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Java Captain
Java Captain
Jun 3, 2025 · Backend Development

Implementation of Order Service with Distributed Transactions, Locks, and Asynchronous Processing in Java

This article explains how to build a robust order service using Seata distributed transactions, Redisson distributed locks, CompletableFuture for asynchronous operations, token-based duplicate‑submission prevention, and RabbitMQ delayed queues for automatic order cancellation, with full Java code examples.

Distributed LockJavaRabbitMQ
0 likes · 21 min read
Implementation of Order Service with Distributed Transactions, Locks, and Asynchronous Processing in Java
Architect
Architect
Sep 23, 2024 · Backend Development

Ensuring Idempotency in Order Services: Preventing Duplicate Orders and Solving the ABA Problem

This article explains how to achieve idempotent order creation and updates by using unique request identifiers, database primary‑key constraints, Redis flags, and optimistic locking with version columns, thereby preventing duplicate orders and solving the ABA problem in distributed backend systems.

ABA problemDatabaseIdempotency
0 likes · 11 min read
Ensuring Idempotency in Order Services: Preventing Duplicate Orders and Solving the ABA Problem
Architecture Digest
Architecture Digest
Dec 12, 2023 · Backend Development

Ensuring Idempotency and Solving the ABA Problem in Order Services

This article explains how to achieve idempotent order creation and updates in backend services by using database transactions, unique request identifiers, Redis flags, and optimistic locking with a version column to prevent duplicate submissions and solve the ABA problem.

ABA problemDatabaseIdempotency
0 likes · 10 min read
Ensuring Idempotency and Solving the ABA Problem in Order Services
Architect's Guide
Architect's Guide
Jul 10, 2023 · Backend Development

Ensuring Idempotency in Order Services: Preventing Duplicate Orders and Solving the ABA Problem

This article explains how to prevent duplicate order submissions and address the ABA concurrency issue by using database transactions, unique constraints, request identifiers, and version‑based optimistic locking to achieve reliable idempotent behavior in backend order services.

ABA problemIdempotencyOptimistic Locking
0 likes · 10 min read
Ensuring Idempotency in Order Services: Preventing Duplicate Orders and Solving the ABA Problem
Selected Java Interview Questions
Selected Java Interview Questions
Apr 27, 2023 · Backend Development

Ensuring Idempotency in Order Services: Preventing Duplicate Orders and Solving the ABA Problem

The article explains how to achieve idempotent order creation and update operations by using unique request identifiers, database primary‑key constraints, Redis flags, and version columns to prevent duplicate submissions and resolve ABA anomalies in distributed backend systems.

ABA problemDatabaseIdempotency
0 likes · 10 min read
Ensuring Idempotency in Order Services: Preventing Duplicate Orders and Solving the ABA Problem
Top Architect
Top Architect
Mar 11, 2023 · Backend Development

Designing a Reusable Shared Order Service: Boundary Definition and Internal Architecture

This article explains how to build a highly reusable shared order service by clearly defining its boundaries, abstracting its internal data model and interfaces, and handling order status management with both main and sub‑status mechanisms, while avoiding tight coupling with other services.

Microservicebackend architectureorder service
0 likes · 15 min read
Designing a Reusable Shared Order Service: Boundary Definition and Internal Architecture
Ctrip Technology
Ctrip Technology
Jul 30, 2020 · Backend Development

Design and Implementation of a Distributed Ticket Order Cache System at Ctrip

This article describes how Ctrip's ticket order post‑service team identified scaling bottlenecks, selected Redis, designed a two‑level cache architecture, implemented active and passive caching strategies, tackled consistency and failure issues, and applied various optimizations to achieve over 90% cache hit rate and dramatically reduce database load.

CacheCtripRedis
0 likes · 14 min read
Design and Implementation of a Distributed Ticket Order Cache System at Ctrip