MODERN EDUCATION AND DEVELOPMENT
Выпуск журнала №-23
Часть–1_ Март –2025
370
CREATING AND PROCESSING QUERIES IN TRANSACTION
MANAGEMENT
Turaev Sohibjon Alijon ugli,
Qarshi State Technical University,
Computer engineering student
Abstract: 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.
MODERN EDUCATION AND DEVELOPMENT
Выпуск журнала №-23
Часть–1_ Март –2025
371
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.
MODERN EDUCATION AND DEVELOPMENT
Выпуск журнала №-23
Часть–1_ Март –2025
372
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.
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Выпуск журнала №-23
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