | 101 | HR |
| 2 | Anna | 102 | Finance |
- **Anomaly**: Deleting John will also remove HR department details.
3. **Updation Anomaly**:
- This happens when we have redundant data and a single update requires multiple changes, increasing the risk of inconsistencies.
- **Example**: If the HR department name is updated to "Human Resources" in one row but not in all rows, inconsistencies arise.
| Employee_ID | Employee_Name | Department_ID | Department_Name |
|-------------|---------------|---------------|-----------------|
| 1 | John | 101 | HR |
| 2 | Anna | 102 | Finance |
| 3 | Mike | 101 | HR |
- **Anomaly**: Updating "HR" to "Human Resources" requires updating multiple rows. If not done properly, some rows will still show "HR".
**Solution - Normalization**:
Normalization is a process of organizing the data in a database to reduce redundancy and improve data integrity. It involves dividing a large table into smaller, related tables and defining relationships between them using foreign keys. This removes the anomalies as:
- Each piece of data is stored only once.
- Updates are made in only one place.
- Deletions and insertions do not affect other data unnecessarily.
For example, by splitting the Employee and Department into two tables:
- **Employee Table**: `Employee_ID, Employee_Name, Department_ID`
- **Department Table**: `Department_ID, Department_Name`
---
**(b) SQL Commands and Usage (4 Marks)**
**(i) Creation of Views**:
- A **view** is a virtual table that provides a way to look at data from one or more tables. It doesn't store data itself but generates it on demand.
**Command**:
```sql
CREATE VIEW EmployeeDept AS
SELECT e.Employee_Name, d.Department_Name
FROM Employee e
JOIN Department d ON e.Department_ID = d.Department_ID;
```
**Usage**: This view simplifies queries, like retrieving employees and their departments without needing to join tables repeatedly.
**(ii) Creation of Sequences**:
- A **sequence** generates a sequence of unique numbers, typically used for creating auto-incremented primary keys.
**Command**:
```sql
CREATE SEQUENCE EmployeeSeq
START WITH 1
INCREMENT BY 1;
```
**Usage**: When inserting a new employee, the sequence can automatically assign a unique ID:
```sql
INSERT INTO Employee (Employee_ID, Employee_Name)
VALUES (EmployeeSeq.NEXTVAL, 'Alice');
```
**(iii) Outer Join**:
- An **outer join** returns all rows from one table and the matching rows from the other table. If no match is found, NULL values are returned.
**Command**:
```sql
SELECT e.Employee_Name, d.Department_Name
FROM Employee e
LEFT OUTER JOIN Department d ON e.Department_ID = d.Department_ID;
```
**Usage**: This query will return all employees, even those who are not assigned to any department (with NULL for Department_Name).
**(iv) To Give Access Permission to Any User**:
- The `GRANT` statement gives specific permissions to a user.
**Command**:
```sql
GRANT SELECT, INSERT ON Employee TO user_name;
```
**Usage**: This allows the user
`user_name` to view and insert data into the `Employee` table without being able to update or delete it.
Q3. a) What are integrity constraints? Discuss the various types of integrity constraints that can be imposed on database.
b) How are database security and database integrity related? Briefly discuss the different levels of
security measures which may be considered to protect the database.
c) Consider the relation R (A, B, C, D, E) and the set of functional dependencies :-
F(A → D, {A,B} → C, D → E)
Assume that the decomposition of R into {R1 (A, B, C) and R2 (A, D, E)}. Is this decomposition lossless? Justify?
Ans:- **(a) What are Integrity Constraints? Discuss the various types of integrity constraints that can be imposed on a database.
**Integrity constraints** are rules enforced on data in a database to ensure its accuracy, consistency, and validity. They prevent the entry of invalid data and maintain the relationships between tables.
The main types of integrity constraints are:
1. **Domain Integrity**:
- Ensures that all values in a column are within a specific domain. This means data entered in a field must be of a valid data type and follow any additional constraints like length or format.
- **Example**: A field for "Age" may only accept positive integers.
2. **Entity Integrity**:
- Ensures that every table has a unique identifier, typically a **Primary Key**, which ensures that no two rows are identical, and each row can be uniquely identified.
- **Example**: In an "Employees" table, the "Employee_ID" column is set as a primary key, so no two employees can have the same ID, and it cannot be NULL.
3. **Referential Integrity**:
- Ensures that relationships between tables remain consistent. It is enforced using **Foreign Keys**, where a value in one table must match a value in another table.
- **Example**: If "Department_ID" in the "Employees" table is a foreign key referencing "Department_ID" in the "Departments" table, every department assigned to an employee must exist in the "Departments" table.
4. **Key Integrity**:
- A combination of fields that are collectively unique (e.g., a **Composite Key**) or a single field that uniquely identifies a record in a table (e.g., **Primary Key**).
- **Example**: {A, B} → C implies that A and B together uniquely determine C.
5. **Unique Constraint**:
- Ensures that all values in a column or set of columns are unique, preventing duplicates.
- **Example**: The "Email" field in a user table must be unique to ensure no two users have the same email.
---
**(b) How are Database Security and Database Integrity Related? Briefly discuss the different levels of security measures to protect the database.
**Database Security** and **Database Integrity** are closely related in ensuring the reliability of the database.
- **Database Integrity** ensures that the data within the database is accurate, valid, and consistent.
- **Database Security** focuses on protecting the data from unauthorized access, breaches, or malicious attacks. If security is compromised, integrity can be affected as unauthorized changes can lead to corrupt or inconsistent data.
**Levels of Security Measures**:
1. **Physical Level Security**:
- Protects the hardware and physical storage systems where the database resides.
- **Measures**: Restricting physical access to servers, locking server rooms, and ensuring backup systems are secure.
2. **Network Level Security**:
- Protects the database from unauthorized access over the network.
- **Measures**: Firewalls, encryption of data in transit (e.g., using SSL/TLS), and VPNs to secure communications between clients and the database.
3. **Access Control (User Level Security)**:
- Ensures that only authorized users can access or modify the data.
- **Measures**: Implementing role-based access control (RBAC), strong authentication mechanisms, user permissions, and the principle of least privilege.
4. **Database-Level Security**:
- Protects the data stored in the database.
- **Measures**: Encryption of sensitive data, database auditing, and logging to monitor access and changes.
5. **Application-Level Security**:
- Ensures that the applications interacting with the database enforce security controls.
- **Measures**: Input validation, sanitization of user inputs to prevent SQL injection, and secure coding practices.
---
**(c) Consider the relation R (A, B, C, D, E) and the set of functional dependencies F(A → D, {A, B} → C, D → E). Is the decomposition of R into {R1 (A, B, C) and R2 (A, D, E)} lossless? Justify.
To check whether a decomposition is **lossless**, we need to ensure that the original relation can be reconstructed from the decomposed relations without any loss of information. This is verified using the **lossless-join decomposition** property, which holds if at least one common attribute between the decomposed tables is a **superkey** for one of the relations.
Steps:
- **Given Relation (R):** R (A, B, C, D, E)
- **Decomposed Relations:**
- R1 (A, B, C)
- R2 (A, D, E)
- **Functional Dependencies (F):** A → D, {A, B} → C, D → E
Decomposition Check:
- The common attribute between R1 and R2 is **A**.
- From the functional dependencies, we know that:
- A → D (A determines D)
- A is a superkey for R2 because it can uniquely determine the other attributes (D, E) in R2.
Since **A** is a superkey for R2, this satisfies the condition for a **lossless join**.
Q4. a) Explain the Log-based recovery scheme with the help of an example.
b) Compute the closure of the following set F of functional dependencies for relation schema
R = (A, B, C, D, E).
A → BC
CD → E
B → D
E → A
List the candidate keys for R.
Ans:- **(a) Explain the Log-Based Recovery Scheme with the help of an example.**
A **Log-based recovery scheme** ensures that in case of a system crash or failure, a database can recover to a consistent state using logs (a record of all transactions). The logs keep a record of transaction start, changes made to the database, and the transaction end (commit or rollback). There are two key types of logs:
- **Redo Logs**: Used to reapply changes from committed transactions after a failure.
- **Undo Logs**: Used to revert changes from uncommitted transactions after a failure.
Steps in Log-based Recovery:
1. **Transaction begins**: A log entry is written, noting the start of the transaction.
- Example: `T1 START`
2. **Transaction modifies data**: Before and after values of any modified data are recorded in the log.
- Example: Suppose transaction T1 modifies a value in record X from 100 to 200.
- Log entry: `T1, X, 100, 200`
3. **Transaction commits**: A log entry is made indicating the transaction has been successfully completed.
- Example: `T1 COMMIT`
4. **System Crash or Failure**:
- **Redo Phase**: The system scans the logs and redoes all committed transactions by reapplying the changes from the logs (ensuring durability).
- **Undo Phase**: The system undoes all uncommitted transactions, reverting the database back to its previous state using the "before" values stored in the logs.
Example:
Assume the following sequence of actions before a crash:
1. `T1 START`
2. `T1, A, 50, 100` (A changes from 50 to 100)
3. `T2 START`
4. `T2, B, 30, 60` (B changes from 30 to 60)
5. `T1 COMMIT`
6. Crash happens before `T2` commits.
**Recovery Process:**
- **Redo Phase**: Since `T1` is committed, the change to A (100) is redone, ensuring it persists.
- **Undo Phase**: Since `T2` is not committed, the change to B is undone, reverting B back to 30.
---
**(b) Compute the closure of the following set F of functional dependencies for relation schema R = (A, B, C, D, E)**.
Given the functional dependencies:
1. A → BC
2. CD → E
3. B → D
4. E → A
**Step 1: Computing the closure of attributes**
We compute the closure of attributes to find all the attributes that can be functionally determined by a given set of attributes.
Let’s compute the closure of **A** (denoted as A⁺):
- Start with: A⁺ = {A}
- Apply A → BC: A⁺ = {A, B, C}
- Apply B → D: A⁺ = {A, B, C, D}
- Apply CD → E: A⁺ = {A, B, C, D, E}
- Apply E → A: A⁺ = {A, B, C, D, E} (A already included)
Thus, **A⁺ = {A, B, C, D, E}**, meaning A can determine all attributes of R.
**Step 2: Candidate Keys**
A **candidate key** is the minimal set of attributes that can determine all attributes in the relation. To find the candidate keys, we look for minimal subsets of attributes whose closures contain all attributes in R.
- Since **A⁺ = {A, B, C, D, E}**, A alone is a candidate key.
Now, check if there are any other candidate keys:
- The closure of B, C, D, or E individually does not cover all attributes.
- Therefore, **A** is the only minimal attribute set that can determine all attributes.
Candidate Key:
- The only candidate key for R is **A**.
Thus, the **candidate key** for R is **A**.
Q5. a) Give the limitations of file based system. How can they be overcome using DBMS?
b) Discuss the importance of file organisation in databases. Mention the different types of file organisations available. Discuss any one of the mentioned file organisations in detail.
Ans:- **(a) Limitations of File-Based Systems and How DBMS Overcomes Them (5 Marks)**
A **file-based system** stores data in a series of files and provides limited functionalities for managing and retrieving data. However, this approach has several limitations:
1. **Data Redundancy and Inconsistency**:
- In file systems, the same data may be duplicated across multiple files, leading to redundancy. When updates are made in one place but not others, it causes data inconsistency.
- **DBMS Solution**: In a DBMS, data is stored in a centralized manner, allowing data to be shared across multiple applications, thus minimizing redundancy. It also uses constraints and normalization techniques to avoid inconsistencies.
2. **Lack of Data Integrity**:
- File systems provide no built-in mechanism to enforce data integrity. Inconsistencies and invalid data might arise because of lack of validation rules.
- **DBMS Solution**: DBMS supports **integrity constraints** such as primary keys, foreign keys, and check constraints to ensure that data remains accurate and consistent.
3. **Poor Data Security**:
- File-based systems offer limited security, as unauthorized users can easily access or modify data if they have access to the file system.
- **DBMS Solution**: DBMS provides fine-grained security measures, including user authentication, access control (e.g., `GRANT`, `REVOKE`), and encryption to protect data.
4. **Data Isolation**:
- Data is spread across multiple files and is often in different formats, making it difficult to retrieve related data efficiently.
- **DBMS Solution**: DBMS organizes data in tables with defined relationships (using foreign keys), enabling easy and efficient access to related data via queries.
5. **Concurrent Access Issues**:
- File systems have difficulties handling multiple users accessing or modifying the same data simultaneously, which can result in inconsistencies.
- **DBMS Solution**: DBMS handles concurrency control using techniques like **locking**, **transactions**, and **ACID properties** (Atomicity, Consistency, Isolation, Durability), ensuring data consistency even in multi-user environments.
6. **Complex Data Retrieval**:
- In file-based systems, retrieving data often requires writing complex, low-level programs.
- **DBMS Solution**: DBMS allows data retrieval using **SQL**, a high-level language, which simplifies querying, sorting, and filtering data.
**Conclusion**: DBMS overcomes the limitations of file-based systems by providing a more structured, secure, and efficient way to manage and manipulate data.
---
**(b) Importance of File Organization in Databases and Types of File Organizations (5 Marks)**
**File organization** refers to the way data is stored in a database file. Efficient file organization is critical because it affects the speed of data retrieval, insertion, deletion, and modification operations. Proper file organization improves database performance, minimizes storage space, and optimizes query response time.
Types of File Organizations:
1. **Heap (Unordered) File Organization**
2. **Sequential File Organization**
3. **Hashed File Organization**
4. **Clustered File Organization**
5. **Indexed File Organization**
Discussing **Sequential File Organization** in Detail:
**Sequential File Organization**:
In **sequential file organization**, records are stored in a specific order based on a key field (e.g., primary key).
This organization allows for efficient reading of records in sequence but is less efficient for random access or updates.
**Key Characteristics**
- Data is arranged in ascending or descending order based on a key field.
- It is efficient for reading large sets of data in sequence.
- To locate a specific record, binary search techniques can be used if the file is sorted.
- Insertion of new records may require reordering the entire file, which can be costly in terms of time and performance.
- Updates are also difficult if they change the ordering of records.
**Advantages**:
- **Fast Sequential Access**: Ideal for applications that require processing of data in order, such as generating reports or processing large data sets.
- **Efficient Range Queries**: Queries that require a range of data (e.g., "find all students with marks between 80 and 90") can be answered efficiently, as the data is already sorted.
**Disadvantages**:
- **Slow Insertions and Updates**: Adding a new record or updating existing records may require rearranging the entire file, which is inefficient for large datasets.
- **Inefficient for Random Access**: If the required record is in the middle or end of the file, finding it may take considerable time, especially in very large files.
**Example**:
Consider a payroll system where employee records are stored in a sequential file based on their employee ID. If you need to process the payroll for all employees in sequence (sorted by employee ID), this file organization is highly efficient.
**Applications**:
- Batch processing systems where records are processed in bulk.
- Scenarios requiring sorted data retrieval, such as generating sequential reports or invoices.
Q6. a) For what reasons is 2-phase locking protocol required? Explain. Discuss the disadvantages of basic 2-phase locking protocol. List the ways and means that can be used to overcome the disadvantages.
b) List and explain the 4 basic properties of a Transaction with the help of appropriate examples.
Ans:- **(a) Why is the 2-Phase Locking (2PL) Protocol Required? Explain. (5 Marks)**
The **2-Phase Locking (2PL)** protocol is required to ensure **serializability** of transactions in a database. Serializability ensures that the outcome of executing concurrent transactions is the same as if they were executed serially, one after another, avoiding conflicts and maintaining data consistency.
In databases, multiple transactions often access the same data concurrently, leading to issues like **dirty reads**, **lost updates**, or **inconsistent retrievals**. The 2PL protocol prevents such issues by managing how locks are acquired and released by transactions, ensuring that no transaction interferes with another until it has safely completed.
Phases of 2PL:
1. **Growing Phase**:
- A transaction may **acquire locks** (read or write) on data items, but it cannot release any locks during this phase.
2. **Shrinking Phase**
- Once a transaction releases its first lock, it enters the shrinking phase, during which it can only **release locks** and cannot acquire any new locks.
These two phases ensure that transactions follow a strict order of acquiring and releasing locks, thus preventing **cascading rollbacks** and ensuring **serializable schedules**.
Disadvantages of the Basic 2-Phase Locking Protocol:
1. **Deadlocks**:
- A deadlock occurs when two or more transactions are waiting indefinitely for each other to release locks. In 2PL, if two transactions acquire locks on different items and then request locks held by the other, a deadlock can occur.
2. **Reduced Concurrency**:
- Since transactions hold locks for extended periods (until the shrinking phase), other transactions may be forced to wait, reducing the level of concurrency in the system and leading to lower throughput.
3. **Possibility of Cascading Aborts**:
- If a transaction holding locks aborts, other transactions dependent on its changes may also need to be aborted, leading to cascading rollbacks and performance degradation.
Ways to Overcome the Disadvantages:
1. **Deadlock Prevention/Detection**:
- **Deadlock Prevention**: Use techniques like a **wait-die** or **wound-wait** approach where older transactions can preempt younger ones.
- **Deadlock Detection**: Use a **wait-for graph** to detect cycles (deadlocks) and resolve them by aborting one of the transactions involved in the deadlock.
2. **Lock Timeout**:
- Transactions waiting for a lock for a certain time can be aborted, preventing indefinite waiting and thus deadlocks.
3. **Strict 2-Phase Locking (Strict 2PL)**:
- In strict 2PL, all locks held by a transaction are only released at the end (after the transaction commits or aborts), eliminating cascading rollbacks since other transactions can only access data after the first transaction finishes.
4. **Optimistic Concurrency Control**:
- Instead of using locks, some systems use optimistic approaches where transactions proceed without locking but validate their actions before committing, reducing the need for locks and improving concurrency.
---
**(b) List and Explain the 4 Basic Properties of a Transaction with Examples. (5 Marks)**
The **ACID** properties define the essential characteristics that ensure the reliability and integrity of database transactions. These properties are:
1. **Atomicity**:
- Atomicity ensures that a transaction is treated as a single "unit of work." Either all the operations within the transaction are successfully executed (committed), or none of them are (rolled back). There is no partial execution.
**Example**: Consider a money transfer between two accounts (A and B). The transaction involves deducting $100 from A and adding $100 to B. If either operation fails (e.g., deduction from A is successful but addition to B fails), the transaction is rolled back, and both operations are undone.
2. **Consistency**:
- Consistency ensures that a transaction takes the database from one valid state to another valid state. The integrity constraints of the database are maintained after the transaction.
**Example**: In a banking system, if a transaction involves transferring money from one account to another, the total balance across both accounts must remain the same before and after the transaction. If account A has $500 and account B has $300, after transferring $100 from A to B, A should have $400, and B should have $400, maintaining the total balance of $800.
3. **Isolation**:
- Isolation ensures that the operations of a transaction are hidden from other transactions until it completes. Even if transactions are executed concurrently, they should not interfere with each other’s operations, giving the illusion that they are executed sequentially.
**Example**: Suppose two transactions T1 and T2 are running concurrently. T1 is updating an inventory record, and T2 is reading it. If isolation is enforced, T2 will see either the state of the record before or after T1's update but not the intermediate state during the update.
4. **Durability**:
- Durability ensures that once a transaction is committed, its effects are permanent in the database, even in the case of system crashes or failures. Committed changes are saved to persistent storage.
**Example**: In a banking system, once a money transfer transaction is completed and committed, the updated balances of the accounts should remain in the database even if there is a system crash immediately afterward. The database recovery system ensures that the changes are not lost.
Summary of ACID Properties:
- **Atomicity**: All or nothing (complete rollback or commit).
- **Consistency**: Database integrity is maintained.
- **Isolation**: Transactions are isolated from one another.
- **Durability**: Committed transactions survive system failures.
These properties ensure that transactions maintain data accuracy, consistency, and reliability in multi-user and concurrent environments.
Q7. a) What do you mean by fragmentation of a database? What is the need of fragmentation in DDBMS environment? Explain different types of fragmentation with an example of each.
b) Explain the need of Distributed DBMS over Centralized DBMS. Also give the structure of Distributed DBMS.
Ans:- **(a) What is Fragmentation of a Database? Why is it Needed in a DDBMS Environment? Explain the Different Types of Fragmentation with Examples. (5 Marks)**
**Fragmentation** in the context of databases refers to breaking down a database into smaller, more manageable pieces (fragments) that are stored across different locations in a **Distributed Database Management System (DDBMS)**. Each fragment is a subset of the original database and is distributed across various sites to improve data access and performance.
**Need for Fragmentation in a DDBMS Environment**:
1. **Improved Performance**: By storing fragments closer to where they are accessed most frequently, fragmentation minimizes data transfer across the network, improving query response times.
2. **Enhanced Reliability and Availability**: If a site fails, other sites with different fragments can continue to function, enhancing the system's overall reliability and availability.
3. **Parallel Processing**: Since fragments can be stored across multiple sites, queries can be processed in parallel, thus improving overall efficiency.
4. **Reduced Communication Costs**: Fragmenting data reduces the need to transfer large datasets over the network, thus reducing communication overhead.
5. **Local Autonomy**: Sites can operate autonomously, with localized data management and query processing capabilities.
**Types of Fragmentation**:
1. **Horizontal Fragmentation**:
- In **horizontal fragmentation**, the database is divided into subsets of rows (tuples), where each fragment contains a subset of records that satisfy a particular condition.
**Example**:
Consider a `CUSTOMER` table with records from different cities. The table can be horizontally fragmented based on city:
- Fragment 1: `CUSTOMER(City = 'New York')`
- Fragment 2: `CUSTOMER(City = 'Los Angeles')`
Each fragment contains the same set of attributes (columns) but different rows based on the city.
2. **Vertical Fragmentation**:
- In **vertical fragmentation**, the database is divided into subsets of columns (attributes). Each fragment contains a subset of attributes from the original table, with a common key to enable recombination.
**Example**:
Consider a `STUDENT` table with columns `Student_ID`, `Name`, `Age`, `Address`, `GPA`. We can fragment it vertically as:
- Fragment 1: `STUDENT_1(Student_ID, Name, Age)`
- Fragment 2: `STUDENT_2(Student_ID, Address, GPA)`
Both fragments share the common key (`Student_ID`) to allow for later reconstruction of the original table.
3. **Hybrid (Mixed) Fragmentation**:
- **Hybrid fragmentation** is a combination of horizontal and vertical fragmentation. First, the database is horizontally fragmented, and then each horizontal fragment is vertically fragmented.
**Example**
Using the `STUDENT` table example, we can first apply horizontal fragmentation based on `Age`:
- Fragment 1: `STUDENT(Age <= 18)`
- Fragment 2: `STUDENT(Age > 18)`
Then we can apply vertical fragmentation to each fragment:
- Fragment 1a: `STUDENT_1a(Student_ID, Name)`
- Fragment 1b: `STUDENT_1b(Student_ID, Age, GPA)`
This hybrid approach allows for greater flexibility in distributing data.
---
**(b) Need for Distributed DBMS over Centralized DBMS and Structure of Distributed DBMS (5 Marks)**
**Need for Distributed DBMS over Centralized DBMS**:
1. **Geographical Distribution**:
- In many organizations, data is distributed across multiple geographic locations. A centralized DBMS would result in high communication costs and latency as all users access a single database over the network. A DDBMS allows data to be stored closer to where it's used, reducing access time and communication overhead.
2. **Scalability**:
- A centralized DBMS becomes difficult to scale as the number of users and data grows. Distributed databases can scale horizontally by adding more nodes, thus handling larger amounts of data and more users efficiently.
3. **Reliability and Availability**:
- In a centralized DBMS, if the central database fails, the entire system is inaccessible. A DDBMS, on the other hand, increases system availability by storing data redundantly across multiple sites. If one site goes down, other sites can still operate, ensuring higher availability and reliability.
4. **Performance**:
- With a DDBMS, data is processed closer to where it is accessed, resulting in lower data access time. Queries can be processed in parallel across multiple nodes, improving overall performance compared to a centralized system.
5. **Local Autonomy**:
- In large organizations, different departments or branches often need some level of autonomy over their data. A DDBMS allows local sites to maintain control over their local databases while still being part of the overall distributed system.
**Structure of Distributed DBMS**:
The structure of a DDBMS typically involves several key components and layers:
1. **Distributed Database**:
- The distributed database is the collection of databases physically located at different sites but logically connected via the DDBMS. The data can be fragmented, replicated, or both across these locations.
2. **Global and Local Schema**:
- **Global Schema**: This provides a unified view of the entire distributed database system. It defines how the distributed data is logically organized and accessible.
- **Local Schema**: Each site may have its own local database schema, representing the data stored at that site.
3. **Distributed Query Processor**:
- The distributed query processor is responsible for processing queries that access data across multiple sites. It breaks down global queries into subqueries and sends them to the appropriate local sites. It also optimizes queries to reduce network traffic and improve efficiency.
4. **Data Replication and Fragmentation**:
- Data replication ensures that copies of the data are stored at multiple locations to enhance availability and fault tolerance. Fragmentation divides the data into smaller parts, which are distributed across the network.
5. **Transaction Manager**:
- The transaction manager ensures that transactions in a distributed environment follow the ACID properties. It coordinates the execution of transactions across multiple sites and ensures that data remains consistent in case of failures.
6. **Communication Network**:
- The communication network connects all the distributed sites. It enables data transfer and query processing across geographically dispersed locations.
**Structure of DDBMS**:
```
+-----------------------------+
| Global Database View |
+-----------------------------+
| |
+---------------+ +---------------+
| Local Site 1 | | Local Site 2 | ... (Local Sites N)
| (DB1) | | (DB2) |
+---------------+ +---------------+
| |
+-----------------------------------+
| Distributed Query Processor |
+-----------------------------------+
|
+-----------------------------------+
| Transaction Manager & Coordinator |
+-----------------------------------+
|
+--------------------------+
| Communication Network |
+--------------------------+
```
Q8. An organization needs to provide Medical facilities to its employees and their dependents. Organization is having a list of Doctors, Hospitals and Test centres for the employees facility. An employee may get Medical facility from the list of Doctors, Hospitals and Test centres provided by the organization tothem. Employee does not need to pay anything for the facilities availed. The Doctors, Hospitals andTest centres directly raise their bill to the organization.
Identify the entities, relationships, constraints and cardinality and construct an ER diagram for the above mentioned specifications. List your assumptions and clearly indicate the cardinality mappings as well as any role indicators in your ER diagram.
Ans:- Entities, Relationships, and Constraints for the Medical Facility System
**Entities**:
1. **Employee**: Represents the employees of the organization who can avail of the medical facilities.
- Attributes: `Employee_ID (PK)`, `Name`, `Department`, `Position`, `Contact_Details`, `Date_of_Joining`.
2. **Dependent**: Represents the dependents (family members) of the employees who are also entitled to medical facilities.
- Attributes: `Dependent_ID (PK)`, `Name`, `Relationship_with_Employee`, `Employee_ID (FK)`.
3. **Doctor**: Represents the doctors providing medical services.
- Attributes: `Doctor_ID (PK)`, `Name`, `Specialization`, `Contact_Details`.
4. **Hospital**: Represents the hospitals in the organization's network for providing medical services.
- Attributes: `Hospital_ID (PK)`, `Name`, `Location`, `Contact_Details`.
5. **Test_Centre**: Represents the test centers where medical tests are conducted.
- Attributes: `Test_Centre_ID (PK)`, `Name`, `Location`, `Contact_Details`.
6. **Medical_Service**: Represents the medical services provided to the employees or their dependents.
- Attributes: `Service_ID (PK)`, `Service_Type (Consultation/Test)`, `Date`, `Cost`, `Employee_ID (FK)`, `Doctor_ID (FK)`, `Hospital_ID (FK)`, `Test_Centre_ID (FK)` (depending on the type of service).
7. **Bill**: Represents the bill raised by the doctors, hospitals, and test centers for the services provided.
- Attributes: `Bill_ID (PK)`, `Date`, `Amount`, `Service_ID (FK)`, `Paid_By (organization)`.
**Relationships**:
1. **Avails**:
- Between `Employee` and `Medical_Service`. It indicates that an employee or their dependent avails of a medical service.
- Cardinality: One employee can avail multiple services, but each service is availed by only one employee or dependent.
- `1:N` (One-to-Many).
2. **Dependents_of**:
- Between `Employee` and `Dependent`. It shows that an employee can have multiple dependents.
- Cardinality: One employee can have many dependents, but a dependent belongs to only one employee.
- `1:N` (One-to-Many).
3. **Provides_Service**:
- Between `Doctor`, `Hospital`, and `Medical_Service`. It indicates that a doctor or hospital provides a medical service to an employee or dependent.
- Cardinality: One doctor or hospital can provide multiple services, but each service is provided by one doctor or one hospital.
- `1:N` (One-to-Many).
4. **Conducts_Test**:
- Between `Test_Centre` and `Medical_Service`. It indicates that a test center conducts medical tests for the employee or dependent.
- Cardinality: One test center can conduct multiple tests, but each test is conduct
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