database management system assignment solution

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• DBMS Tutorial - Database Management System

Basic of DBMS

• Introduction of DBMS (Database Management System) - Set 1
• History of DBMS
• Advantages of Database Management System

Disadvantages of DBMS

• Application of DBMS
• Need for DBMS
• DBMS Architecture 1-level, 2-Level, 3-Level
• Difference between File System and DBMS

Entity Relationship Model

• Introduction of ER Model
• Structural Constraints of Relationships in ER Model
• Difference between entity, entity set and entity type
• Difference between Strong and Weak Entity
• Generalization, Specialization and Aggregation in ER Model
• Recursive Relationships in ER diagrams

Relational Model

• Introduction of Relational Model and Codd Rules in DBMS
• Types of Keys in Relational Model (Candidate, Super, Primary, Alternate and Foreign)
• Anomalies in Relational Model
• Mapping from ER Model to Relational Model
• Strategies for Schema design in DBMS

Relational Algebra

• Introduction of Relational Algebra in DBMS
• Basic Operators in Relational Algebra
• Extended Operators in Relational Algebra
• SQL | Join (Inner, Left, Right and Full Joins)
• Join operation Vs Nested query in DBMS
• Tuple Relational Calculus (TRC) in DBMS
• Domain Relational Calculus in DBMS

Functional Dependencies

• Functional Dependency and Attribute Closure
• Armstrong's Axioms in Functional Dependency in DBMS
• Equivalence of Functional Dependencies
• Canonical Cover of Functional Dependencies in DBMS

Normalisation

• Introduction of Database Normalization
• Normal Forms in DBMS
• First Normal Form (1NF)
• Second Normal Form (2NF)
• Boyce-Codd Normal Form (BCNF)
• Introduction of 4th and 5th Normal Form in DBMS
• The Problem of Redundancy in Database
• Database Management System | Dependency Preserving Decomposition
• Lossless Decomposition in DBMS
• Lossless Join and Dependency Preserving Decomposition
• Denormalization in Databases

Transactions and Concurrency Control

• Concurrency Control in DBMS
• ACID Properties in DBMS
• Implementation of Locking in DBMS
• Lock Based Concurrency Control Protocol in DBMS
• Graph Based Concurrency Control Protocol in DBMS
• Two Phase Locking Protocol
• Multiple Granularity Locking in DBMS
• Polygraph to check View Serializability in DBMS
• Log based Recovery in DBMS
• Timestamp based Concurrency Control
• Dirty Read in SQL
• Types of Schedules in DBMS
• Conflict Serializability in DBMS
• Condition of schedules to View-equivalent
• Recoverability in DBMS
• Precedence Graph for Testing Conflict Serializability in DBMS
• Database Recovery Techniques in DBMS
• Starvation in DBMS
• Deadlock in DBMS
• Types of Schedules based Recoverability in DBMS
• Why recovery is needed in DBMS

Indexing, B and B+ trees

• Indexing in Databases - Set 1
• Introduction of B-Tree
• Insert Operation in B-Tree
• Delete Operation in B-Tree
• Introduction of B+ Tree
• Bitmap Indexing in DBMS
• Inverted Index
• Difference between Inverted Index and Forward Index
• SQL Queries on Clustered and Non-Clustered Indexes

File organization

• File Organization in DBMS - Set 1
• File Organization in DBMS | Set 2
• File Organization in DBMS | Set 3

DBMS Interview questions and Last minute notes

• Last Minute Notes - DBMS
• Commonly asked DBMS interview questions
• Commonly asked DBMS interview questions | Set 2

DBMS GATE Previous Year Questions

• Database Management System - GATE CSE Previous Year Questions
• Database Management Systems | Set 2
• Database Management Systems | Set 3
• Database Management Systems | Set 4
• Database Management Systems | Set 5
• Database Management Systems | Set 6
• Database Management Systems | Set 7
• Database Management Systems | Set 8

Introduction of DBMS (Database Management System) – Set 1

A Database Management System (DBMS) is a software system that is designed to manage and organize data in a structured manner. It allows users to create, modify, and query a database, as well as manage the security and access controls for that database.

DBMS provides an environment to store and retrieve the data in coinvent and efficient manner.

Key Features of DBMS

• Data modeling: A DBMS provides tools for creating and modifying data models, which define the structure and relationships of the data in a database.
• Data storage and retrieval: A DBMS is responsible for storing and retrieving data from the database, and can provide various methods for searching and querying the data.
• Concurrency control: A DBMS provides mechanisms for controlling concurrent access to the database, to ensure that multiple users can access the data without conflicting with each other.
• Data integrity and security: A DBMS provides tools for enforcing data integrity and security constraints, such as constraints on the values of data and access controls that restrict who can access the data.
• Backup and recovery: A DBMS provides mechanisms for backing up and recovering the data in the event of a system failure.
• DBMS can be classified into two types: Relational Database Management System (RDBMS) and Non-Relational Database Management System (NoSQL or Non-SQL)
• RDBMS: Data is organized in the form of tables and each table has a set of rows and columns. The data are related to each other through primary and foreign keys.
• NoSQL: Data is organized in the form of key-value pairs, documents, graphs, or column-based. These are designed to handle large-scale, high-performance scenarios.

A database is a collection of interrelated data which helps in the efficient retrieval, insertion, and deletion of data from the database and organizes the data in the form of tables, views, schemas, reports, etc. For Example, a university database organizes the data about students, faculty, admin staff, etc. which helps in the efficient retrieval, insertion, and deletion of data from it.

Database Languages

Data definition language, data manipulation language, data control language, transactional control language.

DDL is the short name for Data Definition Language, which deals with database schemas and descriptions, of how the data should reside in the database.

• CREATE: to create a database and its objects like (table, index, views, store procedure, function, and triggers)
• ALTER: alters the structure of the existing database
• DROP: delete objects from the database
• TRUNCATE: remove all records from a table, including all spaces allocated for the records are removed
• COMMENT: add comments to the data dictionary
• RENAME: rename an object

DML is the short name for Data Manipulation Language which deals with data manipulation and includes most common SQL statements such SELECT, INSERT, UPDATE, DELETE, etc., and it is used to store, modify, retrieve, delete and update data in a database. Data query language(DQL) is the subset of “Data Manipulation Language”. The most common command of DQL is SELECT statement. SELECT statement help on retrieving the data from the table without changing anything in the table.

• SELECT: retrieve data from a database
• INSERT: insert data into a table
• UPDATE: updates existing data within a table
• DELETE: Delete all records from a database table
• MERGE: UPSERT operation (insert or update)
• CALL: call a PL/SQL or Java subprogram
• EXPLAIN PLAN: interpretation of the data access path
• LOCK TABLE: concurrency Control

DCL is short for Data Control Language which acts as an access specifier to the database.(basically to grant and revoke permissions to users in the database

• GRANT: grant permissions to the user for running DML(SELECT, INSERT, DELETE,…) commands on the table
• REVOKE: revoke permissions to the user for running DML(SELECT, INSERT, DELETE,…) command on the specified table

TCL is short for Transactional Control Language which acts as an manager for all types of transactional data and all transactions. Some of the command of TCL are

• Roll Back: Used to cancel  or Undo changes made in the database 
• Commit: It is used to apply or save changes in the database
• Save Point: It is used to save the data on the temporary basis in the database

Data Query Language (DQL):

Data query language(DQL) is the subset of “Data Manipulation Language” . The most common command of DQL is 1the SELECT statement . SELECT statement helps us in retrieving the data from the table without changing anything or modifying the table. DQL is very important for retrieval of essential data from a database.

Database Management System

The software which is used to manage databases is called Database Management System (DBMS). For Example, MySQL, Oracle, etc. are popular commercial DBMS used in different applications. DBMS allows users the following tasks: 

• Data Definition: It helps in the creation, modification, and removal of definitions that define the organization of data in the database. 
• Data Updation: It helps in the insertion, modification, and deletion of the actual data in the database. 
• Data Retrieval: It helps in the retrieval of data from the database which can be used by applications for various purposes. 
• User Administration: It helps in registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information corrupted by unexpected failure.

Applications of DBMS:

• Enterprise Information: Sales, accounting, human resources, Manufacturing, online retailers.
• Banking and Finance Sector: Banks maintaining the customer details, accounts, loans, banking transactions, credit card transactions. Finance: Storing the information about sales and holdings, purchasing of financial stocks and bonds.
• University: Maintaining the information about student course enrolled information, student grades, staff roles.
• Airlines: Reservations and schedules.
• Telecommunications: Prepaid, postpaid bills maintance.

Paradigm Shift from File System to DBMS

  File System manages data using files on a hard disk. Users are allowed to create, delete, and update the files according to their requirements. Let us consider the example of file-based University Management System. Data of students is available to their respective Departments, Academics Section, Result Section, Accounts Section, Hostel Office, etc. Some of the data is common for all sections like Roll No, Name, Father Name, Address, and Phone number of students but some data is available to a particular section only like Hostel allotment number which is a part of the hostel office. Let us discuss the issues with this system:

• Redundancy of data: Data is said to be redundant if the same data is copied at many places. If a student wants to change their Phone number, he or she has to get it updated in various sections. Similarly, old records must be deleted from all sections representing that student.
• Inconsistency of Data: Data is said to be inconsistent if multiple copies of the same data do not match each other. If the Phone number is different in Accounts Section and Academics Section, it will be inconsistent. Inconsistency may be because of typing errors or not updating all copies of the same data.
• Difficult Data Access: A user should know the exact location of the file to access data, so the process is very cumbersome and tedious. If the user wants to search the student hostel allotment number of a student from 10000 unsorted students’ records, how difficult it can be.
• Unauthorized Access: File Systems may lead to unauthorized access to data. If a student gets access to a file having his marks, he can change it in an unauthorized way.
• No Concurrent Access: The access of the same data by multiple users at the same time is known as concurrency. The file system does not allow concurrency as data can be accessed by only one user at a time.
• No Backup and Recovery: The file system does not incorporate any backup and recovery of data if a file is lost or corrupted.

Advantages of DBMS

• Data organization: A DBMS allows for the organization and storage of data in a structured manner, making it easy to retrieve and query the data as needed.
• Data integrity: A DBMS provides mechanisms for enforcing data integrity constraints, such as constraints on the values of data and access controls that restrict who can access the data.
• Concurrent access: A DBMS provides mechanisms for controlling concurrent access to the database, to ensure that multiple users can access the data without conflicting with each other.
• Data security: A DBMS provides tools for managing the security of the data, such as controlling access to the data and encrypting sensitive data.
• Data sharing: A DBMS allows multiple users to access and share the same data, which can be useful in a collaborative work environment.
• Complexity: DBMS can be complex to set up and maintain, requiring specialized knowledge and skills.
• Performance overhead: The use of a DBMS can add overhead to the performance of an application, especially in cases where high levels of concurrency are required.
• Scalability: The use of a DBMS can limit the scalability of an application, since it requires the use of locking and other synchronization mechanisms to ensure data consistency.
• Cost: The cost of purchasing, maintaining and upgrading a DBMS can be high, especially for large or complex systems.
• Limited Use Cases: Not all use cases are suitable for a DBMS, some solutions don’t need high reliability, consistency or security and may be better served by other types of data storage.

These are the main reasons which made a shift from file system to DBMS. Also, see

A Database Management System (DBMS) is a software system that allows users to create, maintain, and manage databases. It is a collection of programs that enables users to access and manipulate data in a database. A DBMS is used to store, retrieve, and manipulate data in a way that provides security, privacy, and reliability.

Several Types of DBMS

• Relational DBMS (RDBMS): An RDBMS stores data in tables with rows and columns, and uses SQL (Structured Query Language) to manipulate the data.
• Object-Oriented DBMS (OODBMS): An OODBMS stores data as objects, which can be manipulated using object-oriented programming languages.
• NoSQL DBMS: A NoSQL DBMS stores data in non-relational data structures, such as key-value pairs, document-based models, or graph models.

Overall, a DBMS is a powerful tool for managing and manipulating data, and is used in many industries and applications, such as finance, healthcare, retail, and more.

• Database Management System – Introduction | Set 2
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Database systems, final project assignment and ideas.

A large portion (20%) of your grade in 6.830 consists of a final project. This project is meant to be a substantial independent research or engineering effort related to material we have studied in class. Your project may involve a comparison of systems we have read about, an application of database techniques to a system you are familiar with, or be a database-related project in your research area.

This document describes what is expected of a final project and proposes some possible project ideas.

What Is Expected

Good class projects can vary dramatically in complexity, scope, and topic. The only requirement is that they be related to something we have studied in this class and that they contain some element of research — e.g., that you do more than simply engineer a piece of software that someone else has described or architected. To help you determine if your idea is of reasonable scope, we will arrange to meet with each group several times throughout the semester.

What to Hand In

There are two written deliverables, a project proposal and a final report.

Project Proposal : The proposal should consist of 1-2 pages describing the problem you plan to solve, outlining how you plan to solve it, and describing what you will “deliver” for the final project. We will arrange short meetings with every group before the project proposal to help you refine your topic and would be happy to provide feedback on a draft of your proposal before it is due.

Final Report : You should prepare a conference-style report on your project with maximum length of 15 pages (10 pt font or larger, one or two columns, 1 inch margins, single or double spaced — more is not better). Your report should introduce and motivate the problem your project addresses, describe related work in the area, discuss the elements of your solution, and present results that measure the behavior, performance, or functionality of your system (with comparisons to other related systems as appropriate.)

Because this report is the primary deliverable upon which you will be graded, do not treat it as an afterthought . Plan to leave at least a week to do the writing, and make sure you proofread and edit carefully!

Please submit a paper copy of your report. You will also be expected to give a presentation on your project in class that will provide an opportunity for you to present a short demo of your work and show what you have done to other students in the class. Details about the format of the presentation will be posted as the date gets closer.

Project Ideas

The following is a list of possible project ideas; you are not required to choose from this list — in fact, we encourage you to try to solve a problem of your own choosing! If you are interested in working on one of these projects, contact the instructors and we can put you in touch with students and others around MIT working on these ideas. Note that these are not meant to be complete project proposals, but just suggestions for areas to explore — you will need to flesh them out into complete projects by talking with your group members, the course staff, and graduate students working on these projects.

Being able to compare performance of different DBMSs and different storage and access techniques is vital for the database community. To this purpose several synthetic benchmark has been designed and adopted over time (see TPC-C, TPC-H etc…). Wikipedia open source application, and publicly available data (several TB!!), provide a great starting point to develop a benchmark based on real-world data. Moreover, we obtained from the Wikimedia foundation 10% of 4 months of Wikipedia accesses (roughly 20 billion HTTP requests!). The project will consists in using this real-world data, queries and access patterns to design one of the first benchmarks based on real-world data.

Amazon RDS is a database service provided within the EC2 cloud. An interesting project consists in investigating performance and scalability characteristics of Amazon RDS. Also since RDS services run in a virtualized environment, studying the “stability” and “isolation” of the performance offered is interesting.

Hosted database services such as Amazon RDS, Microso SQL Azure are starting to become popular. It is still unclear what is the performance impact of running applications on a local (non-hosted) platform, such as a local enterprise datacenter, while having the data hosted “in the cloud”. An interesting project aim at investigating the performance impact for different classes of applications e.g., OLAP, OLTP, Web.

Performance monitoring is an important portion of data-center and database management. An interesting project consists in developing a monitoring interface for MySQL, capable of monitoring multiple nodes, reporting both DBMS internal statistics, and OS-level statistics (CPU, RAM, DIsk), potentially automating the detection of saturation of resources.

Being able to predict cpu/mem/disk load of database machines can enable “consolidation”, i.e., the co-location of multiple DB within a smaller set of physical servers. We have an interesting set of data from real-world data-centers, the project would consist in investigating machine-learning and other predictive techniques on such real-world data.

Flash memories are very promising technologies, providing lower latency for random operations. However, they have a series of unusual restrictions and performance. An interesting project investigates the performance impact of using flash memories for DB applications.

Often database assume data to be stored on a local disk, however data stored on network file systems can allow for easier administration, and is rather common in enterprises using SAN or NAS storage systems. The project will investigate the impact of local-vs-networked storage on query performance.

Partition-aware object-relational mapping. Many programmers seem to prefer object-relational mapping (ORM) layers such as like Ruby on Rails or Hibernate to a traditional ODBC/JDBC interface to a database. In the H-store Project we have been studying performance benefits that can be obtained in a “partitonable” database, where the tables can be cleanly partitioned according to some key attribute (for example, customer-id), and queries are generally run over just one partition. The goal of this project would be to study how to exploit partitioning to improve the performance of a distributed ORM layer.

Twitter provides a fire hose of data. Automatically filtering, aggregating, analyzing such data can allow a way to harness the full value of the data, extracting valuable information. The idea of this project is investigating stream processing technology to operate on social streams.

Client-side database. Build a Javascript library that client-side Web applications can use to access a database; the idea is to avoid the painful way in which current client-side application have to use the XMLHttpRequest interface to access server-side objects asynchronously. This layer should cache objects on the client side whenever possible, but be backed by a shared, server-side database system.

As a related project, HTML5 browsers (including WebKit, used by Safari and Chrome), include a client-side SQL API in JavaScript. This project would involve investigating how to user such a database to improve client performance, offload work from the server, etc.

Preventing denial-of-service attacks on database systems. Databases are a vulnerable point in many Web sites, because it is often possible for attackers to make some simple request that causes the Web site to issue queries asking the database to do a lot of work. By issuing a large number of such requests, and attacker can effectively issue a denial of service attack against the Web site by disabling the database. The goal of this project would be to develop a set of techniques to counter this problem — for example, one approach might be to modify the database scheduler so that it doesn’t run the same expensive queries over and over.

Auto-admin tools to recommend indices, etc. Design a tool that recommends a set of indices to build given a particular workload and a set of statistics in a database. Alternatively investigate the question of which materialized views to create in a data-warehousing system, such as

Scientific community data management requirements significantly differ from regular web/enterprise ones. To this purpose a specialized DB is currently being developed named: SciDB. Studying performance of SciDB on dedicated servers vs. on virtualized environment such as EC2 is an intriguing topic. Another interesting investigation would cover the impact on SciDB performance of storing the data over the network (e.g., network file system). A third interesting project would explore the performance of clustering algorithms on SciDB vs. MapReduce.

Asynchronous Database Access. Client software interacts with standard SQL databases via a blocking interface like ODBC or JDBC; the client sends SQL, waits for the database to process the query, and receives an answer. A non-blocking interface would allow a single client thread to issue many parallel queries from the same thread, with potential for some impressive performance gains. This project would investigate how this would work (do the queries have to be in different transactions? what kind of modification would need to be made to the database) and would look at the possible performance gains in some typical database benchmarks or applications.

Extend SimpleDB. SimpleDB is very simple. There are a number of ways you might extend it to explore some of the research ideas we have studied in this class. For example, you could add support for optimistic concurrency control and compare its performance to the basic concurrency control scheme you will implement in Problem Set 3. There are a number of other possible projects of this type; we would be happy to discuss these in more detail.

CarTel. In the CarTel project, we are building a system for collecting and managing data from automobiles. There are several possible CarTel related projects: * One of the features of CarTel is a GUI for browsing geo-spatial data collected from cars. We currently have a primitive interface for retrieving parts of the data that are of interest, but developing a more sophisticated interface or query language for browsing and exploring this data would make a great project. * One of the dangers with building a system like CarTel is that it collects relatively sensitive personal information about users location and driving habits. Protecting this information from casual browsers, insurance companies, or other undesired users is important. However, it is also important to be able to combine different users data together to do things like intelligent route planning or vehicle anomaly detection. The goal of this project would be to find a way to securely perform certain types of aggregate queries over CarTel data without exposing personally identifiable information. * We have speed and position data from the last year for 30 taxi cabs on the Boston streets. Think of something exciting you could do with this.

Rollback of long-running or committed transactions. Database systems typically only support UNDO of committed transactions, but there are cases where it might be important to rollback already committed transactions. One approach is to use user-supplied compensating actions, but there may be other models that are possible, or it may be possible to automatically derive such compensating action for certain classes of transactions.

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INFYTQ-DBMS Infosys DBMS(Part-1 & Part-2) Course Exercises and Assignment Solutions

Database Management System Part-1 https://infytq.onwingspan.com/en/app/toc/lex_auth_01275806667282022456_shared/overview

Database Management System Part-2 https://infytq.onwingspan.com/en/app/toc/lex_auth_0127673005629194241_shared/overview

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April 23, 2024

Graduate School selects Salesforce as graduate records management solution

The Graduate School has announced that its next-generation graduate records management solution will be built on the Salesforce platform, replacing the existing GradDB and Graduate School database systems.

The decision comes after an extensive assessment period and stems from the Graduate School’s commitment to modernize and streamline operations while ensuring effectiveness in managing graduate records. The move to Salesforce is expected to provide a more robust and cohesive solution that will better serve the needs of Purdue’s academic community.

The project’s initial phase is underway and will focus on replacing GradDB, which is used by the College of Engineering and some College of Science programs on the West Lafayette campus, with a targeted launch date in October 2024. The Graduate School’s database, which is utilized systemwide by faculty, staff and graduate students on all of Purdue’s campuses, will follow with an expected completion in July 2025.

A dedicated web page has been established to share project-related information and updates. Communications will also be sent out to those directly impacted via their Purdue email accounts and periodic updates will be included in Purdue Today.

Questions related to the database migrations can be sent to Nicole Moody, [email protected] , for the Graduate School or Janet Beagle, [email protected] , for GradDB.

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