This article explains how to use Redis for distributed locking, discusses the shortcomings of naive implementations, and presents robust solutions including identifier verification, Lua scripting for atomicity, the RedLock algorithm, and Redisson's advanced features such as re‑entrancy and watchdog mechanisms.
This article introduces Lock4j, a Java distributed lock library supporting RedisTemplate, Redisson, and Zookeeper, walks through its key features, dependency setup, configuration, annotation attributes, simple and advanced usage examples, and demonstrates custom executors, key builders, and failure strategies for robust concurrency control.
This article explores the subtle timing of Spring transaction start and commit relative to lock/unlock, demonstrates how improper ordering can cause over‑selling in high‑concurrency scenarios, and provides debugging techniques and practical solutions to ensure atomicity and correct rollback behavior.
This article explains Python multithreading fundamentals, covering thread basics, the _thread and threading modules, creating and managing threads, synchronization with locks, ThreadLocal usage, thread pools, and compares multithreading with multiprocessing for CPU‑bound and I/O‑bound tasks.
This article explains how to prevent multiple simultaneous token requests in a web application by using a custom repeatOnce function that caches the token in localStorage and coordinates pending calls through an event emitter, ensuring only the first request fetches the token while others wait for its result.
Rust 1.80 introduces LazyCell and LazyLock, synchronized lazy-initialization primitives that differ from OnceCell and OnceLock in thread safety and built‑in initialization, and this article explains their characteristics, trade‑offs, and provides concrete code examples to help developers select the appropriate type for their use case.
This article explains how TCP connections are identified, the theoretical maximum numbers for client and server sides, and why real‑world limits are governed by system resources, port reuse, and server architecture rather than the 65,535 port ceiling.
This article provides a comprehensive overview of Python multithreading, covering basic concepts, the _thread and threading modules, thread creation methods, synchronization primitives like Lock and RLock, thread-local storage, thread pools, and the differences between multithreading and multiprocessing for both CPU‑bound and I/O‑bound workloads.
The article explains why a backend team moved from PHP to Go for high‑concurrency live‑streaming services and demonstrates two Go concurrency patterns—sync.WaitGroup and errgroup—with code examples and common pitfalls.
This article explains how to use Go's context package for managing request-scoped data, cancellation, deadlines, and timeouts, compares it with Java's ThreadLocal approach, and provides practical code examples for creating contexts, handling goroutine lifecycles, and applying context in network programming.
This article examines why Kotlin coroutine concepts are hard to explain, identifies common shortcomings in existing tutorials, and proposes a step‑by‑step approach that starts from basic thread concepts, uses incremental examples, and introduces task‑flow techniques to clarify coroutine behavior.
This article presents eight practical retry mechanisms for Java applications—including loop, recursion, HttpClient configuration, Spring Retry, Resilience4j, custom utilities, asynchronous thread‑pool retries, and message‑queue based retries—along with code examples, configuration snippets, and best‑practice guidelines to help developers handle transient network failures reliably.
This article explores Go's built‑in concurrency primitives—including Mutex, RWMutex, Condition variables, atomic operations, sync.Once, and WaitGroup—detailing their purposes, usage patterns, and best‑practice guidelines to write correct and efficient concurrent programs.
This article explains the limitations of ThreadPoolExecutor, introduces the Fork/Join model and ForkJoinPool in Java, demonstrates how to implement custom RecursiveTask and RecursiveAction classes with code examples, discusses pool construction, task submission, work‑stealing, monitoring methods, performance testing, and cautions about using the common pool.
The article explains that Spring MVC controllers are singleton by default, which makes mutable instance fields unsafe for concurrent requests, demonstrates the issue with sample code, and shows how applying @Scope("prototype") or using ThreadLocal resolves the thread‑safety problem.
This article summarizes the common pitfalls, monitoring techniques, configuration guidelines, naming conventions, and practical code examples for safely using Java ThreadPoolExecutor, helping developers avoid OOM, deadlocks, and performance issues while optimizing thread‑pool usage.
This article explains Go's memory management by detailing stack and heap differences, describing classic and modern garbage‑collection algorithms, tracing the evolution of Go's GC from version 1.3 to 1.8, and outlining a complete GC cycle with practical code examples.
The article examines why internet architectures have become increasingly complex, explains the unique challenges of flash‑sale (秒杀) business scenarios, and presents practical backend optimization techniques such as request filtering, Redis caching with atomic operations, ordered queues, data‑layer safeguards, and unit‑based isolation for global deployments.
This article explains Java's lock escalation process—covering biased, lightweight, and heavyweight locks—their underlying mechanisms, performance benefits, and the conditions under which each lock type is applied in multithreaded applications.
Java thread pools efficiently manage and reuse threads by applying a producer‑consumer model, transitioning through RUNNING, SHUTDOWN, STOP, and TERMINATED states, handling task queues, and employing configurable rejection policies such as Abort, CallerRuns, Discard, and DiscardOldest, while improving performance, resource utilization, and stability across web servers, asynchronous processing, and other concurrent workloads, distinct from connection pools which manage database connections.
This article explains how to handle massive MySQL export operations by introducing a fixed‑size FIFO queue, detailing the Java classes ExportQueue, AbstractExport, and ExportImpl, and showing a test controller that demonstrates queue limits, concurrency handling, and future considerations.
This article analyzes why two identical DELETE statements on a MySQL table with a unique index can deadlock, explains InnoDB lock types, walks through the execution flow, reproduces the issue with SQL and Java code, and discusses mitigation strategies.
This article explains how to implement distributed locks using Redis, starting with a basic SETNX approach, identifying its shortcomings, and then presenting robust solutions such as identifier‑based unlocking, Lua scripts for atomicity, the RedLock algorithm, and Redisson’s advanced features including a watchdog mechanism.
This article presents a comprehensive guide to improving Java backend performance by using parallel processing with CompletableFuture, minimizing transaction scope, applying effective caching strategies, configuring thread pools, reducing object creation, and employing various concurrency controls such as volatile, CAS, and read‑write locks.
This article explains why browsers limit concurrent HTTP requests, demonstrates the limitation with a test example, and provides a reusable PromiseLimiter class that queues and throttles asynchronous calls to keep the number of simultaneous requests under a defined threshold.
This article details a step‑by‑step investigation of a JSF thread‑pool exhaustion error that occurred when upgrading the Redis version of JD's internal R2M distributed cache, analyzing stack traces, lock contention, ForkJoinPool behavior, and the eventual remediation steps.
This article explains the concept of false sharing caused by CPU cache line interactions, demonstrates how cache padding can mitigate the performance penalty, and provides Go benchmark code and results to illustrate the impact on multi‑core concurrency.
This article walks through practical Java backend performance techniques—including parallel processing with CompletableFuture, fine‑tuned thread‑pool configuration, transaction scope minimization, cache‑line awareness, object‑pool usage, lock granularity, copy‑on‑write collections, and network payload reduction—backed by concrete code samples, benchmark results, and step‑by‑step analysis of trade‑offs and best practices.
This article explores eleven practical approaches for implementing delayed tasks in Java, covering native APIs like DelayQueue and Timer, thread‑pool executors, popular message‑queue solutions such as RocketMQ and RabbitMQ, as well as Redis‑based techniques, Redisson, Netty, Hutool, Quartz, and simple polling implementations.
This article explores eleven practical methods for implementing delayed tasks in Java, covering native APIs like DelayQueue and Timer, advanced executors such as ScheduledThreadPoolExecutor, and popular messaging solutions including RocketMQ, RabbitMQ, Redis, Redisson, Netty, Hutool, and Quartz, with code demos and implementation details.
This article explains the Fork/Join model and Java's ForkJoinPool, covering the divide‑and‑conquer algorithm, custom RecursiveTask examples, core source‑code analysis, common pool pitfalls, and performance testing to help developers decide when and how to use ForkJoinPool effectively.
This article introduces Gleam, a type‑safe functional language that compiles to Erlang and JavaScript, walks through installation, a hello‑world program, package management, pattern matching with algebraic data types, and demonstrates its concurrency‑friendly, null‑free design.
This article explains the limitations of ThreadPoolExecutor, introduces the Fork/Join model and ForkJoinPool, demonstrates how to implement divide‑and‑conquer tasks with RecursiveTask, provides performance benchmarks, and discusses design details, task submission methods, work‑stealing, and cautions about using the common pool.
This article explains Java virtual threads introduced in Java 19, compares them with traditional OS threads, shows how to enable them in Spring Boot, and presents performance benchmarks that demonstrate dramatic latency reductions for I/O‑bound workloads.
This article explores various MySQL write performance tests using different concurrency levels—Statement, Connection, and database-level parallelism—provides benchmark results, sample Java/Groovy code, and discusses key configuration and architectural factors that influence write throughput.
The article explains why fail‑fast iterators throw ConcurrentModificationException when a collection is modified during iteration, outlines two common scenarios that trigger the exception, and presents both incorrect and correct Java code examples along with strategies such as avoiding modifications, using synchronization, iterator.remove(), or switching to fail‑safe concurrent collections.
This article explains how Java's parallelStream uses the shared ForkJoinPool, why developers may need to customize the thread pool for better performance and isolation, and provides two approaches—setting the system property and creating a dedicated ForkJoinPool—along with complete code examples and execution results.
Huawei unveiled the fully self‑developed Cangjie programming language at the 2024 Developer Conference, detailing its native intelligence, full‑scene support, high performance, strong security, multi‑paradigm features, and simple syntax designed specifically for HarmonyOS applications.
This article explains what Java virtual threads are, compares them with traditional threads, shows how to enable them in SpringBoot with configuration and code examples, and presents performance tests that demonstrate dramatic speed improvements for IO‑bound workloads.
This article describes a real‑world incident where rapid pod scaling caused order‑submission failures in a serverless e‑commerce platform, analyzes the root causes, and presents a Go‑based graceful‑shutdown solution—including ASyncClose, SyncClose, and ForceSyncClose modes—implemented in the open‑source GS library to help developers reliably terminate services.
This article explains how Java's CompletableFuture extends traditional concurrency tools with rich APIs for parallel execution, chaining, error handling, and timeout management, providing clear code examples that demonstrate building maintainable asynchronous applications.
This article analyzes how to import one billion 1 KB log records stored in HDFS or S3 into MySQL by evaluating single‑table limits, choosing storage engines, designing sharding, batch insertion, file‑reading strategies, task coordination, and distributed locking to achieve high‑throughput and ordered writes.
This article provides a comprehensive guide to Java thread pools, covering common interview questions, core parameters, execution flow, lock mechanisms, custom queue implementations, rejection policies, best practices, monitoring strategies, and dynamic tuning with DynamicTp, all illustrated with code examples and diagrams.
The article explores why concurrent programming is notoriously difficult, arguing that the root cause lies not in human cognition but in the combinatorial explosion of possible states and interleavings, and presents heuristics for reducing state space, such as using processes, atomic operations, and language constructs.
This guide explains Python's multithreading and multiprocessing concepts, compares thread pools and process pools, provides practical code examples for task execution and file downloading, and offers best‑practice advice for efficient concurrent programming.
To gracefully shut down a Java thread pool, use ExecutorService's shutdown() to reject new tasks, awaitTermination() to wait for running tasks with optional timeout, handle exceptions, and optionally invoke shutdownNow() for forced termination, as illustrated by code examples from Dubbo3 and RocketMQ.
This article explains the principles and implementation of Java's Compare-and-Swap (CAS) and AbstractQueuedSynchronizer (AQS), illustrating how CAS enables lock‑free algorithms and how AQS underpins high‑level synchronization constructs like ReentrantLock and CountDownLatch, while also providing practical step‑by‑step examples.
This article explains Java virtual threads, compares them with traditional OS threads, shows how to enable them in SpringBoot 3, and presents performance benchmarks demonstrating up to 200‑fold speed improvements for I/O‑bound workloads.
This article explains the structure and components of InnoDB's lock module, including the global lock_sys object, its hash tables, latch mechanisms, waiting thread slots, and related attributes, with detailed code examples and diagrams to illustrate how row and table locks are managed.
This article explains Java virtual threads, contrasting them with platform threads, and shows how to create, schedule, and use them effectively with Thread.Builder and Executors to achieve high‑throughput, low‑latency server applications while avoiding common pitfalls like pooling and pinning.
This article compares Java's standard ThreadLocal with Netty's FastThreadLocal, explains their internal mechanisms, shows practical code examples, runs a JMH microbenchmark, and discusses performance, memory management, and usage scenarios to help developers choose the right thread‑local storage solution.
This article explains the core concepts of Java thread pools, walks through the ThreadPoolExecutor class hierarchy and key methods, analyzes thread‑pool states and execution flow, and provides practical guidelines for configuring parameters, avoiding memory leaks, handling task dependencies, and managing exceptions in production systems.
This article explains what Java virtual threads are, how they differ from regular threads, shows how to enable them in SpringBoot 3.1.2 with Java 20, and presents performance benchmarks that demonstrate up to 200‑fold speed improvements for IO‑bound workloads.
This article explains the concepts of concurrency, parallelism, and serial execution, describes common multi‑core scheduling algorithms, and demonstrates Java's concurrent programming tools—including Future, Fork/Join, Stream API, and CompletableFuture—through clear code examples and practical guidelines.
This article examines the shared and distinct fields of InnoDB's table‑lock and row‑lock structures in MySQL 8.0.32, explains the layout of the lock_t, lock_table_t and lock_rec_t structs, decodes the type_mode bit‑field, and discusses how InnoDB merges compatible row‑locks using a bitmap memory area.
This article explains the various ThreadPoolExecutor rejection policies, highlights the risks of using CallerRunsPolicy, provides code examples, and suggests mitigation strategies such as adjusting queue size, thread count, or persisting overflow tasks to databases or message queues.
This article explains the concept of context switching, compares process, thread, and coroutine switches, and details how Go’s M:N scheduler implements low‑cost coroutine switches with examples, costs, and optimization tips for writing efficient concurrent programs.
This article analyses the memory consumption of tasks submitted to a Java ThreadPoolExecutor using execute and submit, compares lambda and queue implementations, and quantifies the overhead of internal objects such as Worker, Node, FutureTask, and RunnableAdapter.
The article explains why a backend developer moved from PHP to Go, highlights Go’s popularity and simplicity, and demonstrates how Go’s concurrency primitives like sync.WaitGroup and errgroup can transform serial live‑stream data fetching into parallel execution, drastically reducing request latency.
This article explains the classic producer‑consumer synchronization challenge, describes its importance in concurrent programming, and provides two complete C implementations—one using mutexes and condition variables and another using semaphores—along with detailed code and sample output.
This article traces the history of the Python Global Interpreter Lock, explains why it remains a performance bottleneck, and examines recent efforts such as multiprocessing, PEP 554, and sub‑interpreters that aim to mitigate or eliminate the GIL in CPython.
This article explains several common technical solutions—locking queues, update‑statement limits, optimistic locking, temporary tables, and Redis pre‑stocking—to prevent inventory overselling, comparing their suitability for different concurrency levels and recommending the best approach for high‑traffic scenarios.
This article explains the purpose of Go's internal/race package, how the -race compiler flag enables automatic data race detection, provides step‑by‑step usage commands, demonstrates a practical example with code, and outlines the underlying detection mechanism.
This article explains why threads are essential for performance, how to create and configure Java thread pools using the Executors utility, distinguishes CPU, IO, and scheduled pool types, and demonstrates monitoring techniques for latency and deadlock detection with practical code examples.
The article presents a suite of interview‑style algorithm and system‑design solutions—including Bloom‑filter URL blacklists, hash‑partitioned word frequencies, missing‑number bit arrays, top‑K min‑heap, low‑memory median, short‑URL encoding, Redis user counting, and extensive Java implementations of sorting, singleton, LRU cache, custom thread pools, producer‑consumer models and various FooBar synchronization techniques.
This article explains the timing of Spring's @Transactional commit relative to lock release, analyzes why committing after unlock can cause overselling, shows how to trace the transaction lifecycle in the source code, and offers practical solutions to ensure atomicity in high‑concurrency scenarios.
Disruptor is an open‑source, lock‑free Java framework that uses a ring‑buffer and sequencer to achieve ultra‑high‑throughput, handling millions of events per second, and is employed by projects like LMAX, Storm, Camel, and Log4j2, with detailed concepts, wait strategies, and usage examples.
This article explains the Snowflake distributed ID algorithm, breaks down the Go implementation in the bwmarrin/snowflake package, and details how initialization, node validation, timestamp handling, and bit‑wise composition work together to produce unique, time‑ordered 64‑bit identifiers in high‑concurrency environments.
This guide explains how Spring Boot 3.2+ leverages JDK 21 virtual threads, demonstrates common pitfalls in non‑web applications—especially daemon thread termination—and shows how to enable keep‑alive configuration to ensure your tasks keep running, complete with code examples and performance insights.
The article explains that SpringBoot’s request capacity is governed by Tomcat’s thread pool and connection settings, derives the formula max‑connections + accept‑count, demonstrates it with a small‑scale experiment, and discusses related concurrency pitfalls in singleton beans.
This article provides an in‑depth overview of Python's multiprocessing module, covering process creation, inter‑process communication, synchronization primitives, error handling, debugging tools, and real‑world project examples to help developers efficiently leverage multi‑core CPUs for CPU‑bound tasks.
This article explains how to solve Java thread‑pool priority problems by leveraging java.util.concurrent.PriorityBlockingQueue, details its thread‑safe and unbounded features, and provides a complete multi‑priority thread‑pool implementation with sample code and a test demonstrating correct task ordering.
This article explains how to design and implement a fixed‑size FIFO export queue in a Java Spring application to control concurrent MySQL data exports, detailing the related entities, code implementation with EasyExcel, a test controller, and observed results.
This article explains why asynchronous programming improves performance, compares serial and parallel implementations of a login flow, and demonstrates how to use Java's CompletableFuture API—including supplyAsync, runAsync, callbacks, composition, and error handling—to write efficient backend code.
This article explains why standard ThreadLocal mechanisms fail with thread pools, introduces the design of a custom solution using YesThreadLocal and YesRunnable, and then details how Alibaba's TransmittableThreadLocal (TTL) implements context capture, replay, and restoration for seamless asynchronous execution.
This article explains how to design and implement a fixed-size FIFO export queue in a Spring Boot backend, using synchronized methods, EasyExcel for large data exports, and a test controller to simulate concurrent export requests, while discussing performance considerations and future enhancements.
This comprehensive guide covers Java's core concepts—including object‑oriented principles, differences from C++, polymorphism, static/final modifiers, abstract classes versus interfaces, generics, reflection, exception hierarchy, key data structures like ArrayList, LinkedList, HashMap, ConcurrentHashMap, serialization, String handling, and essential design patterns such as Singleton, Factory, and Abstract Factory—providing interview‑ready knowledge for developers.
In Spring Boot, using @Transactional and @Async on the same service method does not invalidate the transaction, but the asynchronous execution runs in a separate thread with its own transaction, isolated from the original thread's transaction due to AOP interceptor ordering.
This article explains how Redisson leverages Redis to implement distributed locks, detailing the underlying Lua scripts, lock acquisition and release processes, the watch‑dog mechanism for automatic lease renewal, and provides Java code examples for integrating and testing the lock functionality.
This article explains the motivation, design principles, and implementation details of Conecta, a lightweight, configurable Go library that provides a universal connection pool for various services such as databases, TCP/UDP, and custom connections, complete with extensible callbacks and background health checks.
The article explains Go’s built‑in Goroutine concurrency model and introduces the For‑Select‑Done design pattern, detailing its three components, ideal use cases, a complete code example, and the benefits of improved readability, flow control, and resource‑leak prevention.
This article explains how to implement non‑blocking channel operations in Go using the select statement with a default case, provides detailed code examples for both sending and receiving, and analyzes the benefits, challenges, and practical use cases in high‑performance concurrent systems.
Learn practical ways to enhance a system’s concurrent handling capacity, including traffic distribution via load balancers, database sharding and clustering, message queues, caching layers, CDNs, code and database optimizations, and scaling hardware resources such as servers, CPUs, and memory.
This article introduces PHP’s curl_multi_exec() function, explains its prototype, parameters, return values, provides a complete example for concurrently sending multiple HTTP requests, and outlines important usage considerations for efficient backend network communication.
This article explains Go's native concurrency model, covering lightweight goroutines, channel communication patterns, scheduling details, and demonstrates a practical web‑crawler example that leverages these features for efficient parallel processing.
This article explains the core concepts of Kotlin coroutines, including what they are, how they differ from threads, the mechanics of suspension and resumption, the role of the suspend keyword, and practical code examples that illustrate their usage in Android development.
This article introduces Spring 6.2’s Parallel Bean Initialization feature, explains its benefits for reducing startup time, provides step‑by‑step code examples for configuring background bean initialization and a bootstrap executor, compares traditional and concurrent initialization timings, and details the underlying implementation in the Spring container.
This article explains Go's channel fundamentals, demonstrates how to create and use channels to synchronize multiple goroutines with practical code examples, and visualizes the process with a UML sequence diagram for clearer understanding.
This article examines Go's sync package, detailing how WaitGroup coordinates the completion of multiple goroutines while Mutex protects shared resources, compares their purposes and use cases, and provides practical code examples to help developers choose the right tool for concurrent programming.
This article investigates how Java's java.util.concurrent.ExecutorService thread pools react to exceptions when tasks are submitted via execute versus submit, providing source‑code experiments, observed outcomes, and a detailed analysis of the underlying JDK implementation.
This article compiles common Java bugs such as NullPointerException, thread‑safety issues, improper exception handling, and performance traps, and provides practical solutions including annotations, Optional, MapStruct, concurrent utilities, immutable objects, proper resource management, and Spring transaction safeguards.
This article explains why performance optimization is essential for growing systems, introduces key metrics such as response time and concurrency, outlines systematic thinking and concrete techniques—including caching, parallelism, and async processing—and demonstrates a live‑streaming case study with actionable solutions.
This article compiles a set of Java interview questions covering the differences between ArrayList and LinkedList, the internal workings and resizing of HashMap, concurrency primitives like synchronized and ReentrantLock, JVM memory layout, garbage‑collection algorithms, reference types, and Redis persistence and distributed‑lock mechanisms.
This tutorial explains how to download regular files, web pages, Amazon S3 objects, and other resources in Python by covering multiple modules such as requests, wget, urllib, urllib3, Boto3, and asyncio, and demonstrates handling redirects, large files, parallel downloads, progress bars, proxies, and asynchronous execution.
This article explains the purpose, usage patterns, JVM-level object header and monitor mechanisms, lock state transitions, and lock‑upgrade strategies of Java's synchronized keyword, providing code examples and visual diagrams to illustrate how thread synchronization is achieved internally.
This article examines why HikariCP, the default Spring Boot 2.0 connection pool, achieves high performance by exploring its design concepts such as dual HikariPool instances, FastList, custom ConcurrentBag, thread‑local caching, and bytecode optimization, and includes sample Maven configuration and Java code.
This guide compares Python's synchronous requests library with the asynchronous grequests wrapper, showing when to choose each approach and providing clear code examples for single-threaded, multi-threaded, timeout‑controlled, and exception‑handled HTTP requests.
This comprehensive guide covers high‑performance development techniques—including I/O optimization, zero‑copy, multiplexing, concurrency, thread‑pool design, lock‑free programming, inter‑process communication, RPC, serialization, database indexing, caching strategies, Bloom filters, full‑text search, and load balancing—to help developers build fast, scalable, and reliable systems.
The article outlines the three‑step inventory deduction workflow—select, verify, update—and explains how concurrent requests can cause overselling, then compares mitigation strategies such as pessimistic SELECT FOR UPDATE locks, optimistic CAS version retries, atomic decrement SQL statements, and Redis transactions, highlighting their trade‑offs in consistency and throughput.
Go’s Context package provides a simple, standardized way to control goroutine lifecycles, enforce timeouts, cancel operations, and pass request-scoped values, embodying Go’s philosophy of clarity and efficiency; this article outlines its key characteristics, design philosophy, and demonstrates practical HTTP cancellation with code.
