This presentation discusses about the following topics:
Transaction processing systems
Introduction to TRANSACTION
Need for TRANSACTION
Operations
Transaction Execution and Problems
Transaction States
Transaction Execution with SQL
Transaction Properties
Transaction Log
This document discusses transaction processing and concurrency control in database systems. It defines a transaction as a unit of program execution that accesses and possibly modifies data. It describes the key properties of transactions as atomicity, consistency, isolation, and durability. It discusses how concurrency control techniques like locking and two-phase locking protocols are used to ensure serializable execution of concurrent transactions.
ACID properties
Atomicity, Consistency, Isolation, Durability
Transactions should possess several properties, often called the ACID properties; they should be enforced by the concurrency control and recovery methods of the DBMS.
The document discusses transaction processing in distributed database systems. It covers transaction concepts and models, distributed concurrency control, distributed reliability, and other topics. Transaction processing involves issues like transaction structure, internal database consistency, reliability protocols, concurrency control algorithms, and replica control protocols. The goal is to provide atomic and reliable execution of transactions in the presence of failures and concurrent accesses across distributed nodes.
This document discusses transaction processing systems (TPS). It defines a transaction as a group of tasks that updates or retrieves data. A TPS collects, stores, modifies and retrieves enterprise data transactions. Transactions must follow the ACID properties - atomicity, consistency, isolation, and durability. There are two types of TPS - batch processing, which collects and stores data in batches, and real-time processing, which immediately processes data. Long duration transactions pose challenges as user interaction is required and partial data may be exposed if not committed. Nested transactions and alternatives to waits and aborts can help manage long-running transactions.
This document summarizes key concepts from Chapter 14 of the textbook "Database System Concepts, 6th Ed." including:
1) A transaction is a unit of program execution that accesses and updates data items. For integrity, transactions must have ACID properties: atomicity, consistency, isolation, and durability.
2) Concurrency control ensures serializable execution of concurrent transactions to maintain consistency. Schedules must be conflict serializable and recoverable.
3) SQL supports transactions and different isolation levels to balance consistency and concurrency. The default isolation level is usually serializable but some systems allow weaker isolation.
The document discusses concurrency control in database management systems. It defines key terms like transaction, atomicity, consistency, isolation, and durability. Transactions must have ACID properties - Atomicity, Consistency, Isolation, and Durability. Atomicity means all operations of a transaction are completed or none are. Consistency means the database remains consistent before and after a transaction. Isolation means transactions appear to execute serially despite concurrent execution. Durability means committed transactions persist even after failures.
The document discusses the benefits of exercise for mental health. It states that regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help alleviate symptoms of mental illness.
This document discusses transaction processing and concurrency control in database systems. It defines a transaction as a unit of program execution that accesses and possibly modifies data. It describes the key properties of transactions as atomicity, consistency, isolation, and durability. It discusses how concurrency control techniques like locking and two-phase locking protocols are used to ensure serializable execution of concurrent transactions.
ACID properties
Atomicity, Consistency, Isolation, Durability
Transactions should possess several properties, often called the ACID properties; they should be enforced by the concurrency control and recovery methods of the DBMS.
The document discusses transaction processing in distributed database systems. It covers transaction concepts and models, distributed concurrency control, distributed reliability, and other topics. Transaction processing involves issues like transaction structure, internal database consistency, reliability protocols, concurrency control algorithms, and replica control protocols. The goal is to provide atomic and reliable execution of transactions in the presence of failures and concurrent accesses across distributed nodes.
This document discusses transaction processing systems (TPS). It defines a transaction as a group of tasks that updates or retrieves data. A TPS collects, stores, modifies and retrieves enterprise data transactions. Transactions must follow the ACID properties - atomicity, consistency, isolation, and durability. There are two types of TPS - batch processing, which collects and stores data in batches, and real-time processing, which immediately processes data. Long duration transactions pose challenges as user interaction is required and partial data may be exposed if not committed. Nested transactions and alternatives to waits and aborts can help manage long-running transactions.
This document summarizes key concepts from Chapter 14 of the textbook "Database System Concepts, 6th Ed." including:
1) A transaction is a unit of program execution that accesses and updates data items. For integrity, transactions must have ACID properties: atomicity, consistency, isolation, and durability.
2) Concurrency control ensures serializable execution of concurrent transactions to maintain consistency. Schedules must be conflict serializable and recoverable.
3) SQL supports transactions and different isolation levels to balance consistency and concurrency. The default isolation level is usually serializable but some systems allow weaker isolation.
The document discusses concurrency control in database management systems. It defines key terms like transaction, atomicity, consistency, isolation, and durability. Transactions must have ACID properties - Atomicity, Consistency, Isolation, and Durability. Atomicity means all operations of a transaction are completed or none are. Consistency means the database remains consistent before and after a transaction. Isolation means transactions appear to execute serially despite concurrent execution. Durability means committed transactions persist even after failures.
The document discusses the benefits of exercise for mental health. It states that regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help alleviate symptoms of mental illness.
This document summarizes a student's research project on improving the performance of real-time distributed databases. It proposes a "user control distributed database model" to help manage overload transactions at runtime. The abstract introduces the topic and outlines the contents. The introduction provides background on distributed databases and the motivation for the student's work in developing an approach to reduce runtime errors during periods of high load. It summarizes some existing research on concurrency control in centralized databases.
This document discusses different memory management techniques used in operating systems. It begins by describing the basic components and functions of memory. It then explains various memory management algorithms like overlays, swapping, paging and segmentation. Overlays divide a program into instruction sets that are loaded and unloaded as needed. Swapping loads entire processes into memory for execution then writes them back to disk. Paging and segmentation are used to map logical addresses to physical addresses through page tables and segment tables respectively. The document compares advantages and limitations of these approaches.
The document discusses transaction concepts in database systems. It defines transactions as units of program execution that access and update database items. Transactions must satisfy the ACID properties of atomicity, consistency, isolation, and durability. Concurrent transaction execution allows for increased throughput but requires mechanisms to ensure serializability and recoverability. The document describes transaction states, schedule serializability testing using precedence graphs, and the goal of concurrency control protocols to enforce serializability without examining schedules after execution.
The document discusses transaction processing and ACID properties in databases. It defines a transaction as a group of tasks that must be atomic, consistent, isolated, and durable. It provides examples of transactions involving bank account transfers. It explains the four ACID properties - atomicity, consistency, isolation, and durability. It also discusses transaction states, recovery, concurrency control techniques like two-phase locking and timestamps to prevent deadlocks.
comprehensive lecture on join odering fragments queries. it is the topic of DDBMS and the content are taken from multiple sources including google, book, class lecture.
prepared by IFZAL HUSSAIN student of CS in SHAHEED BENAZIR BHUTTO UNIVERSITY SHERINGAL DIR UPPER KPK, PAKISTAN.
This presentation will discusses about the following topics: Importance of Data Models
Basic Building Blocks
Business Rules
Translating Business Rules into Data Models
Evolution of Data Models
Hierarchical Data Model
Network Data Model
Relational Data Model
Entity Relational Model
Object Model
Summary
Followed by a Quiz
Database recovery techniques restore the database to its most recent consistent state before a failure. There are three states: pre-failure consistency, failure occurrence, and post-recovery consistency. Recovery approaches include steal/no-steal and force/no-force, while update strategies are deferred or immediate. Shadow paging maintains current and shadow tables to recover pre-transaction states. The ARIES algorithm analyzes dirty pages, redoes committed transactions, and undoes uncommitted ones. Disk crash recovery uses log/database separation or backups.
Why needed ACID properties?
->Failures of various kinds, such as hardware failures and system crashes
-> Concurrent execution of multiple transactions
->ACID properties in order to ensure accuracy, completeness, and data integrity.
The document discusses concurrency control in databases. It describes transactions, their ACID properties (atomicity, consistency, independence, durability), and problems that can occur with concurrent transactions like lost updates, integrity constraint violations, and inconsistent retrievals. It also covers serialization, serial schedules, serializable schedules, and concurrency control techniques like locking, timestamps, and optimistic methods.
The document discusses various concurrency control techniques for database systems, including lock-based protocols, timestamp-based protocols, and graph-based protocols. Lock-based protocols use locks to control concurrent access to data with different lock modes. Timestamp-based protocols assign timestamps to transactions and manage concurrency to ensure transactions execute in timestamp order. Graph-based protocols impose a partial ordering on data items modeled as a directed acyclic graph.
Concurrency control mechanisms use various protocols like lock-based, timestamp-based, and validation-based to maintain database consistency when transactions execute concurrently. Lock-based protocols use locks on data items to control concurrent access, with two-phase locking being a common approach. Timestamp-based protocols order transactions based on timestamps to ensure serializability. Validation-based protocols validate that a transaction's writes do not violate serializability before committing its writes.
The document discusses the ACID properties of database transactions: Atomicity ensures transactions are all or nothing; Consistency ensures transactions change the database from one valid state to another; Isolation ensures transactions execute serially despite concurrent execution; Durability ensures transaction changes are permanent even if the database fails. Each property is managed by a different database component - transaction management, application programmer, concurrency control manager, and recovery manager respectively.
The document discusses the ACID properties that guarantee database transactions are processed reliably. ACID is an acronym that stands for atomicity, consistency, isolation, and durability. Atomicity means all or nothing transactions. Consistency means transactions can only change data in allowed ways and guarantees the committed transaction state. Isolation means transactions appear to be the only action and transactions are independent. Durability means committed data will never be lost once a transaction is successfully completed.
This document discusses lock-based protocols for concurrency control. It describes that locks can be requested in exclusive or shared mode to control concurrent access to data items. A lock compatibility matrix is used to determine if a requested lock is compatible with existing locks held by other transactions. The Two Phase Locking protocol is introduced to ensure conflict serializable schedules by restricting transactions to an growing phase where they only acquire locks and a shrinking phase where they only release locks.
This document discusses stack organization and operations. A stack is a last-in, first-out data structure where items added last are retrieved first. It uses a stack pointer to track the top of the stack. Common operations are push, which adds an item to the top of the stack, and pop, which removes an item from the top. Stacks can be implemented with registers, using a stack pointer and data register. Reverse Polish notation places operators after operands, making it suitable for stack-based expression evaluation.
Coupling refers to the interdependence between software modules. There are several types of coupling from loose to tight, with the tightest being content coupling where one module relies on the internal workings of another. Cohesion measures how strongly related the functionality within a module is, ranging from coincidental to functional cohesion which is the strongest. Tight coupling and low cohesion can make software harder to maintain and reuse modules.
Transaction management and concurrency controlDhani Ahmad
The document discusses transaction management and concurrency control in database systems. It covers topics such as transactions and their properties, concurrency control methods like locking, time stamping and optimistic control, and database recovery management. The goal of these techniques is to coordinate simultaneous transaction execution while maintaining data consistency and integrity in multi-user database environments.
recognizer for a language, Deterministic finite automata, Non-deterministic finite automata, conversion of NFA to DFA, Regular Expression to NFA, Thomsons Construction
Unit 4 chapter - 8 Transaction processing Concepts (1).pptxKoteswari Kasireddy
The document provides an overview of transaction processing concepts. It defines a transaction as a sequence of operations that transforms a database from one consistent state to another. Transaction processing systems are characterized by large databases, high volumes of concurrent users, and need for reliability. The document discusses transaction states, logging, concurrency control techniques like locking, and properties like atomicity, consistency, isolation and durability (ACID) that ensure transaction integrity.
The document discusses transaction concepts in database systems. It defines a transaction as a series of actions performed by a single user or application to access and modify database contents. Transactions must follow the ACID properties - atomicity, consistency, isolation, and durability. Concurrency control techniques like locking are used to ensure transactions execute correctly in a concurrent environment without interfering with each other. Serializability is discussed as a way to identify which non-serial schedules maintain consistency. Conflict serializability and precedence graphs are described as a technique to test schedules for serializability.
This document summarizes a student's research project on improving the performance of real-time distributed databases. It proposes a "user control distributed database model" to help manage overload transactions at runtime. The abstract introduces the topic and outlines the contents. The introduction provides background on distributed databases and the motivation for the student's work in developing an approach to reduce runtime errors during periods of high load. It summarizes some existing research on concurrency control in centralized databases.
This document discusses different memory management techniques used in operating systems. It begins by describing the basic components and functions of memory. It then explains various memory management algorithms like overlays, swapping, paging and segmentation. Overlays divide a program into instruction sets that are loaded and unloaded as needed. Swapping loads entire processes into memory for execution then writes them back to disk. Paging and segmentation are used to map logical addresses to physical addresses through page tables and segment tables respectively. The document compares advantages and limitations of these approaches.
The document discusses transaction concepts in database systems. It defines transactions as units of program execution that access and update database items. Transactions must satisfy the ACID properties of atomicity, consistency, isolation, and durability. Concurrent transaction execution allows for increased throughput but requires mechanisms to ensure serializability and recoverability. The document describes transaction states, schedule serializability testing using precedence graphs, and the goal of concurrency control protocols to enforce serializability without examining schedules after execution.
The document discusses transaction processing and ACID properties in databases. It defines a transaction as a group of tasks that must be atomic, consistent, isolated, and durable. It provides examples of transactions involving bank account transfers. It explains the four ACID properties - atomicity, consistency, isolation, and durability. It also discusses transaction states, recovery, concurrency control techniques like two-phase locking and timestamps to prevent deadlocks.
comprehensive lecture on join odering fragments queries. it is the topic of DDBMS and the content are taken from multiple sources including google, book, class lecture.
prepared by IFZAL HUSSAIN student of CS in SHAHEED BENAZIR BHUTTO UNIVERSITY SHERINGAL DIR UPPER KPK, PAKISTAN.
This presentation will discusses about the following topics: Importance of Data Models
Basic Building Blocks
Business Rules
Translating Business Rules into Data Models
Evolution of Data Models
Hierarchical Data Model
Network Data Model
Relational Data Model
Entity Relational Model
Object Model
Summary
Followed by a Quiz
Database recovery techniques restore the database to its most recent consistent state before a failure. There are three states: pre-failure consistency, failure occurrence, and post-recovery consistency. Recovery approaches include steal/no-steal and force/no-force, while update strategies are deferred or immediate. Shadow paging maintains current and shadow tables to recover pre-transaction states. The ARIES algorithm analyzes dirty pages, redoes committed transactions, and undoes uncommitted ones. Disk crash recovery uses log/database separation or backups.
Why needed ACID properties?
->Failures of various kinds, such as hardware failures and system crashes
-> Concurrent execution of multiple transactions
->ACID properties in order to ensure accuracy, completeness, and data integrity.
The document discusses concurrency control in databases. It describes transactions, their ACID properties (atomicity, consistency, independence, durability), and problems that can occur with concurrent transactions like lost updates, integrity constraint violations, and inconsistent retrievals. It also covers serialization, serial schedules, serializable schedules, and concurrency control techniques like locking, timestamps, and optimistic methods.
The document discusses various concurrency control techniques for database systems, including lock-based protocols, timestamp-based protocols, and graph-based protocols. Lock-based protocols use locks to control concurrent access to data with different lock modes. Timestamp-based protocols assign timestamps to transactions and manage concurrency to ensure transactions execute in timestamp order. Graph-based protocols impose a partial ordering on data items modeled as a directed acyclic graph.
Concurrency control mechanisms use various protocols like lock-based, timestamp-based, and validation-based to maintain database consistency when transactions execute concurrently. Lock-based protocols use locks on data items to control concurrent access, with two-phase locking being a common approach. Timestamp-based protocols order transactions based on timestamps to ensure serializability. Validation-based protocols validate that a transaction's writes do not violate serializability before committing its writes.
The document discusses the ACID properties of database transactions: Atomicity ensures transactions are all or nothing; Consistency ensures transactions change the database from one valid state to another; Isolation ensures transactions execute serially despite concurrent execution; Durability ensures transaction changes are permanent even if the database fails. Each property is managed by a different database component - transaction management, application programmer, concurrency control manager, and recovery manager respectively.
The document discusses the ACID properties that guarantee database transactions are processed reliably. ACID is an acronym that stands for atomicity, consistency, isolation, and durability. Atomicity means all or nothing transactions. Consistency means transactions can only change data in allowed ways and guarantees the committed transaction state. Isolation means transactions appear to be the only action and transactions are independent. Durability means committed data will never be lost once a transaction is successfully completed.
This document discusses lock-based protocols for concurrency control. It describes that locks can be requested in exclusive or shared mode to control concurrent access to data items. A lock compatibility matrix is used to determine if a requested lock is compatible with existing locks held by other transactions. The Two Phase Locking protocol is introduced to ensure conflict serializable schedules by restricting transactions to an growing phase where they only acquire locks and a shrinking phase where they only release locks.
This document discusses stack organization and operations. A stack is a last-in, first-out data structure where items added last are retrieved first. It uses a stack pointer to track the top of the stack. Common operations are push, which adds an item to the top of the stack, and pop, which removes an item from the top. Stacks can be implemented with registers, using a stack pointer and data register. Reverse Polish notation places operators after operands, making it suitable for stack-based expression evaluation.
Coupling refers to the interdependence between software modules. There are several types of coupling from loose to tight, with the tightest being content coupling where one module relies on the internal workings of another. Cohesion measures how strongly related the functionality within a module is, ranging from coincidental to functional cohesion which is the strongest. Tight coupling and low cohesion can make software harder to maintain and reuse modules.
Transaction management and concurrency controlDhani Ahmad
The document discusses transaction management and concurrency control in database systems. It covers topics such as transactions and their properties, concurrency control methods like locking, time stamping and optimistic control, and database recovery management. The goal of these techniques is to coordinate simultaneous transaction execution while maintaining data consistency and integrity in multi-user database environments.
recognizer for a language, Deterministic finite automata, Non-deterministic finite automata, conversion of NFA to DFA, Regular Expression to NFA, Thomsons Construction
Unit 4 chapter - 8 Transaction processing Concepts (1).pptxKoteswari Kasireddy
The document provides an overview of transaction processing concepts. It defines a transaction as a sequence of operations that transforms a database from one consistent state to another. Transaction processing systems are characterized by large databases, high volumes of concurrent users, and need for reliability. The document discusses transaction states, logging, concurrency control techniques like locking, and properties like atomicity, consistency, isolation and durability (ACID) that ensure transaction integrity.
The document discusses transaction concepts in database systems. It defines a transaction as a series of actions performed by a single user or application to access and modify database contents. Transactions must follow the ACID properties - atomicity, consistency, isolation, and durability. Concurrency control techniques like locking are used to ensure transactions execute correctly in a concurrent environment without interfering with each other. Serializability is discussed as a way to identify which non-serial schedules maintain consistency. Conflict serializability and precedence graphs are described as a technique to test schedules for serializability.
This document discusses transaction management and concurrency control in databases. It defines a transaction as a logical unit of work that must be entirely completed or aborted, with no partial states. Transactions have properties of atomicity, consistency, isolation, and durability. The document uses an example of a sales transaction to illustrate transactions and explains how the database transaction log tracks transactions to support recovery.
The document discusses transaction management in database systems. It covers the ACID properties that transactions must satisfy - atomicity, consistency, isolation, and durability. It also discusses concurrency control techniques used to allow concurrent execution of transactions while preventing anomalies, including strict two-phase locking and lock-based concurrency control. Serializability is introduced as a way to ensure concurrent schedules have the same effect as serial schedules.
This document discusses transaction processing in databases. It covers topics like ACID properties, transaction states, concurrency control techniques like locking, and problems that can occur in transaction processing like dirty reads, lost updates, and phantoms reads. Transaction processing aims to ensure transactions are atomic, consistent, isolated, and durable despite concurrent execution through techniques like locking, logging, and multi-version concurrency control.
This presentation discusses the following topics:
What is Recovery ?
Database Recovery techniques
System log
Working of Commit and Roll back
Recovery techniques
Backup techniques
The document discusses transaction processing systems and transactions. A transaction processing system handles large databases and concurrent users executing transactions. A transaction is a logical unit of database processing that includes database access operations like insertions, deletions, modifications, or retrievals. Transactions must be atomic, consistent, isolated, and durable (ACID properties). Concurrency control mechanisms are needed to ensure transactions execute correctly when run concurrently. Schedules specify the order transactions execute and must be serializable to ensure consistency.
Transaction processing systems handle large databases and hundreds of concurrent users executing transactions. A transaction is a logical unit of database processing that includes database access operations like insertions, deletions, modifications, or retrievals. Transactions must be atomic, consistent, isolated, and durable (ACID properties). Concurrency control techniques like locking and timestamps are used to coordinate concurrent transactions and ensure serializability and isolation. The two-phase locking protocol enforces serializability by acquiring all locks in the growing phase before releasing any locks in the shrinking phase.
The document discusses database recovery techniques. It describes the purpose of database recovery as bringing the database to its last consistent state prior to a failure. It discusses different types of failures and data update techniques like deferred and immediate updating. For deferred updating, recovery involves redoing transactions after the last checkpoint, while for immediate updating, recovery uses undo for active transactions and redo for committed transactions.
This document provides an introduction to transaction processing in database management systems. It discusses key concepts such as transactions, concurrency control, recovery from failures, and desirable transaction properties. The main points covered are:
- A transaction is a logical unit of work that includes database access operations like insert, delete, update, or retrieve.
- Concurrency control is needed to prevent problems that can occur from uncontrolled concurrent execution of transactions, like lost updates or dirty reads.
- Recovery is required to ensure transactions are fully committed or rolled back even after failures, maintaining atomicity and durability.
- Desirable transaction properties include atomicity, consistency, isolation, and durability (ACID).
Chapter 9 introduction to transaction processingJafar Nesargi
This document provides an introduction to transaction processing in database management systems. It discusses key concepts such as transactions, concurrency control, recovery from failures, and desirable transaction properties. The main points covered are:
- A transaction is a logical unit of work that includes database operations that must succeed as a whole or fail as a whole.
- Concurrency control is needed to prevent problems that can arise from uncontrolled concurrent execution of transactions, such as lost updates or dirty reads.
- Recovery is required to handle failures and ensure transactions are fully committed or rolled back. The system log tracks transaction operations.
- Desirable transaction properties include atomicity, consistency, isolation, and durability.
Chapter 9 introduction to transaction processingJafar Nesargi
This document provides an introduction to transaction processing in database management systems. It discusses how multiple users can concurrently access a database using concepts like multiprogramming and interleaving. It defines transactions as logical units of database processing that include database access operations. The document outlines problems that can occur without concurrency control, like lost updates, dirty reads, and incorrect summaries. It also discusses the need for recovery from failures and the basic transaction and system concepts used, including transaction states and operations.
Chapter-10 Transaction Processing and Error RecoveryKunal Anand
This chapter discusses the concept of concurrency in database systems. We talk about different concurrency control techniques along with error recovery.
This document provides information about database transactions in MySQL. It defines a transaction as a logical unit of work that takes a database from one consistent state to another while obeying constraints. Transactions have ACID properties - atomicity, consistency, isolation, and durability. The different states of a transaction are outlined as active, partially committed, failed, aborted, and committed. Sample code is provided to demonstrate how to use START TRANSACTION and COMMIT commands to successfully transfer money between accounts in a transaction.
Transaction Processing; Concurrency control; ACID properties; Schedule and Discoverability; Serialization; Concurrency control and Recovery; Two Phase locking; Deadlock Shadow Paging
Transaction is a unit of program execution that accesses and possibly updates various data items.
Usually, a transaction is initiated by a user program written in a high-level data-manipulation language or programming language (for example, SQL,COBOL, C, C++, or Java), where it is delimited by statements (or function calls) of the form begin transaction and end transaction.
This document discusses mobile database systems and their fundamentals. It describes the conventional centralized database architecture with a client-server model. It then covers distributed database systems which partition and replicate data across multiple servers. The key aspects covered are database partitioning, partial and full replication, and how they impact data locality, consistency, reliability and other factors. Transaction processing fundamentals like atomicity, consistency, isolation and durability are also summarized.
TRANSACTION MANAGEMENT AND TIME STAMP PROTOCOLS AND BACKUP RECOVERYRohit Kumar
The document discusses transactions and concurrency control in database systems. It defines transactions as logical units of work that ensure data integrity during concurrent operations. It describes four key properties of transactions - atomicity, consistency, isolation, and durability (ACID) - and explains how they maintain data correctness. The document also discusses serialization, schedules, locking protocols like two-phase locking, and isolation levels to coordinate concurrent transactions and avoid anomalies like dirty reads.
Similar to Introduction to transaction management (20)
This presentation discusses the following topics:
Basic features of R
Exploring R GUI
Data Frames & Lists
Handling Data in R Workspace
Reading Data Sets & Exporting Data from R
Manipulating & Processing Data in R
Association rule mining is used to find relationships between items in transaction data. It identifies rules that can predict the occurrence of an item based on other items purchased together frequently. Some key metrics used to evaluate rules include support, which measures how frequently an itemset occurs; confidence, which measures how often items in the predicted set occur given items in the predictor set; and lift, which compares the confidence to expected confidence if items were independent. An example association rule evaluated is {Milk, Diaper} -> {Beer} with support of 0.4, confidence of 0.67, and lift of 1.11.
This document discusses clustering, which is the task of grouping data points into clusters so that points within the same cluster are more similar to each other than points in other clusters. It describes different types of clustering methods, including density-based, hierarchical, partitioning, and grid-based methods. It provides examples of specific clustering algorithms like K-means, DBSCAN, and discusses applications of clustering in fields like marketing, biology, libraries, insurance, city planning, and earthquake studies.
Classification is a data analysis technique used to predict class membership for new observations based on a training set of previously labeled examples. It involves building a classification model during a training phase using an algorithm, then testing the model on new data to estimate accuracy. Some common classification algorithms include decision trees, Bayesian networks, neural networks, and support vector machines. Classification has applications in domains like medicine, retail, and entertainment.
The document discusses the assumptions and properties of ordinary least squares (OLS) estimators in linear regression analysis. It notes that OLS estimators are best linear unbiased estimators (BLUE) if the assumptions of the linear regression model are met. Specifically, it assumes errors have zero mean and constant variance, are uncorrelated, and are normally distributed. Violation of the assumption of constant variance is known as heteroscedasticity. The document outlines how heteroscedasticity impacts the properties of OLS estimators and their use in applications like econometrics.
This document provides an introduction to regression analysis. It discusses that regression analysis investigates the relationship between dependent and independent variables to model and analyze data. The document outlines different types of regressions including linear, polynomial, stepwise, ridge, lasso, and elastic net regressions. It explains that regression analysis is used for predictive modeling, forecasting, and determining the impact of variables. The benefits of regression analysis are that it indicates significant relationships and the strength of impact between variables.
MYCIN was an early expert system developed at Stanford University in 1972 to assist physicians in diagnosing and selecting treatment for bacterial and blood infections. It used over 600 production rules encoding the clinical decision criteria of infectious disease experts to diagnose patients based on reported symptoms and test results. While it could not replace human diagnosis due to computing limitations at the time, MYCIN demonstrated that expert knowledge could be represented computationally and established a foundation for more advanced machine learning and knowledge base systems.
The document discusses expert systems, which are computer applications that solve complex problems at a human expert level. It describes the characteristics and capabilities of expert systems, why they are useful, and their key components - knowledge base, inference engine, and user interface. The document also outlines common applications of expert systems and the general development process.
The Dempster-Shafer Theory was developed by Arthur Dempster in 1967 and Glenn Shafer in 1976 as an alternative to Bayesian probability. It allows one to combine evidence from different sources and obtain a degree of belief (or probability) for some event. The theory uses belief functions and plausibility functions to represent degrees of belief for various hypotheses given certain evidence. It was developed to describe ignorance and consider all possible outcomes, unlike Bayesian probability which only considers single evidence. An example is given of using the theory to determine the murderer in a room with 4 people where the lights went out.
A Bayesian network is a probabilistic graphical model that represents conditional dependencies among random variables using a directed acyclic graph. It consists of nodes representing variables and directed edges representing causal relationships. Each node contains a conditional probability table that quantifies the effect of its parent nodes on that variable. Bayesian networks can be used to calculate the probability of events occurring based on the network structure and conditional probability tables, such as computing the probability of an alarm sounding given that no burglary or earthquake occurred but two neighbors called.
This document discusses knowledge-based agents in artificial intelligence. It defines knowledge-based agents as agents that maintain an internal state of knowledge, reason over that knowledge, update their knowledge based on observations, and take actions. Knowledge-based agents have two main components: a knowledge base that stores facts about the world, and an inference system that applies logical rules to deduce new information from the knowledge base. The document also describes the architecture of knowledge-based agents and different approaches to designing them.
A rule-based system uses predefined rules to make logical deductions and choices to perform automated actions. It consists of a database of rules representing knowledge, a database of facts as inputs, and an inference engine that controls the process of deriving conclusions by applying rules to facts. A rule-based system mimics human decision making by applying rules in an "if-then" format to incoming data to perform actions, but unlike AI it does not learn or adapt on its own.
This document discusses formal logic and its applications in AI and machine learning. It begins by explaining why logic is useful in complex domains or with little data. It then describes logic-based approaches to AI that use symbolic reasoning as an alternative to machine learning. The document proceeds to explain propositional logic and first-order logic, noting how first-order logic improves on propositional logic by allowing variables. It also mentions other logics and their applications in areas like automated discovery, inductive programming, and verification of computer systems and machine learning models.
The document discusses production systems, which are rule-based systems used in artificial intelligence to model intelligent behavior. A production system consists of a global database, set of production rules, and control system. The rules fire to modify the database based on conditions. Different control strategies are used to determine which rules fire. Production systems are modular and allow knowledge representation as condition-action rules. Examples of applications in problem solving are provided.
The document discusses game playing in artificial intelligence. It describes how general game playing (GGP) involves designing AI that can play multiple games by learning the rules, rather than being programmed for a specific game. The document outlines how the minimax algorithm is commonly used for game playing, involving move generation and static evaluation functions to search game trees and determine the best move by maximizing or minimizing values at each level.
A study on “Diagnosis Test of Diabetics and Hypertension by AI”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
A study on “Impact of Artificial Intelligence in COVID-19 Diagnosis”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
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Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.
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Introduction to transaction management
1. Department of Information Technology 1Data base Technologies (ITB4201)
Introduction to Transaction concepts
Dr. C.V. Suresh Babu
Professor
Department of IT
Hindustan Institute of Science & Technology
2. Department of Information Technology 2Data base Technologies (ITB4201)
Action Plan
• Transaction processing systems
• Introduction to TRANSACTION
• Need for TRANSACTION
• Operations
• Transaction Execution and Problems
• Transaction States
• Transaction Execution with SQL
• Transaction Properties
• Transaction Log
• Quiz
3. Department of Information Technology 3Data base Technologies (ITB4201)
Transaction processing systems
• Transaction is a logical unit of work that represents real-world events of
any organisation.
• Transaction processing systems execute database transactions with large
databases and hundreds of concurrent users,
for example,
• railway and air reservations systems,
• banking system,
• credit card processing,
• stock market monitoring,
• super market inventory and
• checkouts and so on.
4. Department of Information Technology 4Data base Technologies (ITB4201)
Introduction to TRANSACTION
• A transaction is a logical unit of work of database processing that includes one or more database
access operations.
• A transaction can be defined as an action or series of actions that is carried out by a single user or
application program to perform operations for accessing the contents of the database. The
operations can include
– retrieval (Read)
– insertion (Write)
– deletion and
– modification.
• A transaction must be either completed or aborted.
It can either be embedded within an application program or can be specified interactively via a high-
level query language such as SQL.
• Its execution preserves the consistency of the database.
Each transaction should access shared data without interfering with the other transactions and
whenever a transaction successfully completes its execution; its effect should be permanent.
5. Department of Information Technology 5Data base Technologies (ITB4201)
Need for TRANSACTION
This basic abstraction frees the database application programmer
from the following concerns :
• Inconsistencies caused by conflicting updates from concurrent
users.
• Partially completed transactions in the event of systems failure.
• User-directed undoing of transactions.
• A transaction is a sequence of READ and WRITE actions that are
grouped together to from a database access. A transaction may
consist of a simple SELECT operation to generate a list of table
contents, or it may consist of a series of related UPDATE command
sequences.
6. Department of Information Technology 6Data base Technologies (ITB4201)
Operations
• A transaction can include the following basic database access operations:
Operations Descriptions
Retrieve To retrieve data stored ina database.
Insert To store new data in database.
Delete To delete existing data from database.
Update To modify existing data in database.
Commit To save the work done permanently.
Rollback To undo the work done.
• Transaction that changes the contents of the database must alter the database from one consistent state to
another.
• A consistent database state is one in which all data integrity constraints are satisfied.
To ensure database consistency, every transaction must begin with the database in a known consistent state.
7. Department of Information Technology 7Data base Technologies (ITB4201)
Transaction Execution and Problems
• A transaction which successfully completes its execution is said
to have been committed. Otherwise, the transaction is
aborted.
• Thus, if a committed transaction performs any update
operation on the database, its effect must be reflected on the
database even if there is a failure.
8. Department of Information Technology 8Data base Technologies (ITB4201)
Transaction States
• A transaction can be in one of the following states:
9. Department of Information Technology 9Data base Technologies (ITB4201)
State Description
Active state
• A transaction goes into an active state immediately after it starts execution, where it
can issue READ and WRITE operations.
• A transaction may be aborted when the transaction itself detects an error during
execution which it cannot recover from, for example, a transaction trying to debit loan
amount of an employee from his insufficient gross salary.
• A transaction may also be aborted before it has been committed due to system failure
or any other circumstances beyond its control.
Partially
committed
• When the transaction ends, it moves to the partially committed state. When the last
state is reached.
• To this point, some recovery protocols need to ensure that a system failure will not
result in an inability to record the changes of the transaction permanently.
• Once this check is successful, the transaction is said to have reached its commit point
and enters the committed state.
Aborted
• When the normal execution can no longer be performed.
Failed or aborted transactions may be restarted later, either automatically or after
being resubmitted by the user as new transactions.
Committed
• After successful completion of transaction.
• A transaction is said to be in a committed state if it has partially committed and it can
be ensured that it will never be aborted.
10. Department of Information Technology 10Data base Technologies (ITB4201)
Transaction Execution with SQL
• The American National Standards Institute (ANSI) has defined standards that govern SQL database
transactions. Transaction support is provided by two SQL statements namely COMMIT and
ROLLBACK.
The ANSI standards require that, when a transaction sequence is initiated by a user or an application
program, it must continue through all succeeding SQL statements until one of the following four
events occur :
• A COMMIT statement is reached, in which case all changes are permanently recorded within the
database. The COMMIT statement automatically ends the SQL transaction. The COMMIT operations
indicates successful end-of-transaction.
• A ROLLBACK statement is reached, in which case all the changes are aborted and the database is
rolled back to its previous consistent state. The ROLLBACK operation indicates unsuccessful end-of-
transaction.
• The end of a program is successfully reached, in which case all changes are permanently recorded
within the database. This action is equivalent to COMMIT.
• The program is abnormally terminated, in which case the changes made in the database are aborted
and the database is rolled back to its previous consistent state. This action is equivalent to
ROLLBACK.
11. Department of Information Technology 11Data base Technologies (ITB4201)
Transaction Properties
A transaction must have the following four properties, called
ACID properties (also called ACIDITY of a transaction), to ensure
that a database remains stable state after the transaction is
executed:
• Atomicity.
• Consistency.
• Isolation.
• Durability.
12. Department of Information Technology 12Data base Technologies (ITB4201)
Atomicity
• The atomicity property of a transaction requires that all operations of a
transaction be completed, if not, the transaction is aborted. In other
words, a transaction is treated as single, individual logical unit of work.
Therefore, a transaction must execute and complete each operation in its
logic before it commits its changes.
• As stated earlier, the transaction is considered as one operation even
though there are multiple read and writes. Thus, transaction completes or
fails as one unit.
• The atomicity property of transaction is ensured by the transaction
recovery subsystem of a DBMS.
• In the event of a system crash in the midst of transaction execution, the
recovery techniques undo any effects of the transaction on the database.
13. Department of Information Technology 13Data base Technologies (ITB4201)
Consistency
• Database consistency is the property that every transaction sees a consistent database
instance. In other words, execution of a transaction must leave a database in either its prior
stable state or a new stable state that reflects the new modifications (updates) made by the
transaction.
• If the transaction fails, the database must be returned to the state it was in prior to the
execution of the failed transaction.
• If the transaction commits, the database must reflect the new changes. Thus, all resources
are always in a consistent state.
• The preservation of consistency is generally the responsibility of the programmers who
write the database programs or of the DBMS module that enforces integrity constraints.
• A database program should be written in a way that guarantees that, if the database is in a
consistent state before executing the transaction, it will be in a consistent state after the
complete execution of the transaction, assuming that no interference with other
transactions occur. In other words, a transaction must transform the database from one
consistent state to another consistent state.
14. Department of Information Technology 14Data base Technologies (ITB4201)
Isolation
• Isolation property of a transaction means that the data used
during the execution of a transaction cannot be used by a
second transaction until the first one is completed.
• This property isolates transactions from one another. In other
words, if a transaction T1 is being executed and is using the
data item X, that data item cannot be accessed by any other
transaction (T2………..Tn) until T1 ends.
• The isolation property is enforced by the concurrency control
subsystem of the DBMS.
15. Department of Information Technology 15Data base Technologies (ITB4201)
Durability
• The durability property of transaction indicates the performance of
the database's consistent state. It states that the changes made by
a transaction are permanent.
• They cannot be lost by either a system failure or by the erroneous
operation of a faulty transaction.
• When a transaction is completed, the database reaches a
consistent state and that state cannot be lost, even in the event of
system's failure.
• Durability property is the responsibility of the recovery subsystem
of the DBMS.
16. Department of Information Technology 16Data base Technologies (ITB4201)
Transaction Log (or Journal)
To support transaction processing, DBMSs maintain a transaction record of every change made to the
database into a log (also called journal). For each transaction, the following data is recorded on the log:
A start-of-transaction marker.
• The transaction identifier which could include who and where information.
• The record identifiers which include the identifiers for the record occurrences.
• The operation(s) performed on the records (for example, insert, delete, modify).
• The previous value(s) of the modified data. This information is required for undoing the changes
made by a partially completed transaction. It is called the undo log. Where the modification made by
the transaction is the insertion of a new record, the previous values can be assumed to be null.
• The updated value(s) of the modified record(s). This information is required for making sure that the
changes made by a committed transaction are in fact reflected in the database and can be used to
redo these modifications. This information is called the redo part of the log. In case the modification
made by the transaction is the deletion of a record, the updated values can be assumed to be null.
• A commit transaction marker if the transaction is committed, otherwise an abort or rollback
transaction marker.
17. Department of Information Technology 17Data base Technologies (ITB4201)
Test Yourself
1. With regards to transaction processing, any DBMS should be capable of:
a. Ensuring that transactions are free from interference from other users.
b. Parts of a transaction are not lost due to a failure.
c. Transactions do not make the database inconsistent.
d. All of the above.
2. What is ACID properties of Transactions?
a. Atomicity, Consistency, Isolation, Database
b. Atomicity, Consistency, Inconsistent, Durability
c. Automatically, Concurrency, Isolation, Durability
d. Atomicity, Consistency, Isolation, Durability
3. A transaction completes its execution is said to be
a. Saved b. Loaded c. Rolled d. Committed
4. The deadlock state can be changed back to stable state by using _____________ statement.
a. Commit b. Rollback c. Savepoint d. Deadlock
5. A transaction for which all committed changes are permanent is called:
a. Atomic b. Consistent c. Isolated d. durable
18. Department of Information Technology 18Data base Technologies (ITB4201)
Answers
1. With regards to transaction processing, any DBMS should be capable of:
a. Ensuring that transactions are free from interference from other users.
b. Parts of a transaction are not lost due to a failure.
c. Transactions do not make the database inconsistent.
d. All of the above.
2. What is ACID properties of Transactions?
a. Atomicity, Consistency, Isolation, Database
b. Atomicity, Consistency, Inconsistent, Durability
c. Automatically, Concurrency, Isolation, Durability
d. Atomicity, Consistency, Isolation, Durability
3. A transaction completes its execution is said to be
a. Saved b. Loaded c. Rolled d. Committed
4. The deadlock state can be changed back to stable state by using _____________ statement.
a. Commit b. Rollback c. Savepoint d. Deadlock
5. A transaction for which all committed changes are permanent is called:
a. Atomic b. Consistent c. Isolated d. durable