Sakar Pradhananga Level Master Programme MCIS Semester Fall Year 2024 Course Distributed Database System Full Marks 100 Pass Marks 60 Time 4 hrs Candidates are required to give their answers in their own words as far as practicable. The figures in the margin indicate full marks. Attempt all the questions. 1. Explain ho distributed database systems address … Read more
Level: Master Year: 2025 Programme: ME/CS/MCIS Full Marks: 50 Course: Distributed Database System Pass Marks: 30 Time: 2hrs Candidates are required to give answers in their own words as far as practicable. The figures in the margin indicate full marks. Question 1: a. Explain the concept of distributed query optimization and its significance in improving … Read more
A Parallel Database Management System (DBMS) is a type of database system that uses multiple processors or computers to perform database operations simultaneously. This approach allows for faster processing of queries and transactions, making it suitable for handling large volumes of data and complex operations. By leveraging parallel processing techniques, these systems aim to improve … Read more
The Three-Phase Commit Protocol (3PC) is a distributed algorithm designed to ensure that all participants in a distributed transaction either commit or abort the transaction in a coordinated manner. It addresses some of the limitations of the Two-Phase Commit (2PC) protocol, particularly in scenarios where a coordinator may fail or where network partitions may occur. … Read more
In distributed database systems, maintaining data integrity and consistency across multiple sites is a complex challenge. The Local Recovery Manager (LRM) plays a vital role in addressing this challenge by managing transactions and ensuring that the database can recover from failures. By maintaining a detailed log file of all operations, the LRM facilitates effective recovery … Read more
Concurrency control mechanisms are crucial in Distributed Databases (DDB) to ensure data consistency and integrity when multiple transactions are executed simultaneously. In a distributed environment, where data is spread across multiple locations, the likelihood of conflicts increases, making it essential to manage how transactions access and modify data. Some key reasons why concurrency control is … Read more
In database systems, a transaction is a sequence of operations performed as a single, logical unit of work that either fully completes or fully fails. This all-or-nothing approach ensures data integrity and consistency within the database. To maintain these qualities, transactions adhere to the ACID properties: Differences Between Flat and Nested Transactions: Aspect Flat Transactions … Read more
Query decomposition is essential in processing distributed queries as it breaks down a high-level query into manageable components, facilitating efficient execution across multiple databases. Data-based client-server architecture in distributed databases (DDB) involves the separation of client and server roles, enhancing scalability and resource management. It includes: 1. Data Distribution: Techniques for distributing data across multiple … Read more
Creating views in a database serves several important purposes, and they can be categorized into different types based on their functionality and use cases. Additionally, authorization control in distributed databases (DDB) is crucial for ensuring data security and integrity. Below, I will discuss the reasons for creating views, their types with examples, and the concept … Read more
Data-based client-server architecture in Distributed Database (DDB) systems is a model where the database is distributed across multiple locations, and clients interact with the database through a server. This architecture allows for improved performance, scalability, and availability of data. In a DDB, data can be stored in different locations, and clients can access this data … Read more