THE ROLE OF XML AND DATABASES IN SOCIETY

Аннотация

Transaction management is a fundamental aspect of database systems, ensuring data integrity, consistency, and reliability. Query processing within transactions plays a crucial role in maintaining atomicity, consistency, isolation, and durability (ACID properties). This paper explores the methods for creating and processing queries in transaction management, focusing on SQL-based and NoSQL approaches. It discusses transaction control mechanisms, query optimization techniques, and concurrency control strategies. Additionally, case studies demonstrate best practices in query execution within transactional environments, highlighting performance considerations and error-handling techniques. Keywords: Transaction Management, Query Processing, ACID Properties, Concurrency Control, SQL, NoSQL, Query Optimization, Database Transactions. Transaction management is essential for maintaining data integrity in multi- user database environments. It ensures that database operations are executed in a reliable and consistent manner. Query creation and processing within transactions involve optimizing execution plans, managing concurrent access, and ensuring compliance with ACID properties. This paper examines these aspects and explores how different database models handle transaction queries. Transaction Management and ACID Properties. A transaction is a sequence of database operations that must be executed as a single logical unit. The ACID properties ensure that: Atomicity: Transactions are either fully completed or fully rolled back. Consistency: Transactions maintain database integrity. Выпуск журнала №-23 Часть–1_ Март –2025 370 MODERN EDUCATION AND DEVELOPMENT Isolation: Transactions do not interfere with each other. Durability: Committed transactions are permanently recorded. Query Creation in Transaction Management: 1. SQL-Based Transactions Structured Query Language (SQL) supports transactions using commands such as: BEGIN TRANSACTION: Initiates a transaction. COMMIT: Saves all changes made in the transaction. ROLLBACK: Reverts changes in case of failure. SAVEPOINT: Creates a checkpoint for partial rollbacks. Example: BEGIN TRANSACTION; UPDATE accounts SET balance = balance - 500 WHERE account_id = 1; UPDATE accounts SET balance = balance + 500 WHERE account_id = 2; IF @@ERROR 0 ROLLBACK; ELSE COMMIT; 2. NoSQL Transactions. NoSQL databases, such as MongoDB and Cassandra, provide transaction support for multi-document operations. Unlike SQL, transactions in NoSQL rely on distributed consistency models and optimistic concurrency control. Example (MongoDB): session.startTransaction(); db.accounts.updateOne({account_id: 1}, {$inc: {balance: -500}}, {session}); db.accounts.updateOne({account_id: 2}, {$inc: {balance: 500}}, {session}); session.commitTransaction(); Query Processing and Optimization. Efficient query processing in transaction management requires optimization techniques such as: Indexing: Enhances query performance by reducing lookup time. Query Execution Plans: Uses cost-based optimization to select efficient query execution strategies. Caching: Reduces repeated computations for frequently executed queries. Выпуск журнала №-23 Часть–1_ Март –2025 371 MODERN EDUCATION AND DEVELOPMENT Partitioning: Distributes data across multiple nodes for better scalability. Concurrency Control in Transaction Queries. Managing concurrent transactions is crucial for preventing issues like deadlocks, lost updates, and dirty reads. Concurrency control techniques include: Pessimistic Locking: Locks resources until a transaction is completed. Optimistic Concurrency Control (OCC): Allows multiple transactions but checks for conflicts before committing. Multiversion Concurrency Control (MVCC): Maintains multiple versions of data to support concurrent reads and writes. Case Studies and Practical Applications. Case Study 1: Banking System Transactions. A banking application requires robust transaction management to process money transfers. The system ensures atomicity by rolling back incomplete transactions in case of failure. Case Study 2: E-Commerce Order Processing. In e-commerce applications, transactions involve inventory management, payment processing, and order confirmation. Query optimization techniques such as indexing and caching improve performance. Query creation and processing in transaction management are vital for ensuring data integrity and performance in database systems. By leveraging SQL and NoSQL transaction mechanisms, query optimization strategies, and concurrency control techniques, databases can handle complex transactional workloads efficiently. Future advancements in distributed transaction models and AI-driven query optimization will further enhance transaction management capabilities.